CN120263891A

CN120263891A - A method and system for detecting linear defects of OLED mobile phone screens

Info

Publication number: CN120263891A
Application number: CN202510755073.XA
Authority: CN
Inventors: 蔡振; 许雅静
Original assignee: Shenzhen Kutong Xiaoyang Technology Co ltd
Current assignee: Shenzhen Small Sample Intelligent Display Technology Co.,Ltd.
Priority date: 2025-06-06
Filing date: 2025-06-06
Publication date: 2025-07-04
Anticipated expiration: 2045-06-06
Also published as: CN120263891B

Abstract

The present invention relates to the field of mobile phone detection technology, and in particular to a method and system for detecting linear defects of OLED mobile phone screens. The present invention obtains a vibration time domain signal within a preset time period on the screen surface, so that it does not depend on the display brightness of the screen, obtains the defect position through the abnormal signal interval, thereby avoiding misjudgment caused by uneven display image brightness, uses a spectral image to capture the spectral data of each pixel, and can effectively eliminate the influence of ambient light and display brightness. Defects are analyzed by the gradient amplitude of the spectral data, which can reduce misjudgments caused by light changes and screen brightness differences. By analyzing the gradient amplitude to distinguish abnormal pixels from normal pixels, subtle differences between pixels can be more accurately identified. By obtaining the parameter characteristics of each abnormal pixel, the characteristics of the defect can be more comprehensively described, thereby improving the accuracy of defect identification. By evaluating the degree of defects through parameter characteristics, a more accurate evaluation of the degree of defects can be obtained.

Description

OLED mobile phone screen linear defect detection method and system

Technical Field

The invention relates to the technical field of mobile phone detection, in particular to a method and a system for detecting linear defects of an OLED mobile phone screen.

Background

The OLED (organic light emitting diode) is a display technology, and is mainly characterized in that each pixel point is made of an organic material and can emit light autonomously, unlike a traditional LCD screen, the OLED does not need a backlight source, and each displayed pixel can be controlled independently, so that the OLED has higher contrast, brighter color, darker black display, and thinner screen, and the linear defect of the mobile phone screen refers to a vertical or horizontal linear defect which does not meet the normal display effect in the display area of the OLED screen, and the defects are usually represented as black lines with inconsistent brightness, distorted color or no display at all.

In the prior art, the main detection method of the linear defect of the OLED mobile phone screen is to identify the linear or linear defect in the image by acquiring the display image of the OLED screen and applying algorithms such as image filtering, edge detection or linear detection, etc., but the image processing method generally depends on the display brightness of the screen, and any change of ambient light can influence the detection effect, so that the detection algorithm cannot be effectively identified, and the result of detecting the defect degree is inaccurate.

Disclosure of Invention

The invention mainly aims to provide a linear defect detection method for an OLED mobile phone screen, and aims to solve the technical problems in the prior art.

The invention provides a linear defect detection method for an OLED mobile phone screen, which comprises the following steps:

acquiring a plurality of vibration time domain signals in a preset time period on the surface of an OLED mobile phone screen, and carrying out Fourier transform processing on each vibration time domain signal to obtain a corresponding vibration frequency domain signal;

Performing synchronous alignment calibration on a plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals;

Acquiring an abnormal signal interval according to a plurality of synchronous vibration signals, and acquiring vibration abnormality according to the abnormal signal interval;

Judging whether the vibration anomaly is greater than a preset anomaly;

If the vibration anomaly degree is larger than the preset anomaly degree, judging that the OLED mobile phone screen has a linear defect, and acquiring the linear defect position of the OLED mobile phone screen according to the anomaly signal interval;

Acquiring a spectrum image of a linear defect position in an OLED mobile phone screen, and acquiring spectrum data of each pixel point according to the spectrum image;

Acquiring corresponding gradient amplitude values according to each spectrum data, and determining abnormal pixel points and normal pixel points according to the gradient amplitude values;

and acquiring the parameter characteristics of each abnormal pixel point, and acquiring a defect degree value according to a plurality of parameter characteristics.

Preferably, the step of performing synchronous alignment calibration on the plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals includes:

Removing direct current components in each vibration frequency domain signal by adopting a high-pass filter to obtain a plurality of dynamic vibration signals, and sequentially denoising and normalizing each dynamic vibration signal to obtain a corresponding standard vibration signal;

Sorting the plurality of standard vibration signals according to time sequence, marking the standard vibration signal arranged at the first position as a reference vibration signal, and marking the rest standard vibration signals as calibration vibration signals;

acquiring a first initial time point of the reference vibration signal and a second initial time point of each calibration vibration signal, and acquiring a corresponding hysteresis value according to the first initial time point and each second initial time point;

And obtaining corresponding cross-correlation coefficients according to the reference vibration signals, each hysteresis value and the corresponding calibration vibration signals, and carrying out translation on a time axis according to the corresponding calibration vibration signals of each cross-correlation coefficient to obtain a plurality of synchronous vibration signals.

Preferably, the step of acquiring the abnormal signal section from the plurality of synchronous vibration signals includes:

Acquiring first amplitudes of each synchronous vibration signal at each time point, and carrying out weighted average processing according to a plurality of first amplitudes at each time point to obtain a composite vibration signal;

acquiring a first amplitude at each frequency point according to the composite vibration signal, and acquiring a corresponding power spectral density according to each first amplitude;

Establishing a frequency-density coordinate axis by taking the frequency as an X axis and the power spectral density as a Y axis, and drawing the power spectral density corresponding to each frequency on the frequency-density coordinate axis as a connection point;

sequentially connecting a plurality of connection points through curves to obtain a power spectrum waveform diagram, and obtaining the peak value and the valley value of the power spectrum waveform diagram;

dividing a power spectrum waveform diagram into a plurality of curves according to two adjacent peaks and valleys, obtaining the curvature of each curve, and judging whether the curvature is larger than a preset threshold value or not;

and if the curvature is larger than a preset threshold, judging that the curve corresponding to the curvature is an abnormal curve, and acquiring an abnormal signal section according to the abnormal curve and the power spectrum waveform diagram.

Preferably, the step of acquiring vibration anomaly from the anomaly signal section includes:

Acquiring an abnormal frequency component of each frequency point according to the abnormal signal interval, acquiring a historical frequency component of each same frequency point in the historical normal signal of the OLED mobile phone screen, and acquiring a frequency offset according to a plurality of historical frequency components and the abnormal frequency components;

Acquiring the total frequency band number, the maximum frequency and the minimum frequency according to the abnormal signal interval, and acquiring the center frequency of each frequency band according to the total frequency band number, the maximum frequency and the minimum frequency;

Dividing an abnormal signal interval into a plurality of frequency interval sections according to each central frequency, acquiring a second amplitude of each frequency interval section, acquiring energy density of a corresponding frequency interval section according to each second amplitude, and acquiring energy of a corresponding abnormal frequency according to each energy density;

Acquiring a plurality of historical frequency energies in the historical normal signals of the OLED mobile phone screen, acquiring frequency energy anomaly degrees according to the historical frequency energies and the abnormal frequency energies, and acquiring vibration anomaly degrees according to the frequency energy anomaly degrees and the frequency offset degrees.

Preferably, the step of acquiring a corresponding gradient amplitude according to each spectrum data and determining an abnormal pixel point and a normal pixel point according to the gradient amplitude includes:

acquiring a left pixel value and a right pixel value of a corresponding pixel point in the horizontal direction according to each spectrum data, and acquiring a corresponding horizontal gradient according to each left pixel value and each right pixel value;

Acquiring an upper pixel value and a lower pixel value of a corresponding pixel point in the vertical direction according to each spectrum data, and acquiring a corresponding vertical gradient according to each upper pixel value and each lower pixel value;

acquiring corresponding gradient amplitude values according to each horizontal gradient and each vertical gradient, and judging whether the gradient amplitude values are larger than a preset gradient or not;

If the gradient amplitude is larger than the preset gradient, judging the pixel point corresponding to the gradient amplitude as an abnormal pixel point;

if the gradient amplitude is not greater than the preset gradient, the pixel point corresponding to the gradient amplitude is judged to be a normal pixel point.

Preferably, the step of obtaining the defect degree value according to a plurality of the parameter features includes:

acquiring pixel areas of corresponding abnormal pixel points and a plurality of first abnormal principal component characteristic values according to each parameter characteristic;

Obtaining a defect total area of a linear defect position in an OLED mobile phone screen, and obtaining an abnormal pixel defect occupation ratio according to the defect total area and a plurality of pixel areas;

acquiring corresponding abnormal average characteristic values according to the characteristic values of the abnormal main components of each abnormal pixel point;

Acquiring a plurality of historical normal principal component characteristic values of normal pixel points corresponding to each same abnormal pixel point in the historical normal spectrum image of the OLED mobile phone screen, and acquiring a corresponding normal average characteristic value according to the plurality of historical normal principal component characteristic values of each normal pixel point;

and obtaining an abnormal characteristic difference duty ratio according to the normal average characteristic values and the abnormal average characteristic values, and obtaining a defect degree value according to the abnormal characteristic difference duty ratio and the abnormal pixel defect duty ratio.

The application also provides an OLED mobile phone screen linear defect detection system, which comprises:

The first acquisition module is used for acquiring a plurality of vibration time domain signals in a preset time period on the surface of the OLED mobile phone screen, and carrying out Fourier transform processing on each vibration time domain signal to obtain a corresponding vibration frequency domain signal;

the calibration module is used for synchronously aligning and calibrating the vibration frequency domain signals to obtain synchronous vibration signals;

the second acquisition module is used for acquiring an abnormal signal interval according to the synchronous vibration signals and acquiring vibration abnormality according to the abnormal signal interval;

the judging module is used for judging whether the vibration anomaly degree is larger than a preset anomaly degree or not;

The third acquisition module is used for acquiring a spectrum image of a linear defect position in the OLED mobile phone screen and acquiring spectrum data of each pixel point according to the spectrum image;

The determining module is used for acquiring corresponding gradient amplitude values according to each spectrum data and determining abnormal pixel points and normal pixel points according to the gradient amplitude values;

And the fourth acquisition module is used for acquiring the parameter characteristics of each abnormal pixel point and acquiring a defect degree value according to a plurality of parameter characteristics.

Preferably, the fourth acquisition module includes:

The first acquisition unit is used for acquiring the pixel area of the corresponding abnormal pixel point and a plurality of first abnormal principal component characteristic values according to each parameter characteristic;

The second acquisition unit is used for acquiring the defect total area of the linear defect position in the OLED mobile phone screen and acquiring the defect occupation ratio of the abnormal pixel according to the defect total area and the pixel areas;

The third acquisition unit is used for acquiring a corresponding abnormal average characteristic value according to the characteristic values of the plurality of abnormal principal components of each abnormal pixel point;

The fourth acquisition unit is used for acquiring a plurality of historical normal principal component characteristic values of the normal pixel points corresponding to each identical abnormal pixel point in the historical normal spectrum image of the OLED mobile phone screen, and acquiring a corresponding normal average characteristic value according to the plurality of historical normal principal component characteristic values of each normal pixel point;

And a fifth obtaining unit, configured to obtain an abnormal feature difference duty ratio according to the plurality of normal average feature values and abnormal average feature values, and obtain a defect level value according to the abnormal feature difference duty ratio and the abnormal pixel defect duty ratio.

The invention also provides computer equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the OLED mobile phone screen linear defect detection method when executing the computer program.

The invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, realizes the steps of the method for detecting the linear defect of the OLED mobile phone screen.

The method has the advantages that vibration time domain signals in a preset time period of the surface of the screen are acquired, the vibration time domain signals are independent of display brightness of the screen, detection stability and reliability are guaranteed, the vibration signals are not affected by ambient light intensity changes through analysis, high-frequency information can be acquired through Fourier transform processing of a plurality of vibration signals, fine anomalies in vibration are accurately captured, detection sensitivity is improved, a plurality of synchronous vibration frequency domain signals are acquired, vibration anomaly degree is calculated, a more objective and quantitative defect measurement standard can be provided, defect positions are acquired through an anomaly signal interval, display content and screen brightness are not depended, misjudgment caused by display image brightness unevenness or ambient light changes is avoided, spectral data of each pixel are captured through a light spectrum image, the influence of ambient light and display brightness can be effectively eliminated, defects are analyzed through gradient amplitude of the spectral data, misjudgment caused by light changes and screen brightness differences can be reduced, abnormal pixels and pixels can be distinguished through analysis of gradient amplitude, the accurate characteristics can be accurately and comprehensively evaluated through the fact that the characteristics of the pixels are different from each other, and the defects can be accurately estimated through the characteristics.

Drawings

FIG. 1 is a flow chart of a method according to an embodiment of the invention.

Fig. 2 is a schematic diagram of a system structure according to an embodiment of the invention.

Fig. 3 is a schematic diagram illustrating an internal structure of a computer device according to an embodiment of the application.

The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

As shown in fig. 1-3, the present application provides a method for detecting linear defects of an OLED mobile phone screen, including:

S1, acquiring a plurality of vibration time domain signals in a preset time period on the surface of an OLED mobile phone screen, and performing Fourier transform processing on each vibration time domain signal to obtain a corresponding vibration frequency domain signal;

s2, carrying out synchronous alignment calibration on a plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals;

S3, acquiring an abnormal signal interval according to the synchronous vibration signals, and acquiring vibration anomaly degree according to the abnormal signal interval;

S4, judging whether the vibration anomaly degree is larger than a preset anomaly degree or not;

s5, acquiring a spectrum image of a linear defect position in the OLED mobile phone screen, and acquiring spectrum data of each pixel point according to the spectrum image;

S6, acquiring corresponding gradient amplitude values according to each spectrum data, and determining abnormal pixel points and normal pixel points according to the gradient amplitude values;

s7, acquiring parameter characteristics of each abnormal pixel point, and acquiring a defect degree value according to a plurality of parameter characteristics.

In the steps S1-S7, the invention obtains a plurality of vibration time domain signals on the surface of the OLED mobile phone screen within a preset time period, performs Fourier transform processing on each vibration time domain signal to obtain a corresponding vibration frequency domain signal, performs synchronous alignment calibration on the plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals, namely, synchronously aligns and calibrates a plurality of vibration frequency domain signals on the surface of the OLED mobile phone screen at different time points to the same time point so as to eliminate time deviation among the signals, ensures the synchronism of the vibration signals, obtaining an abnormal signal interval through a plurality of synchronous vibration signals, obtaining vibration abnormal degree according to the abnormal signal interval, judging whether the vibration abnormal degree is larger than a preset abnormal degree, if the vibration abnormal degree is larger than the preset abnormal degree, judging that the OLED mobile phone screen has a linear defect, conventional methods for detecting linear defects of an OLED screen are generally performed by analyzing a display image of the screen, and are severely dependent on brightness and display contents of the screen if the display brightness is unstable or due to a change in ambient light (e.g., light reflection, Ambient light intensity change and the like) can interfere with the detection effect to cause inaccuracy of the detection result, but the vibration time domain signal is the change process of the vibration signal recorded on the time axis in a preset time period of the screen surface, the vibration time domain signal can reflect the intensity or amplitude of vibration of an object, help judge whether the object excessively vibrates or not, whether abnormal vibration behaviors (such as linear defects of an OLED mobile phone screen) exist or not are helped, so that the vibration time domain signal can be obtained by obtaining the vibration time domain signal so as to enable the vibration time domain signal not to depend on the display brightness of the screen, and the acquisition of the vibration time domain signal is irrelevant to the display content of the screen, thereby avoiding the influence of external ambient light on the detection, ensuring the detection stability and reliability, ensuring the acquisition of the vibration signal to be free from the influence of the change of the ambient light intensity, and not affecting the detection result no matter how the ambient light condition changes, the vibration time domain signal can still maintain high accuracy under different illumination conditions, the vibration time domain signal can be better adaptive, a plurality of vibration time domain signals can be obtained by Fourier transformation, the high-frequency information in the vibration frequency signals can be accurately obtained, the vibration time domain signal can be captured, the vibration time domain signal can be accurately and accurately acquired in the vibration frequency domain signal can be more accurate than the vibration time domain signal, and can be obtained by the vibration time domain signal can be accurately, and the vibration time domain signal can be accurately has the same as the vibration signal has the vibration signal Acquisition time or other external factors (e.g., ambient noise, A small error of the device, etc.), each vibration signal may have a deviation in time, for example, the signals from different sensors may be slightly advanced or delayed, resulting in inconsistent time alignment between them, if the signals are not synchronously aligned, they are directly combined and analyzed, which may mislead understanding of the vibration mode, and affect accuracy of defect detection, when a plurality of vibration signals are synchronously aligned, the vibration mode of the whole screen surface may be revealed more clearly, thereby helping to identify whether a local defect or a non-uniform vibration feature exists, a more objective and quantitative defect measurement standard may be provided, if the vibration anomaly degree exceeds a preset threshold, the OLED screen may be determined to have a linear defect very clearly, because when a plurality of vibration signals are subjected to fourier transformation and are synchronously aligned, and thus change of each vibration frequency domain signal is analyzed, a portion different from a normal mode is identified, that is an abnormal signal interval, which may be generally represented by frequency peak value offset or peak value increase, and the like, and when the vibration anomaly degree exceeds a preset threshold, which means that the vibration anomaly degree is more clearly corresponds to the frequency peak value, the abnormal signal is more clearly, the normal frequency domain signal is converted to the abnormal frequency domain signal, and the abnormal frequency domain signal is converted into a normal frequency domain signal, which is compared to have a significant amplitude of the vibration defect, and the normal error is detected by the normal error, and the normal frequency domain signal is detected by the normal error is more clearly, and the normal error is detected by the normal error, and the vibration has been significantly detected by the vibration signal, the frequency domain signal processing can effectively filter noise and redundant information in the signals, improve the signal quality, enable the subsequent abnormal signal analysis to be more accurate, further improve the recognition accuracy of the abnormal signals, enable the frequency domain analysis to capture the frequency fluctuation caused by the linear defects more clearly, further improve the detection accuracy and stability, greatly improve the automation and intelligent level of the detection process by utilizing the automatic vibration signal acquisition and the frequency domain analysis, judge whether the defects exist or not by setting a threshold value, and enable the whole detection process to be efficient, The method is precisely completed, reduces human intervention, improves the detection efficiency of a production line, improves the quality control level of an OLED mobile phone screen, acquires the linear defect position of the OLED mobile phone screen according to an abnormal signal interval, and is characterized in that the position of the abnormal signal on the screen can be determined by analyzing the frequency domain characteristics in the abnormal signal interval, particularly, the abnormality of the vibration frequency domain signal is usually concentrated in a defect area, so that the defect position can be estimated by combining the frequency distribution of the abnormal signals, for example, the linear defect is usually represented as a vibration abnormal section parallel to the edge or the center of the screen on the surface of the OLED mobile phone screen, the fluctuation of the abnormal signal on the line can be relatively consistent, the position of the linear defect can be calculated through the abnormal signal interval, and the spectral image of the linear defect position in the OLED mobile phone screen can be acquired, the spectral data of each pixel is acquired according to the spectral image, the corresponding gradient amplitude is acquired through each spectral data, the abnormal pixel and the normal pixel are determined according to the gradient amplitude, the parameter characteristic of each abnormal pixel is acquired, the defect degree value is acquired according to a plurality of parameter characteristics, the defect position is acquired through an abnormal signal interval and is independent of display content and screen brightness, so that misjudgment caused by uneven brightness or change of ambient light of the display image is avoided, the spectral data of each pixel is captured by using the spectral image, the influence of ambient light and display brightness can be effectively eliminated, the spectral image can provide more information than that of a common image, such as reflectivity and absorption characteristics of different wave bands, so that detection is more accurate and robust, more information can be acquired from a plurality of wavelength ranges by acquiring the spectral data of each pixel, the identification of defects is not influenced by the change of ambient light and screen display content, the spectrum data is not easily interfered by the change of external conditions, a more stable and accurate detection result can be provided, the existing method possibly depends on brightness gradient or color contrast, but the data is greatly influenced by the screen display content and the brightness change thereof, so that the detection process is inaccurate, the defects are analyzed through the gradient amplitude of the spectrum data, the misjudgment caused by the light change and the screen brightness difference can be reduced, the gradient amplitude reflects the change condition among pixels, not just brightness or color itself, therefore, higher accuracy can be maintained under various illumination conditions, the vibration signal analysis can provide direct information about the physical structure of the screen, especially about the dynamic response of the screen in the working state, when the OLED screen generates linear defects, the defect area can physically induce the change of vibration modes, the vibration signals of the screen are subjected to Fourier transformation, and a plurality of signals are synchronously calibrated, so that the position of the defects can be rapidly determined by calculating the vibration anomaly degree of an abnormal signal interval, the processing of a spectrum image involves data of a plurality of wavebands, the calculation complexity is high, if the spectrum data is directly used for full screen detection in the early stage, the processing speed can be influenced, each pixel of the spectrum data has information of a plurality of wavelengths, and the information is extracted, The analysis and post-processing need to consume a large amount of calculation resources, the abnormal position is determined rapidly through methods such as vibration time domain signals, and then the abnormal defect degree is accurately and stably detected through a spectrum image, so that the linear defect detection of an OLED mobile phone screen can be realized more rapidly and accurately, in the traditional technology, the judgment of abnormal pixels is usually dependent on the brightness contrast and color difference of a static image, but larger deviations can be generated under different environments, so that the abnormal pixels can not be accurately detected, the abnormal pixels and normal pixels can be distinguished through the analysis of gradient amplitude values, the fine difference between the pixels can be accurately identified, the error based on brightness or color is avoided, the analysis of the gradient amplitude values can also identify the defect region more reliably even in an environment with unstable illumination conditions, the defect identification accuracy is improved through the acquisition of the parameter characteristics of each abnormal pixel, the parameter characteristics not only consider the brightness change of the pixels, but also cover more spectrum and physical properties, the abnormal region can be better captured and analyzed, the defect degree can be comprehensively evaluated through the parameter characteristics, the defect degree can be accurately and comprehensively evaluated, and the defect quality can be accurately estimated, and the defect degree can be accurately estimated, and the defect quality can be comprehensively estimated, and the defect can be accurately estimated and accurately.

In one embodiment, the step S2 of performing synchronous alignment calibration on the plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals includes:

s21, removing direct current components in each vibration frequency domain signal by adopting a high-pass filter to obtain a plurality of dynamic vibration signals, and sequentially denoising and normalizing each dynamic vibration signal to obtain a corresponding standard vibration signal;

S22, sorting a plurality of standard vibration signals according to a time sequence, marking the standard vibration signal arranged at the first position as a reference vibration signal, and marking the rest standard vibration signals as calibration vibration signals;

S23, acquiring a first initial time point of the reference vibration signal and a second initial time point of each calibration vibration signal, and acquiring a corresponding hysteresis value according to the first initial time point and each second initial time point;

S24, obtaining corresponding cross-correlation coefficients according to the reference vibration signals, each hysteresis value and the corresponding calibration vibration signals, and carrying out translation on a time axis according to the corresponding calibration vibration signals of each cross-correlation coefficient to obtain a plurality of synchronous vibration signals.

As described in the above steps S21 to S24, the present invention eliminates the dc component in each vibration frequency domain signal by using the high-pass filter to obtain a plurality of dynamic vibration signals, sequentially denoises and normalizes each dynamic vibration signal to obtain a corresponding standard vibration signal, sequentially ranks the plurality of standard vibration signals according to time sequence, marks the standard vibration signal arranged at the first position as a reference vibration signal, marks the remaining standard vibration signal as a calibration vibration signal, obtains a first initial time point of the reference vibration signal and a second initial time point of each calibration vibration signal, obtains a corresponding hysteresis value according to the first initial time point and each second initial time point, obtains a corresponding cross-correlation coefficient according to the reference vibration signal, each hysteresis value and the corresponding calibration vibration signal, and translates on the time axis according to each cross-correlation coefficient to the corresponding calibration vibration signal to obtain a plurality of synchronous vibration signals, and removes the dc component by the high-pass filter, thus, the low-frequency noise can be filtered, the dynamic part in the vibration signal can be more clearly detected without depending on the display image itself, thus the environmental noise can be prevented from being influenced by the detection and the noise, the vibration signal can be more clearly analyzed by the device, and the noise can be reduced, the vibration signal can be more clearly has a better stability and the stability due to the vibration signal can be more clearly measured, and the vibration signal can be compared with the vibration frequency and the vibration frequency signal, and the vibration frequency can be clearly has a low noise, the method can eliminate time deviation among signals, ensure synchronism of vibration signals, improve accuracy and reliability of defect detection, compare and analyze all vibration signals under the same time frame by accurately calculating hysteresis values and using the hysteresis values for time alignment, eliminate influence caused by signal delay or transmission inconsistency, improve detection accuracy, quantitatively measure similarity among signals by calculating cross-correlation coefficients, effectively identify time correlation and similarity among different vibration signals, enable defect detection to be more accurate, avoid misjudgment caused by ambient light change or image noise in traditional image detection, ensure that all signals are synchronized to a common time standard by carrying out time axis translation on the signals, further improve comparability among the signals, accurately capture vibration modes related to the defects, avoid misjudgment caused by different time delays, and improve accuracy and reliability of defect identification.

In one embodiment, the step S3 of acquiring the abnormal signal interval according to the plurality of synchronous vibration signals includes:

S31, acquiring first amplitudes of each synchronous vibration signal at each time point, and carrying out weighted average processing according to a plurality of first amplitudes at each time point to obtain a composite vibration signal;

s32, acquiring first amplitude at each frequency point according to the composite vibration signal, and calculating corresponding power spectral density according to each first amplitude, wherein a calculation formula is as follows:

;

Wherein G (PM) represents the power spectral density, F (DZ) represents the first amplitude, and C (XM) represents the frequency points;

S33, establishing a frequency-density coordinate axis by taking the frequency as an X axis and the power spectral density as a Y axis, and drawing the power spectral density corresponding to each frequency on the frequency-density coordinate axis as a connection point;

S34, sequentially connecting the connecting points through curves to obtain a power spectrum waveform diagram, and obtaining the peak value and the valley value of the power spectrum waveform diagram;

s35, dividing a power spectrum waveform diagram into a plurality of curves according to two adjacent peaks and valleys, and obtaining the curvature of each curve;

S36, judging whether the curvature is larger than a preset threshold value or not;

In the steps S31-S36, the calculation formulas of the power spectrum densities all normalize the parameters of the first amplitude in advance to eliminate the dimensional differences between different variables, so as to ensure that the calculation is more stable and effective, the invention obtains the first amplitude of each synchronous vibration signal at each time point, performs weighted average processing according to the first amplitudes at each time point to obtain a composite vibration signal, obtains the first amplitude at each frequency point through the composite vibration signal, calculates the corresponding power spectrum density according to each first amplitude, establishes a frequency-density coordinate axis with the frequency as the X-axis, draws the power spectrum density corresponding to each frequency as the Y-axis, sequentially connects the plurality of connection points through curves to obtain a power spectrum waveform map, obtains the peak value and the valley value of the power spectrum waveform map, divides the power spectrum waveform map into a plurality of curves through two adjacent peak values and valley values, obtains the curvature of each curve, and judges whether the curvature of each curve is larger than the preset curvature, and detects the curve according to the preset curvature, and detects the curve, and the image signal is based on the curve, thereby the image is not influenced by the conventional method, the method has the image sensor is compared with the conventional method, the image sensor has the problem that the image is not influenced by the conventional method, the image sensor is changed, the image sensor is detected, the image sensor is changed, and the image sensor is changed, the image sensor is or the image signal is changed, errors and noise caused by single signal fluctuation can be reduced, the final composite vibration signal is more stable and reliable, fluctuation caused by external factors is reduced compared with the traditional method, the detection result is more accurate, the state of a screen can be more comprehensively known by analyzing the frequency characteristics of the vibration signal, potential defects can be more effectively identified by frequency analysis than the frequency analysis which only depends on image brightness, particularly, when the environment light is processed to change, the stability of the frequency characteristics can improve the detection robustness, the change trend and frequency components of the vibration signal can be clearly observed by establishing the relation between the frequency and the power spectrum density, the position and the property of the defects can be more accurately positioned instead of depending on the deviation possibly caused by the environment light or the display brightness in the image information, and the detection of peaks and valleys is utilized, the periodic variation of the signal can be further analyzed to find potential abnormal fluctuation, compared with the traditional image detection method, the frequency domain analysis is more reliable, because the frequency domain analysis is not directly influenced by the displayed image, errors caused by ambient light or display setting variation in image analysis are avoided, the complexity of signal variation can be revealed and normal signals and abnormal signals can be distinguished by carrying out curvature analysis on a power spectrum waveform graph, the method can carry out finer analysis on the complicated vibration signals, thereby effectively distinguishing different types of defects, improving the accuracy of defect detection, automatically detecting abnormal vibration characteristics and quickly responding, the algorithm can effectively identify fine defects which are difficult to capture in the traditional image detection, such as tiny display non-uniformity or structural damage, the situation of false detection and missing detection is avoided, and the position and degree of the defect can be accurately identified by accurately positioning the signal interval where the abnormal curve is located, so that the detection result is not only at the level of whether the defect exists, but also the detailed information of the defect is further provided, and the subsequent analysis and processing are facilitated.

In one embodiment, the step S3 of obtaining the vibration anomaly according to the anomaly signal interval includes:

S37, acquiring abnormal frequency components of each frequency point according to the abnormal signal interval, and acquiring historical frequency components of each same frequency point in the historical normal signal of the OLED mobile phone screen;

s38, calculating a frequency offset according to a plurality of historical frequency components and abnormal frequency components, wherein a calculation formula is as follows:

;

Wherein P (PY) represents the frequency offset, N represents the number of abnormal frequency components, i represents the number of abnormal frequency components, Y (PC) _i represents the i-th abnormal frequency component, and L (PC) _i represents the i-th historical frequency component;

s39, acquiring the total frequency band number, the maximum frequency and the minimum frequency according to the abnormal signal interval, and acquiring the center frequency of each frequency band according to the total frequency band number, the maximum frequency and the minimum frequency;

S310, dividing an abnormal signal interval into a plurality of frequency interval sections according to each central frequency, and acquiring a second amplitude of each frequency interval section;

S311, acquiring energy density of a corresponding frequency interval section according to each second amplitude, and acquiring energy of a corresponding abnormal frequency according to each energy density;

s312, acquiring a plurality of historical frequency energies in the historical normal signals of the OLED mobile phone screen, and calculating frequency energy anomaly degree according to the historical frequency energies and the anomaly frequency energies, wherein a calculation formula is as follows:

;

Wherein P (NY) represents a frequency energy abnormality degree, M represents the number of abnormal frequency energies, Y (PN) _m represents an mth abnormal frequency energy, and L (PN) _m represents an mth historical frequency energy;

S313, obtaining the vibration anomaly degree according to the frequency energy anomaly degree and the frequency offset degree.

As described in the above steps S37-S313, the calculation formulas of the frequency energy anomaly degree are normalized in advance for the two parameters of the history frequency energy and the anomaly frequency energy to eliminate the dimensional difference between the different variables, so as to ensure that all the variables are on the same order of magnitude and thus the calculation is more stable and effective, and the anomaly frequency component refers to the change or anomaly of the signal at a specific frequency point in hertz (Hz) and the frequency offset degree in hertz (Hz), for example, the history frequency components (10, 20, 30) and the anomaly frequency components (12, 19, 28) are brought into the calculation formulas of the frequency offset degreeWhereas the prior art usually calculates the difference between the actual frequency and the reference frequency, i.e. the frequency offset = actual frequency-reference frequency, but only considers a single frequency offset to bring errors to the detection result, the invention calculates the frequency offset of the overall average by the historical frequency components and the abnormal frequency components corresponding to a plurality of frequency points, which is calculated by the mean square error of the frequency components, and can be averaged over a plurality of frequency points, compared with the prior art, to provide an overall and comprehensive error assessment, in the multi-frequency signal, the calculated frequency offset is more accurate because it considers the deviation of each frequency component, rather than just a single frequency deviation, the invention obtains the abnormal frequency components of each frequency point through the abnormal signal interval, and obtains the historical frequency components of each identical frequency point in the historical normal signal of the OLED mobile phone screen, calculates the frequency offset by the historical frequency components and the abnormal frequency components, obtains the total frequency band number through the abnormal signal interval, maximum frequency and minimum frequency, and according to total frequency band number, The method comprises the steps of obtaining the center frequency of each frequency band by maximum frequency and minimum frequency, dividing an abnormal signal interval into a plurality of frequency interval sections through each center frequency, obtaining the second amplitude of each frequency interval section, obtaining the energy density of the corresponding frequency interval section through each second amplitude, obtaining the corresponding abnormal frequency energy according to each energy density, obtaining a plurality of historical frequency energies in the historical normal signal of an OLED mobile phone screen, calculating the frequency energy anomaly degree according to the historical frequency energies and the abnormal frequency energy, obtaining the vibration anomaly degree through the frequency energy anomaly degree and the frequency offset degree, analyzing through the frequency components based on the signals, directly extracting abnormal information from signal characteristics, enabling the abnormal analysis of the signals to be more accurate, eliminating the interference of external factors such as ambient light, enabling a reference of signal change to be established through combining the historical normal signal, having higher identification accuracy, enabling long-term offset to be identified through the comparison of historical data, further reducing false positive (report) and false negative (error) frequency offset) probability to be better than the historical error rate, enabling the frequency change to be accurately detected through the frequency offset of the frequency component based on the signals, providing a more accurate and more accurate frequency offset, providing a method to the frequency change to be better than the historical change, and better accurate frequency change can be revealed through the frequency change, the frequency change can be detected through the frequency component based on the frequency component of the signal, Accurate defect detection capability, the frequency distribution situation of the signal can be more clearly known through dividing and analyzing the frequency bands of the signal, and frequency intervals which possibly cause defects can be identified, the frequency domain analysis can more finely capture problems, especially the problems which can not be found through image detection, the characteristics of each frequency band can be clarified through calculating the center frequency of each frequency band, and accurate signal segmentation is provided for subsequent analysis, the method can enable abnormal points of the signal to be more easily identified, interference on noise signals is reduced, the characteristics and changes of each frequency band can be finely analyzed through dividing the frequency intervals, the detection can be more refined, the problem areas of specific frequency bands can be positioned, higher detection precision is provided, the intensity distribution of the abnormal signal can be deeply known through analyzing the energy density of each frequency interval, the energy density analysis provides a quantized standard to help detect whether abnormal frequency energy aggregation exists, further improves accuracy of defect identification, the energy density is one of important indexes of frequency signal abnormality, abnormal frequency energy of a signal can be captured more directly through energy calculation, so that a fine abnormal signal is identified, the method has the advantages that the quantized degree is high, accurate abnormal measurement can be provided, the trend and rule of signal change can be revealed by comparing historical frequency energy with current abnormal frequency energy, long-term abnormality can be identified, the abnormal degree of the signal can be quantitatively evaluated by calculating the abnormal degree of the frequency energy, accordingly, not only single frequency deviation is considered, but also overall frequency energy change can be comprehensively evaluated, and reliability and comprehensiveness of detection results are enhanced, the frequency offset degree and the frequency energy abnormality degree are combined, the overall abnormality condition of the signal can be comprehensively evaluated, potential vibration abnormality can be accurately detected, and the multi-dimensional abnormality measurement method can effectively improve detection accuracy and reduce false alarm and missing report.

In one embodiment, the step S6 of obtaining a corresponding gradient amplitude according to each spectrum data and determining an abnormal pixel point and a normal pixel point according to the gradient amplitude includes:

s61, acquiring a left pixel value and a right pixel value of a corresponding pixel point in the horizontal direction according to each spectrum data, and acquiring a corresponding horizontal gradient according to each left pixel value and each right pixel value;

S62, acquiring an upper pixel value and a lower pixel value of a corresponding pixel point in the vertical direction according to each spectrum data, and acquiring a corresponding vertical gradient according to each upper pixel value and each lower pixel value;

s63, acquiring corresponding gradient amplitude values according to each horizontal gradient and each vertical gradient;

S64, judging whether the gradient amplitude is larger than a preset gradient or not;

As described in the above steps S61-S64, the present invention obtains the left pixel value and the right pixel value of the corresponding pixel point in the horizontal direction through each spectrum data, obtains the corresponding horizontal gradient according to each left pixel value and each right pixel value, obtains the upper pixel value and the lower pixel value of the corresponding pixel point in the vertical direction through each spectrum data, obtains the corresponding vertical gradient according to each upper pixel value and each lower pixel value, obtains the corresponding gradient amplitude through each horizontal gradient and each vertical gradient, and judges whether the gradient amplitude is greater than the preset gradient, if the gradient amplitude is greater than the preset gradient, then judges the pixel point corresponding to the gradient amplitude as an abnormal pixel point, if the gradient amplitude is not greater than the preset gradient, then judges the pixel point corresponding to the gradient amplitude as a normal pixel point, in the prior art, the linear defect detection of the OLED screen is generally dependent on the displayed image content, such as a test pattern or a specific image, so that the result is subjected to ambient light, The influence of factors such as brightness and the like, which leads to unstable detection, can reduce the dependence on the display content of a screen by acquiring pixel values through using spectral data and calculating gradients, avoid the interference caused by the brightness or content change of an image, and the influence of the screen content or the display brightness is also avoided by the gradient calculation in the vertical direction, so that the local change condition of the pixels can be comprehensively considered by the gradient calculation in the vertical and horizontal directions without depending on the specific display content, thereby providing more stable detection, The method has the advantages that the algorithm can keep higher accuracy under different ambient lights no matter how the image content changes, the calculation of gradient amplitude integrates the information of the horizontal direction and the vertical direction, the more comprehensive pixel change condition is provided, the prior art can only rely on the gradient of a single direction or the simple image content detection, the information of other directions is ignored, the abnormal change of the pixel point can be better captured by combining the gradient of the horizontal direction and the gradient of the vertical direction, the robustness and the accuracy of the detection are improved, particularly the abnormal point can be more accurately identified when the linear defect is processed, the detection sensitivity can be flexibly controlled by setting the preset gradient value, the detection result is optimized, the preset threshold value can be adjusted according to the requirement of practical application, thereby being suitable for different defect detection standards, the prior art relies on the display content and brightness change of the image, and can not flexibly adjust the detection standard, so that the detection accuracy and consistency can be influenced under different environmental conditions, the detection process is more objective and stable by using the gradient amplitude as a judgment basis, the influence of human intervention or image brightness change is reduced, the magnitude of the gradient amplitude can effectively distinguish normal pixels from abnormal pixels, the abnormal pixels usually show larger gradient difference from surrounding pixels, and therefore, the abnormal pixels can be judged by the gradient amplitude to more accurately identify straight line defects, the method has the advantages that the dependence on the display content is avoided by digital gradient calculation, the defects can be stably identified under the condition of not being interfered by the ambient light or screen content change, and the traditional method often depends on the brightness difference or the image content, this is subject to ambient light changes, The influence of factors such as screen brightness adjustment and the like influences the detection accuracy, spectrum data and pixel gradient information are changed without depending on image content and brightness, the detection process is more stable and consistent, and interference of ambient light, screen brightness or content change can be overcome, so that no matter how the ambient light changes or what the image content is displayed on the screen, the defect detection effect is still reliable, and the defect detection accuracy and practicality are improved.

In one embodiment, the step S7 of obtaining the defect level value according to a plurality of the parameter features includes:

S71, acquiring pixel areas of corresponding abnormal pixel points and a plurality of first abnormal principal component characteristic values according to each parameter characteristic;

S72, obtaining a defect total area of a linear defect position in the OLED mobile phone screen, and obtaining an abnormal pixel defect duty ratio according to the defect total area and a plurality of pixel areas;

S73, acquiring corresponding abnormal average characteristic values according to a plurality of abnormal principal component characteristic values of each abnormal pixel point;

S74, acquiring a plurality of historical normal principal component characteristic values of normal pixel points corresponding to each same abnormal pixel point in the historical normal spectrum image of the OLED mobile phone screen, and acquiring a corresponding normal average characteristic value according to the plurality of historical normal principal component characteristic values of each normal pixel point;

S75, obtaining an abnormal characteristic difference duty ratio according to the normal average characteristic value and the abnormal average characteristic value, and obtaining a defect degree value according to the abnormal characteristic difference duty ratio and the abnormal pixel defect duty ratio.

As described in the above steps S71-S75, the present invention obtains the pixel area of the corresponding abnormal pixel point and a plurality of first abnormal principal component feature values through each parameter feature, obtains the defect total area of the linear defect position in the OLED mobile phone screen, obtains the abnormal pixel defect ratio according to the defect total area and the plurality of pixel areas, obtains the corresponding abnormal average feature value through a plurality of abnormal principal component feature values of each abnormal pixel point, obtains the plurality of historical normal principal component feature values of the corresponding normal pixel point of each same abnormal pixel point in the historical normal spectrum image of the OLED mobile phone screen, obtains the corresponding normal average feature value according to a plurality of historical normal principal component feature values of each normal pixel point, obtains the abnormal feature difference ratio through a plurality of normal average feature values and the abnormal average feature value, the defect degree value is obtained according to the difference proportion of abnormal characteristics and the defect proportion of abnormal pixels, excessive dependence on screen brightness can be avoided by extracting the characteristics of each pixel point and analyzing the characteristic value of the main component, the detection accuracy can be still kept under different ambient light conditions, the abnormal degree of each abnormal pixel point can be more accurately judged, the detection stability is improved, the distribution condition of defects can be comprehensively known by measuring the total area of linear defects, the accuracy of defect identification can be improved for the high-resolution display screen such as an OLED screen, the whole condition can be better judged particularly under the condition that large-area defects or a plurality of defects coexist, the severity of the defects can be quantitatively estimated by calculating the abnormal pixel proportion, and the defect position identification is not only relied on, can provide a more quantitative result, can flexibly adjust and evaluate under different conditions, avoid deviation caused by simple relying on manual experience, can more comprehensively analyze the characteristics of abnormal pixels by extracting a plurality of main component characteristics of the abnormal pixels and calculating the average characteristic value thereof, can provide more accurate abnormal recognition capability especially for irregular forms or defects which are difficult to judge through traditional brightness, can greatly improve the accuracy of abnormal detection by introducing the contrast analysis of historical normal spectrum images, can not normally compare with the normal state, can judge the defects only according to real-time display images, can compare the currently detected abnormal pixels with the historical normal state through the support of the historical normal data, further improves the recognition accuracy of the abnormal mode, the risk of misjudgment or missed judgment is reduced, detailed characteristic information can be extracted from the historical data of normal pixel points, the detection algorithm can still keep accurate grasp of the normal state when facing the change of ambient light by calculating the average characteristic value in the normal state, compared with the prior method, the comparison based on the historical data enables a detection system to be more sensitive and have higher robustness, the quality and the severity of defects can be more carefully evaluated by calculating the difference proportion between the normal characteristic and the abnormal characteristic, the method can more accurately reflect the health condition of a screen, reduce errors, provide more effective basis for subsequent fault diagnosis, and finally obtain the defect degree value as a comprehensive quantization result by integrating the difference proportion of the abnormal characteristic and the defect proportion of the pixel, the detection mode comprehensively considering multiple dimensions can comprehensively evaluate the actual influence of defects, and particularly under the complex condition of interaction of multiple factors, the method can provide more accurate defect evaluation and provide scientific basis for subsequent quality control and maintenance.

In one embodiment, the fourth acquisition module includes:

It should be noted that each module and unit in the linear defect detection system of the OLED mobile phone screen corresponds to the steps in the linear defect detection method of the OLED mobile phone screen one by one.

As shown in fig. 3, the present application also provides a computer device, which may be a server, and the internal structure of which may be as shown in fig. 3. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for storing all data required by the process of the linear defect detection method of the OLED mobile phone screen. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to realize the linear defect detection method of the OLED mobile phone screen.

It will be appreciated by those skilled in the art that the architecture shown in fig. 3 is merely a block diagram of a portion of the architecture in connection with the present inventive arrangements and is not intended to limit the computer devices to which the present inventive arrangements are applicable.

An embodiment of the present application further provides a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor implements any one of the above-mentioned OLED mobile phone screen linear defect detection methods.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by hardware associated with a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided by the present application and used in embodiments may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, apparatus, article, or method that comprises the element.

The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes using the descriptions and drawings of the present invention or directly or indirectly applied to other related technical fields are included in the scope of the invention.

Claims

1. A method for detecting straight line defects of an OLED mobile phone screen, comprising:

Acquire multiple vibration time domain signals on the surface of the OLED mobile phone screen within a preset time period, and perform Fourier transform processing on each of the vibration time domain signals to obtain a corresponding vibration frequency domain signal;

Performing synchronous alignment and calibration on the plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals;

Acquire an abnormal signal interval according to the plurality of synchronous vibration signals, and acquire a vibration abnormality degree according to the abnormal signal interval;

Determining whether the vibration abnormality is greater than a preset abnormality;

If the vibration abnormality is greater than the preset abnormality, it is determined that the OLED mobile phone screen has a linear defect, and the linear defect position of the OLED mobile phone screen is obtained according to the abnormal signal interval;

Obtain a spectral image of a linear defect position in an OLED mobile phone screen, and obtain spectral data of each pixel point based on the spectral image;

Acquire a corresponding gradient amplitude according to each of the spectral data, and determine abnormal pixel points and normal pixel points according to the gradient amplitude;

A parameter feature of each abnormal pixel is obtained, and a defect degree value is obtained according to a plurality of the parameter features.

2. The method for detecting linear defects of OLED mobile phone screens according to claim 1, characterized in that the step of synchronously aligning and calibrating the plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals comprises:

A high-pass filter is used to remove the DC component in each of the vibration frequency domain signals to obtain a plurality of dynamic vibration signals, and each of the dynamic vibration signals is subjected to denoising and normalization processing in turn to obtain a corresponding standard vibration signal;

Sorting the plurality of standard vibration signals in chronological order, marking the first standard vibration signal as a reference vibration signal, and marking the remaining standard vibration signals as calibration vibration signals;

Acquire a first initial time point of the reference vibration signal and a second initial time point of each calibration vibration signal, and acquire a corresponding hysteresis value according to the first initial time point and each second initial time point;

Corresponding cross-correlation coefficients are obtained according to the reference vibration signal, each hysteresis value and the corresponding calibration vibration signal, and the corresponding calibration vibration signal is translated on the time axis according to each cross-correlation coefficient to obtain multiple synchronous vibration signals.

3. The method for detecting linear defects of OLED mobile phone screens according to claim 1, characterized in that the step of obtaining an abnormal signal interval according to a plurality of the synchronous vibration signals comprises:

Acquire the first amplitude of each of the synchronous vibration signals at each time point, and perform weighted average processing according to multiple first amplitudes at each time point to obtain a composite vibration signal;

Acquire a first amplitude at each frequency point according to the composite vibration signal, and acquire a corresponding power spectrum density according to each first amplitude;

With frequency as the X-axis and power spectrum density as the Y-axis, a frequency-density coordinate axis is established, and the power spectrum density corresponding to each frequency is plotted as a connection point on the frequency-density coordinate axis;

Connecting the plurality of connection points in sequence through a curve to obtain a power spectrum waveform, and obtaining peak values and valley values of the power spectrum waveform;

Dividing the power spectrum waveform into multiple curves according to two adjacent peak values and valley values, obtaining the curvature of each curve, and determining whether the curvature is greater than a preset threshold;

If the curvature is greater than a preset threshold, the curve corresponding to the curvature is determined to be an abnormal curve, and the abnormal signal interval is obtained according to the abnormal curve and the power spectrum waveform diagram.

4. The method for detecting straight line defects of an OLED mobile phone screen according to claim 1, wherein the step of obtaining the vibration abnormality according to the abnormal signal interval comprises:

Obtain the abnormal frequency component of each frequency point according to the abnormal signal interval, obtain the historical frequency component of each same frequency point in the historical normal signal of the OLED mobile phone screen, and obtain the frequency deviation degree according to the multiple historical frequency components and abnormal frequency components;

Acquire the total number of frequency bands, the maximum frequency and the minimum frequency according to the abnormal signal interval, and acquire the center frequency of each frequency band according to the total number of frequency bands, the maximum frequency and the minimum frequency;

Dividing the abnormal signal interval into a plurality of frequency interval segments according to each of the center frequencies, acquiring a second amplitude of each of the frequency interval segments, acquiring an energy density of a corresponding frequency interval segment according to each of the second amplitudes, and acquiring a corresponding abnormal frequency energy according to each of the energy densities;

Acquire multiple historical frequency energies in the historical normal signal of the OLED mobile phone screen, obtain the frequency energy abnormality according to the multiple historical frequency energies and the abnormal frequency energies, and obtain the vibration abnormality according to the frequency energy abnormality and the frequency deviation.

5. The method for detecting straight line defects of an OLED mobile phone screen according to claim 1, characterized in that the step of obtaining a corresponding gradient amplitude according to each of the spectral data and determining abnormal pixels and normal pixels according to the gradient amplitude comprises:

According to each of the spectral data, a left pixel value and a right pixel value of a corresponding pixel point in the horizontal direction are obtained, and according to each of the left pixel value and the right pixel value, a corresponding horizontal gradient is obtained;

According to each of the spectral data, an upper pixel value and a lower pixel value of a corresponding pixel point in a vertical direction are obtained, and according to each of the upper pixel value and the lower pixel value, a corresponding vertical gradient is obtained;

Acquire a corresponding gradient amplitude according to each of the horizontal gradient and the vertical gradient, and determine whether the gradient amplitude is greater than a preset gradient;

If the gradient amplitude is greater than the preset gradient, the pixel point corresponding to the gradient amplitude is determined to be an abnormal pixel point;

If the gradient amplitude is not greater than the preset gradient, the pixel point corresponding to the gradient amplitude is determined to be a normal pixel point.

6. The method for detecting straight line defects of OLED mobile phone screens according to claim 1, characterized in that the step of obtaining defect degree values according to the plurality of parameter features comprises:

According to each of the parameter features, a pixel area of a corresponding abnormal pixel point and a plurality of first abnormal principal component eigenvalues are obtained;

Obtain the total defect area of the linear defect position in the OLED mobile phone screen, and obtain the abnormal pixel defect ratio based on the total defect area and multiple pixel areas;

Obtain the corresponding abnormal average eigenvalue according to multiple abnormal principal component eigenvalues of each abnormal pixel point;

Obtain multiple historical normal principal component eigenvalues of normal pixel points corresponding to each identical abnormal pixel point in the historical normal spectrum image of the OLED mobile phone screen, and obtain the corresponding normal average eigenvalue according to the multiple historical normal principal component eigenvalues of each normal pixel point;

The abnormal feature difference ratio is obtained according to the plurality of normal average feature values and the abnormal average feature values, and the defect degree value is obtained according to the abnormal feature difference ratio and the abnormal pixel defect ratio.

7. An OLED mobile phone screen linear defect detection system, characterized by comprising:

The first acquisition module is used to acquire multiple vibration time domain signals within a preset time period on the surface of the OLED mobile phone screen, and perform Fourier transform processing on each of the vibration time domain signals to obtain a corresponding vibration frequency domain signal;

A calibration module, used for synchronously aligning and calibrating the plurality of vibration frequency domain signals to obtain a plurality of synchronous vibration signals;

A second acquisition module, configured to acquire an abnormal signal interval according to the plurality of synchronous vibration signals, and acquire a vibration abnormality degree according to the abnormal signal interval;

A judging module, used for judging whether the vibration abnormality is greater than a preset abnormality;

The third acquisition module is used to obtain a spectral image of the position of the linear defect in the OLED mobile phone screen, and obtain spectral data of each pixel point according to the spectral image;

A determination module, used for acquiring a corresponding gradient amplitude according to each of the spectral data, and determining abnormal pixel points and normal pixel points according to the gradient amplitude;

The fourth acquisition module is used to acquire the parameter characteristics of each abnormal pixel point, and acquire the defect degree value according to the multiple parameter characteristics.

8. The OLED mobile phone screen straight line defect detection system according to claim 7, characterized in that the fourth acquisition module comprises:

A first acquisition unit, used for acquiring a pixel area of a corresponding abnormal pixel point and a plurality of first abnormal principal component eigenvalues according to each of the parameter features;

A second acquisition unit is used to acquire the total defect area of the linear defect position in the OLED mobile phone screen, and acquire the abnormal pixel defect ratio according to the total defect area and multiple pixel areas;

A third acquisition unit is used to acquire a corresponding abnormal average eigenvalue according to multiple abnormal principal component eigenvalues of each abnormal pixel point;

A fourth acquisition unit is used to acquire multiple historical normal principal component eigenvalues of normal pixel points corresponding to each identical abnormal pixel point in the historical normal spectrum image of the OLED mobile phone screen, and acquire a corresponding normal average eigenvalue according to the multiple historical normal principal component eigenvalues of each normal pixel point;

The fifth acquisition unit is used to acquire the abnormal feature difference ratio according to the plurality of normal average feature values and abnormal average feature values, and acquire the defect degree value according to the abnormal feature difference ratio and the abnormal pixel defect ratio.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein the processor implements the steps of the method according to any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.