CN118759260B - Sector scanning detection method and system for detecting conductivity of supercapacitor - Google Patents
Sector scanning detection method and system for detecting conductivity of supercapacitor Download PDFInfo
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Abstract
本发明涉及电导率检测技术领域，尤其涉及一种用于检测超级电容器电导率的扇形扫描检测方法及系统，该方法包括：监测各监测点处的实时热声信号；提取实时热声信号的实时信号强度和实时信号稳定度；调整预设数量；调整预设旋转角速度；调整预设角度；提取实时电导率；调整预设旋转半径，或修正调整后的预设角度；构建电导率分布图并输出。本发明通过脉冲磁场和超声换能器的结合使用，能够高效地激发并捕捉到超级电容器的热声响应，实时信号强度和稳定度的提取与动态参数调整机制，确保了在不同条件下都能获得高质量的信号数据，有效解决了采样密度要求高和计算复杂度高导致检测时间长和系统压力大引起的检测效率低的问题。
The present invention relates to the field of conductivity detection technology, and in particular to a sector scanning detection method and system for detecting the conductivity of a supercapacitor, the method comprising: monitoring real-time thermoacoustic signals at each monitoring point; extracting real-time signal strength and real-time signal stability of the real-time thermoacoustic signal; adjusting a preset number; adjusting a preset rotation angular velocity; adjusting a preset angle; extracting real-time conductivity; adjusting a preset rotation radius, or correcting the adjusted preset angle; constructing a conductivity distribution map and outputting it. The present invention can efficiently excite and capture the thermoacoustic response of a supercapacitor through the combined use of a pulsed magnetic field and an ultrasonic transducer, and the extraction of real-time signal strength and stability and the dynamic parameter adjustment mechanism ensure that high-quality signal data can be obtained under different conditions, effectively solving the problem of low detection efficiency caused by long detection time and high system pressure due to high sampling density requirements and high computational complexity.
Description
Technical Field
The invention relates to the technical field of conductivity detection, in particular to a sector scanning detection method and system for detecting the conductivity of a supercapacitor.
Background
The performance of the super capacitor is related to the conductivity of the electrode material, and the conductivity determines the charge and discharge performance of the super capacitor, so that the detection of the conductivity plays an extremely important role in developing the super capacitor. The induction type thermo-acoustic detection system is a non-contact detection method, and is characterized in that a pulse magnetic field is used for exciting a super capacitor material to be detected, eddy currents induced in the material to be detected absorb thermal expansion under the action of the magnetic field to emit thermo-acoustic signals, and ultrasonic transducers arranged on the periphery receive the filtered and amplified ultrasonic signals to reconstruct conductivity distribution in the material to be detected. The existing induction type thermoacoustic detection system is characterized in that a detected energy storage material is placed in a pulse magnetic field, an ultrasonic transducer is placed around a target body to be detected, and thermoacoustic signals are detected by rotating around the target body to be detected in a circle, so that conductivity information of the target body to be detected is rebuilt.
The existing induction type thermoacoustic detection method has the technical defects that the induction type thermoacoustic detection method is divided into two processes according to the conductivity of a target body to be detected by inversion of a thermoacoustic signal, firstly, a time inversion method or a back projection method is used for inverting the heat absorption function of the target body to be detected according to the collected thermoacoustic signal, and secondly, the conductivity distribution information of the target body to be detected is inverted according to the inverted heat absorption function by a least square iteration algorithm. Since the annular scanning has a maximum viewing angle of 360 degrees in a two-dimensional plane, the most object information to be measured can be obtained in the annular scanning process. However, the time inversion method or the back projection method needs a large amount of comprehensive detection information in the inversion process to invert the heat absorption function, has very large requirements on the sampling density in space and time, brings relatively large pressure to the system, has relatively long time for collecting the thermo-acoustic signals, increases the detection time and workload, and simultaneously increases the calculation complexity for the inversion algorithm due to a large amount of detection information.
Disclosure of Invention
Therefore, the invention provides a sector scanning detection method and a sector scanning detection system for detecting the conductivity of a supercapacitor, which are used for solving the problems of low detection efficiency caused by long detection time and high system pressure due to high sampling density requirement and high calculation complexity in the prior art.
In order to achieve the above object, the present invention provides a sector scanning detection method for detecting the conductivity of a supercapacitor, comprising:
Placing a target body to be detected in a pulse magnetic field, rotating a preset angle with a preset rotating radius and a preset rotating angular speed by using a preset number of ultrasonic transducers, and monitoring real-time thermoacoustic signals at all monitoring points;
Extracting the real-time signal intensity and the real-time signal stability of the real-time thermo-acoustic signal;
Adjusting a preset quantity according to the real-time signal strength and the preset standard signal strength;
Adjusting a preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;
Adjusting a preset angle according to the maximum value of all real-time signal intensities in the preset rotation time and a preset standard peak value range;
Using a preset algorithm based on a compressed sensing theory, reconstructing a conductivity matrix of a target body to be detected through real-time thermo-acoustic signals of all monitoring points, and extracting real-time conductivity from the conductivity matrix;
Adjusting a preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range;
And constructing a conductivity distribution diagram according to the real-time thermo-acoustic signal with the real-time conductivity within the preset standard conductivity range and outputting the conductivity distribution diagram.
Further, extracting the real-time signal strength of the real-time thermo-acoustic signal includes:
And converting the real-time thermo-acoustic signal into a digital signal by using an analog-to-digital converter, and calculating the root mean square of the digital signal in a preset window time period to obtain the real-time signal intensity.
Further, extracting the real-time signal stability of the real-time thermo-acoustic signal includes:
and calculating the standard deviation of the real-time thermo-acoustic signal converted into the digital signal to obtain the stability of the real-time signal.
Further, the adjusting the preset number according to the real-time signal strength and the preset standard signal strength includes:
when the real-time signal strength is smaller than the preset standard signal strength, the preset number is increased and adjusted according to the real-time signal strength and the preset standard signal strength in a preset number adjusting proportion.
Further, the adjusting the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability includes:
When the real-time signal stability is greater than the preset standard signal stability, the preset rotation angle speed is reduced and adjusted according to the real-time signal stability and the preset standard signal stability by using a preset stability adjustment proportion.
Further, adjusting the preset angle according to the maximum value of all the real-time signal intensities within the preset rotation time and the maximum value of the preset standard peak range comprises:
And when the maximum value of all the real-time signal intensities is larger than the maximum value of the preset standard peak value range, reducing and adjusting the preset angle according to the maximum value of all the real-time signal intensities, the maximum value of the preset standard peak value range and the preset peak value adjusting proportion.
Further, adjusting the preset angle according to the maximum value of all real-time signal intensities within the preset rotation time and the minimum value of the preset standard peak range comprises:
And when the maximum value of all the real-time signal intensities is smaller than the minimum value of the preset standard peak value range, increasing and adjusting the preset angle according to the maximum value of all the real-time signal intensities, the minimum value of the preset standard peak value range and the peak value adjusting proportion.
Further, the reconstructing the conductivity matrix of the target body to be detected by using a preset algorithm based on the compressed sensing theory through the real-time thermo-acoustic signals of each monitoring point, and extracting the real-time conductivity from the conductivity matrix comprises:
sampling a random vector of a preset sampling number of thermo-acoustic signals of preset monitoring times randomly monitored by an ultrasonic transducer in rotation time to obtain sampling data;
integrating the sampled data to obtain a corresponding velocity potential function matrix;
selecting an orthogonal base matrix, and calculating an observation matrix according to the speed potential function data of random sampling;
Reconstructing a heat absorption function matrix of the target body to be detected by using the wavelet basis and the Fourier basis as sparse basis;
reconstructing a conductivity matrix of the target body to be detected by using a least square iterative algorithm;
Extracting real-time conductivity corresponding to each monitoring point from the reconstructed conductivity matrix;
further, the adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range includes:
when the real-time conductivity is larger than the maximum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is larger than the preset standard difference, reducing the adjusted preset angle according to the difference, the preset standard difference and the preset angle correction proportion;
When the real-time conductivity is smaller than the minimum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is larger than the preset standard difference, the adjusted preset angle is increased according to the difference, the preset standard difference and the preset angle correction proportion;
When the real-time conductivity is larger than the maximum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is smaller than the preset standard difference, reducing the preset rotation radius according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment proportion;
When the real-time conductivity is smaller than the minimum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is smaller than the preset standard difference, the preset rotation radius is increased according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment proportion.
A sector scan detection system for detecting supercapacitor conductivity, comprising:
The data monitoring module comprises a preset number of ultrasonic transducers, is used for rotating at a preset angle with a preset rotation radius and a preset rotation angular velocity, and monitors real-time thermoacoustic signals from a target body to be detected in the pulse magnetic field at each monitoring point;
The signal extraction module is connected with the data monitoring module and used for extracting the real-time signal intensity and the real-time signal stability of the real-time thermo-acoustic signal according to a built-in preset extraction algorithm;
The adjusting module is connected with the signal extracting module and is used for adjusting the preset quantity according to the real-time signal strength and the preset standard signal strength;
the adjusting module is also used for adjusting a preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;
The adjusting module is also used for adjusting a preset angle according to the maximum value of all real-time signal intensities in the preset rotation time and a preset standard peak value range;
The conductivity reconstruction extraction module is respectively connected with the adjustment module and the data monitoring module and is used for reconstructing a conductivity matrix of the target body to be detected through real-time thermo-acoustic signals of all monitoring points by using a preset algorithm based on a compressed sensing theory and extracting real-time conductivity from the conductivity matrix;
The correction module is connected with the conductivity reconstruction extraction module and is used for adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range or correcting the adjusted preset angle;
the output module is respectively connected with the conductivity reconstruction extraction module and the correction module and is used for constructing and outputting a conductivity distribution diagram according to the real-time thermoacoustic signal of which the real-time conductivity is in the preset standard conductivity range.
Compared with the prior art, the invention has the beneficial effects that the thermal acoustic response of the super capacitor can be efficiently excited and captured through the combined use of the pulse magnetic field and the ultrasonic transducer, and the sensitivity and the accuracy of detection are improved. The extraction of the real-time signal strength and stability and the dynamic parameter adjustment mechanism enhance the self-adaptive capacity of the system and ensure that high-quality signal data can be obtained under different conditions. The algorithm based on the compressed sensing theory not only improves the efficiency of data processing, but also reduces the requirements on the quantity and the performance of monitoring equipment, visual and detailed capacitor performance information is provided for a user by constructing a conductivity distribution diagram, the optimization design and the quality control of materials are facilitated, and the problems of low detection efficiency caused by long detection time and high system pressure due to high sampling density requirements and high calculation complexity are effectively solved.
Further, the root mean square value provides an accurate measure of signal power, which is helpful for distinguishing signals from noise, so that the accuracy of signal detection is improved, the use of the analog-to-digital converter can ensure that the digital processing of the signals is not affected by interference and attenuation possibly encountered in the transmission process of analog signals, and reliable data support can be provided for subsequent signal stability evaluation and system parameter adjustment through accurate extraction of the real-time signal strength, so that the efficiency of the whole detection system is optimized.
Further, the standard deviation provides an objective measure of quantifying signal fluctuations so that the stability of the signal can be accurately assessed. A smaller standard deviation means that the signal fluctuations are smaller, indicating a high signal quality and a low noise level, thus contributing to an improved accuracy of the signal processing. Monitoring signal stability in real time allows the system to dynamically adjust parameters, such as the monitoring frequency or gain of the ultrasound transducer, to accommodate changes in the signal, ensuring measurement continuity and reliability.
Further, the quality of signal acquisition and the self-adaptive capacity of the system can be remarkably improved by adjusting the number of ultrasonic transducers according to the comparison result of the real-time signal intensity and the preset standard signal intensity. When the signal intensity is insufficient, the ultrasonic transducer is added to enhance the receiving capability of the signal, so that the definition and accuracy of the signal are ensured, and the measurement error caused by weak signal is avoided.
Further, by the method of adjusting the rotation angular velocity according to the real-time signal stability, the acquisition quality of the signal can be effectively optimized. When the signal fluctuation is large, the rotation angular velocity is slowed down, which is helpful for the system to capture the signal change more finely, reduces signal distortion or omission caused by rapid rotation, improves the flexibility and adaptability of the system, and ensures that high-quality signal data can be obtained under different measurement conditions.
Further, when the real-time signal intensity exceeds the expected high value, fine scanning of the high-intensity area of the signal can be achieved by reducing the preset angle, and accurate positioning and analysis of the signal source are facilitated. This not only improves the resolution of the monitoring, but also enhances the ability to identify anomalies or critical areas. When the real-time signal strength is lower than the expected value, the preset angle is increased to ensure the integrity of the whole monitoring area, so that any important information which can influence the evaluation result is avoided being omitted.
Further, the conductivity matrix is reconstructed by adopting the algorithm of the compressed sensing theory, and under the condition that the signal sampling is far lower than the Nyquist rate, the complete signal can be effectively recovered from the sparse sampling data, so that the required monitoring data volume is greatly reduced, and the data processing efficiency is improved. Through the integration and the use of the orthogonal base matrix, the accuracy and the robustness of data processing are enhanced. The wavelet basis and the Fourier basis are used as sparse basis, so that local characteristics and frequency components of signals can be better captured, and the reconstruction quality is improved. The application of the least square iterative algorithm further optimizes the reconstruction process of the conductivity matrix, and ensures the accuracy and reliability of the reconstruction result. The real-time conductivity U obtained by the method can provide accurate data support for the electrical property analysis of the material.
Further, by dynamically adjusting the monitoring parameters by comparing the real-time conductivity with a preset standard conductivity range, an adaptive monitoring strategy is provided, which can respond accurately to different conductivity conditions. When the real-time conductivity is higher or lower than the preset standard conductivity range, the abnormal conductivity region can be more effectively positioned and evaluated by adjusting the angle or the radius, so that more accurate material characteristic analysis is realized.
Furthermore, the system can adaptively adjust the monitoring parameters, and ensure that high-quality signal data can be obtained under different conditions, thereby improving the accuracy and repeatability of measurement. The application of the compressed sensing theory greatly reduces the data acquisition requirement, and simultaneously maintains the high precision of the reconstruction result. The dynamic adjustment and correction mechanism enables the system to respond to real-time monitoring results quickly and optimize measurement strategies.
Drawings
FIG. 1 is a flow chart of a sector scanning detection method for detecting supercapacitor conductivity according to the present embodiment;
FIG. 2 is a schematic diagram of the present embodiment monitoring real-time thermo-acoustic signals at various monitoring points;
FIG. 3 is a diagram showing a decision logic for deciding to adjust a preset rotational angular velocity according to the present embodiment;
FIG. 4 is a schematic diagram of a sector scanning detection system for detecting supercapacitor conductivity according to the present embodiment;
the reference numerals indicate 1, a pulse magnetic field, 2, a target body to be measured and 3, an ultrasonic transducer.
Detailed Description
The invention will be further described with reference to examples for the purpose of making the objects and advantages of the invention more apparent, it being understood that the specific examples described herein are given by way of illustration only and are not intended to be limiting.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
In addition, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, integrally connected, mechanically connected, electrically connected, directly connected, indirectly connected through an intermediate medium, or in communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, a flow chart of a sector scanning detection method for detecting the conductivity of a supercapacitor according to the present embodiment is shown;
Please continue to refer to fig. 2, which is a schematic diagram of the present embodiment for monitoring real-time thermo-acoustic signals at each monitoring point;
The embodiment provides a sector scanning detection method for detecting the conductivity of a supercapacitor, which comprises the following steps:
placing an object 2 to be tested in a pulse magnetic field 1, rotating a preset number of ultrasonic transducers 3 by a preset angle at a preset rotation radius and a preset rotation angular velocity, and monitoring real-time thermo-acoustic signals at each monitoring point, wherein the rotation radius is the distance between the lowest ultrasonic transducer 3 and the center of the object to be tested, and the rotation angle is the rotation range of the ultrasonic transducer 3 around the object 2 to be tested, wherein the preset angle is smaller than 360 degrees, so that the scanning range is in a fan shape;
Extracting the real-time signal intensity and the real-time signal stability of the real-time thermo-acoustic signal;
Adjusting a preset quantity according to the real-time signal strength and the preset standard signal strength;
Adjusting a preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;
Adjusting a preset angle according to the maximum value of all real-time signal intensities in the preset rotation time and a preset standard peak value range;
Reconstructing a conductivity matrix of the target body to be detected according to the real-time thermo-acoustic signals at each monitoring point by using a preset algorithm based on a compressed sensing theory, and extracting real-time conductivity;
Adjusting a preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range;
And constructing a conductivity distribution diagram according to the real-time thermo-acoustic signal with the real-time conductivity within the preset standard conductivity range and outputting the conductivity distribution diagram.
Firstly, placing a super capacitor to be tested in a pulse magnetic field, and carrying out sector scanning on the capacitor by utilizing a plurality of ultrasonic transducers under the preset rotation radius and speed. During the scanning process, the system monitors and records the real-time thermo-acoustic signal generated by each monitoring point. These signals are converted into digital signals by an analog-to-digital converter, and the signal strength and stability are calculated. And comparing the parameters with preset standards, and dynamically adjusting the number, rotation angular speed and angle of the ultrasonic transducers to optimize the quality and efficiency of signal acquisition. And then, processing and reconstructing the collected thermo-acoustic signals by using an algorithm based on a compressed sensing theory, so as to obtain a conductivity matrix of the capacitor. And finally, according to the comparison result of the real-time conductivity and the preset conductivity range, further adjusting the rotation radius or angle, ensuring the measurement accuracy, and constructing a conductivity distribution map for output.
Through the combined use of the pulse magnetic field and the ultrasonic transducer, the thermo-acoustic response of the super capacitor can be efficiently excited and captured, and the sensitivity and the accuracy of detection are improved. The extraction of the real-time signal strength and stability and the dynamic parameter adjustment mechanism enhance the self-adaptive capacity of the system and ensure that high-quality signal data can be obtained under different conditions. The algorithm based on the compressed sensing theory not only improves the efficiency of data processing, but also reduces the requirements on the quantity and the performance of monitoring equipment, and visual and detailed capacitor performance information is provided for users by constructing a conductivity distribution diagram, thereby being beneficial to the optimal design and quality control of materials.
Specifically, extracting the real-time signal strength of the real-time thermo-acoustic signal includes:
converting the real-time thermo-acoustic signal into a digital signal by using an analog-to-digital converter, calculating the root mean square of the digital signal in a preset window time period to obtain the real-time signal intensity, wherein, I is real-time signal intensity, T is a preset window time period, v (T) is a real-time voltage value in a digital signal of time T, and dt is a unit time interval.
The received analog thermo-acoustic signal is first converted to digital form using an analog-to-digital converter to facilitate further digital signal processing. Then, a predetermined window period is selected, and the root mean square calculation is performed on the digital signal during the period. Root mean square value is an effective measure of signal power by calculating the average of the squares of all sample points of the signal within the window and then taking the square root. This value reflects the strength of the signal and is a key step in analyzing the signal characteristics and performing subsequent processing.
The root mean square value provides an accurate measure of signal power, helps to distinguish between signals and noise, thereby improving the accuracy of signal detection, and the use of an analog-to-digital converter can ensure that the digital processing of the signals is not affected by interference and attenuation possibly encountered in the transmission process of analog signals, and can provide reliable data support for subsequent signal stability evaluation and system parameter adjustment through accurate extraction of the real-time signal strength, thereby optimizing the efficiency of the whole detection system.
Specifically, extracting the real-time signal stability of the real-time thermo-acoustic signal includes:
calculating standard deviation of the real-time thermo-acoustic signal converted into the digital signal to obtain the real-time signal stability, wherein, S is the real-time signal stability, v' is the average of all real-time voltage values over the window time period.
First, the real-time thermo-acoustic signal is converted into a digital signal by an analog-to-digital converter, which ensures the accuracy of the signal and the feasibility of subsequent processing. These digitized signal samples are then analyzed over a particular time window, and the deviation of each sample value from the average of the signal over the window is calculated. The variances are squared, summed, and divided by the number of samples to obtain the variance. Finally, the square root of the square difference is divided to obtain the standard deviation, and the fluctuation degree of the signal, namely the stability of the signal, is quantized by the numerical value.
The standard deviation provides an objective measure of the signal fluctuation of the quantification so that the stability of the signal can be accurately assessed. A smaller standard deviation means that the signal fluctuations are smaller, indicating a high signal quality and a low noise level, thus contributing to an improved accuracy of the signal processing. Monitoring signal stability in real time allows the system to dynamically adjust parameters, such as the monitoring frequency or gain of the ultrasound transducer, to accommodate changes in the signal, ensuring measurement continuity and reliability.
Specifically, the adjusting the preset number according to the real-time signal strength and the preset standard signal strength includes:
when the real-time signal strength is smaller than the preset standard signal strength, the preset number is increased and adjusted according to the real-time signal strength and the preset standard signal strength in a preset number adjustment proportion, wherein W '=w+a1× (I-I0), W' is the adjusted preset number, W is the preset number, a1 is the preset number adjustment proportion, and I0 is the preset standard signal strength.
The preset quantity adjustment ratio a1 is a scaling factor for adjusting the preset quantity W. When there is a difference between the real-time signal strength I and the preset standard signal strength I0, the scaling factor determines the magnitude by which the preset number W is adjusted according to the difference. Depending on the sensitivity requirements of the system and the response speed of the system, it is usually determined experimentally or empirically. In this embodiment, a quick response to a change in signal strength is required, and the preset quantity adjustment ratio a1 is set to 0.5.
Firstly, the intensity of a thermoacoustic signal is monitored and calculated in real time, and a numerical value of the real-time signal intensity is obtained. The real-time signal strength is then compared with a predetermined standard signal strength. If the real-time signal intensity is found to be lower than the preset standard signal intensity, the proportion is adjusted according to the difference value between the real-time signal intensity and the preset quantity, and the use quantity of the ultrasonic transducers is automatically increased. This increased amount is calculated in accordance with a predetermined adjustment ratio to ensure that the signal strength meets or exceeds the desired criteria.
The quantity of the ultrasonic transducers is adjusted according to the comparison result of the real-time signal intensity and the preset standard signal intensity, so that the quality of signal acquisition and the self-adaptive capacity of the system can be remarkably improved. When the signal intensity is insufficient, the ultrasonic transducer is added to enhance the receiving capability of the signal, so that the definition and accuracy of the signal are ensured, and the measurement error caused by weak signal is avoided.
Please continue to refer to fig. 3, which is a logic diagram illustrating the decision of adjusting the preset rotation angular velocity according to the present embodiment;
Specifically, the adjusting the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability includes:
When the real-time signal stability is greater than the preset standard signal stability, the preset rotation angular velocity is reduced and adjusted according to the real-time signal stability and the preset standard signal stability by a preset stability adjustment proportion, wherein V '=v-a2× (S-S0), V' is the adjusted preset rotation angular velocity, V is the preset rotation angular velocity, a2 is the preset stability adjustment proportion, and S0 is the preset standard signal stability.
The preset stability adjustment ratio a2 is a scale factor for adjusting the rotation angular velocity according to the signal stability variation. Depending on the sensitivity requirements of the system to signal stability and the required speed of the adjustment response. Typically set to a value less than 1 to ensure a smooth adjustment. In this embodiment, the system performance requirement and the experimental result are determined to be 0.3. The system can ensure the sensitive response of the system to the stability change, avoid excessive or insufficient adjustment and improve the stability of the system.
The fluctuations of the signal are quantified by calculating the standard deviation of the signal. The system compares the obtained real-time signal stability with a preset standard signal stability. When the real-time signal stability exceeds the preset standard signal stability, namely the signal fluctuation is larger, the system can adjust the proportion according to the difference of the real-time signal stability and the preset stability, and correspondingly reduce the preset rotation angular velocity of the ultrasonic transducer. This adjustment aims at increasing the time resolution of the signal acquisition by slowing down the rotational angular velocity, thereby obtaining a more stable and reliable signal.
The method for adjusting the preset rotation angular velocity according to the real-time signal stability can effectively optimize the acquisition quality of the signal. When the signal fluctuation is large, the rotation angular velocity is slowed down, which is helpful for the system to capture the signal change more finely, reduces signal distortion or omission caused by rapid rotation, improves the flexibility and adaptability of the system, and ensures that high-quality signal data can be obtained under different measurement conditions.
Specifically, adjusting the preset angle according to the maximum value of all real-time signal intensities within the preset rotation time and the maximum value of the preset standard peak range includes:
And when the maximum value of the total real-time signal intensity is larger than the maximum value of the preset standard peak value range, reducing and adjusting the preset angle according to the maximum value of the total real-time signal intensity, the maximum value of the preset standard peak value range and the preset peak value adjusting proportion, wherein D '=D-a 3× (I-Imax), D' is the adjusted preset angle, D is the preset angle, a3 is the preset peak value adjusting proportion, and Imax is the maximum value of the preset standard peak value range.
The preset peak adjustment ratio a3 is a scale factor for adjusting the preset angle according to the peak variation of the signal intensity. Depending on the sensitivity of the system to signal strength peaks and the required adjustment amplitude. Typically set to a value less than 1, this embodiment is set to 0.05 to ensure smooth and efficient angular adjustment.
Specifically, adjusting the preset angle according to the maximum value of all real-time signal intensities within the preset rotation time and the minimum value of the preset standard peak range includes:
when the maximum value of all the real-time signal intensities is smaller than the minimum value of the preset standard peak value range, increasing and adjusting the preset angle according to the maximum value of all the real-time signal intensities, the minimum value of the preset standard peak value range and the preset peak value adjusting proportion, wherein D' =D+a3× (Imin-I), and Imin is the minimum value of the preset standard peak value range.
Firstly, collecting the real-time signal intensity of all monitoring points in a preset rotation time, and determining the maximum value of the signal intensity. This maximum value is compared with the boundary value of the preset standard peak range. If the maximum value of the real-time signal intensity exceeds the maximum value of the preset standard peak value range, the preset angle is reduced according to the exceeding proportion and the preset peak value adjusting proportion, so that the area with high signal intensity is scanned more finely. Conversely, if the maximum value of the real-time signal strength is lower than the minimum value of the preset standard peak value range, the preset angle is increased according to the insufficient proportion and the peak value adjustment proportion, so that the monitoring range is enlarged, and the coverage of the signal strength area possibly omitted is ensured.
When the signal intensity exceeds the expected high value, fine scanning of the high-intensity area of the signal can be realized by reducing the preset angle, and accurate positioning and analysis of the signal source are facilitated. This not only improves the resolution of the monitoring, but also enhances the ability to identify anomalies or critical areas. When the real-time signal strength is lower than the expected value, the preset angle is increased to ensure the integrity of the whole monitoring area, so that any important information which can influence the evaluation result is avoided being omitted.
Specifically, the reconstructing a conductivity matrix of the target body to be detected by using a preset algorithm based on a compressed sensing theory through real-time thermo-acoustic signals of each monitoring point, and extracting real-time conductivity from the conductivity matrix comprises:
Sampling N random vectors of the thermoacoustic signals randomly monitored by the ultrasonic transducer in the rotation time to obtain sampling data;
Integrating the sampled data to obtain a corresponding velocity potential function matrix ;
Selecting an orthogonal base matrix, and calculating an observation matrix K according to the speed potential function data of random sampling;
Reconstructing a heat absorption function matrix Q' of the target body to be detected by using the wavelet basis and the Fourier basis as sparse basis;
Reconstructing a conductivity matrix of a target body to be detected by utilizing a least square iterative algorithm ;
Extracting real-time conductivity U corresponding to each monitoring point from the reconstructed conductivity matrix;
The sound pressure wave equation satisfied by the thermoacoustic signal is:
;
Where p (r, t) is the thermo-acoustic signal received by the ultrasonic transducer at the monitoring point r, 2 P (r, t) is the sum of the second derivatives of the thermoacoustic signal p (r, t) in space, c s 2 represents the square of the wave's speed of sound, Q (r ') is the intensity of the thermoacoustic source at location r ', t is time,(T) is a Dirac function of time t, C P is the specific heat capacity of the material, beta is the volume expansion coefficient of the material, r' represents the position of the object to be measured, and the velocity potential function of introducing thermoacoustic signal vibration(r,t),(R, t) is a velocity potential function matrixThe relation between the display form at the monitoring point r and the time t and the sound pressure is as follows:
;
the velocity potential wave equation for the thermo-acoustic signal vibration is:
;
the above formula is solved by using the selectivity of the Grignard function and the Dirac function, and the expression of the velocity potential can be obtained as follows:
R is a preset rotation radius, and l is an integral variable of a range used for integration and a variation in an integration process;
Represented in matrix form by a moment method:
F=K×Q ;
wherein F is a velocity potential function The column vector corresponding to (r, t), Q is the column vector corresponding to the intensity Q (r ') of the thermoacoustic source of the object to be measured at the position r', and K is the matrix related to the acoustic field. Assuming that y discrete points exist in the detection area, the number of ultrasonic transducers is m, and the time point of each ultrasonic transducer for collecting data is n, the speed potential function corresponding to the collected sound signal is obtained(R, t) is discretized into(R k,tl) wherein[1:m],[1:N ], F is a column vector of dimension m×n. K is a matrix with dimensions of m x n rows and y columns. If the coefficient matrix K is nonsingular, the solution can be adopted by a generalized inversion method, namely the heat absorption coefficient distribution is as follows:
Q=K-1F;
Randomly sampling signals acquired by an ultrasonic transducer and forming corresponding velocity potential function moments And observing the matrix K, and then reconstructing the distribution of the heat absorption function of the object to be detected by adopting a wavelet basis and a Fourier basis as sparse basis.
In the process of reconstructing the conductivity matrix by using an algorithm based on a compressed sensing theory, sampling N random vectors of M thermo-acoustic signals obtained by randomly monitoring an ultrasonic transducer in rotation time to obtain sampling data. Then, the sampled data are integrated to obtain a velocity potential function matrix. Then, an orthogonal basis matrix is selected and the velocity potential function data is used to calculate an observation matrix. And then, reconstructing a heat absorption function matrix Q' of the target body by adopting a wavelet basis and a Fourier basis as sparse basis. On this basis, a least squares iterative algorithm is applied to optimize and reconstruct the conductivity matrix. And finally, extracting the real-time conductivity U corresponding to each monitoring point from the reconstructed conductivity matrix.
The conductivity matrix is reconstructed by adopting the algorithm of the compressed sensing theory, and the complete signal can be effectively recovered from the sparse sampling data under the condition that the signal sampling is far lower than the Nyquist rate, so that the required monitoring data volume is greatly reduced, and the data processing efficiency is improved. Through the integration and the use of the orthogonal base matrix, the accuracy and the robustness of data processing are enhanced. The wavelet basis and the Fourier basis are used as sparse basis, so that local characteristics and frequency components of signals can be better captured, and the reconstruction quality is improved. The application of the least square iterative algorithm further optimizes the reconstruction process of the conductivity matrix, and ensures the accuracy and reliability of the reconstruction result. The real-time conductivity U obtained by the method can provide accurate data support for the electrical property analysis of the material.
Specifically, the adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range includes:
When the real-time conductivity is larger than the maximum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is larger than the preset standard difference, reducing the adjusted preset angle according to the difference, the preset standard difference and the preset angle correction proportion, wherein D ' = D ' -a4× (U-Umax), D ' is the corrected preset angle, a4 is the preset angle correction proportion, U is the real-time conductivity, and Umax is the maximum value of the preset standard conductivity range;
When the real-time conductivity is smaller than the minimum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is larger than the preset standard difference, the adjusted preset angle is increased according to the difference, the preset standard difference and the preset angle correction proportion, wherein D '= D' +a4× (Umin-U), and Umin is the minimum value of the preset standard conductivity range;
When the real-time conductivity is larger than the maximum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is smaller than the preset standard difference, reducing the preset rotating radius according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment proportion, wherein R '=R-a 5× (U-Umax), R' is the adjusted preset rotating radius, R is the preset rotating radius, and a5 is the preset radius adjustment proportion;
when the real-time conductivity is smaller than the minimum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is smaller than the preset standard difference, the preset rotation radius is increased according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment proportion, wherein R' =R+a5× (Umin-U).
In the process of adjusting the preset radius of rotation or correcting the preset angle, the system first evaluates the relationship between the real-time conductivity U and the preset standard conductivity range (Umin, umax). If the real-time conductivity U exceeds Umax and the difference between U and Umax is greater than the preset standard difference, the system uses the preset angle correction proportion a4 to reduce the adjusted preset angle D' according to the difference so as to reduce the monitoring focus and more accurately position the high-conductivity region. Conversely, if U is lower than Umin and the difference between U and Umax is greater than the preset standard deviation, the system will increase the adjusted preset angle D' to expand the monitoring range and capture the low conductivity region that may be missed. If U exceeds Umax but the difference is less than the preset standard deviation, the system uses a preset radius adjustment ratio a5 to reduce the preset radius R to improve the monitoring accuracy. If U is below Umin and the difference is less than the preset standard deviation, the system increases the preset radius of rotation R to ensure full coverage of the low conductivity region.
The monitoring parameters are dynamically adjusted through comparison of the real-time conductivity and the preset standard conductivity range, so that a self-adaptive monitoring strategy is provided, and accurate response can be made for different conductivity conditions. When the real-time conductivity is higher or lower than the preset standard conductivity range, the abnormal conductivity region can be more effectively positioned and evaluated by adjusting the angle or the radius, so that more accurate material characteristic analysis is realized.
Referring to fig. 4, a schematic diagram of a sector scanning detection system for detecting the conductivity of the supercapacitor according to the present embodiment is shown;
the present embodiment provides a sector scanning detection system for detecting the conductivity of a supercapacitor, comprising:
The data monitoring module comprises a preset number of ultrasonic transducers 3, is used for rotating at a preset angle with a preset rotation radius and a preset rotation angular velocity, and monitors real-time thermo-acoustic signals from the target body 2 to be detected in the pulse magnetic field 1 at each monitoring point;
The signal extraction module is connected with the data monitoring module and used for extracting the real-time signal intensity and the real-time signal stability of the real-time thermo-acoustic signal according to a built-in preset extraction algorithm;
The adjusting module is connected with the signal extracting module and is used for adjusting the preset quantity according to the real-time signal strength and the preset standard signal strength;
the adjusting module is also used for adjusting a preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;
The adjusting module is also used for adjusting a preset angle according to the maximum value of all real-time signal intensities in the preset rotation time and a preset standard peak value range;
The conductivity reconstruction extraction module is respectively connected with the adjustment module and the data monitoring module and is used for reconstructing a conductivity matrix of the target body to be detected through real-time thermo-acoustic signals of all monitoring points by using a preset algorithm based on a compressed sensing theory and extracting real-time conductivity from the conductivity matrix;
The correction module is connected with the conductivity reconstruction extraction module and is used for adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range or correcting the adjusted preset angle;
the output module is respectively connected with the conductivity reconstruction extraction module and the correction module and is used for constructing and outputting a conductivity distribution diagram according to the real-time thermoacoustic signal of which the real-time conductivity is in the preset standard conductivity range.
The workflow of the sector scanning detection system begins with a data monitoring module that monitors real-time thermo-acoustic signals of a target object in a pulsed magnetic field using a preset number of ultrasonic transducers according to a preset radius of rotation and speed and angle. The signal extraction module processes the received signal and extracts the signal strength and stability. The adjusting module is used for comparing the extracted signal parameters with preset standard signal intensity and dynamically adjusting the preset number, the preset rotation angular velocity and the preset angle of the ultrasonic transducer so as to optimize signal acquisition. The conductivity reconstruction extraction module uses a compressed sensing theory algorithm to reconstruct a conductivity matrix in combination with the monitoring data and extract real-time conductivity. And the correction module adjusts the rotation radius or correction angle according to the comparison result of the real-time conductivity and the preset range so as to improve the measurement accuracy. Finally, the output module constructs and outputs a conductivity profile providing visual data for analysis and evaluation.
The system can adaptively adjust the monitoring parameters, and ensure that high-quality signal data can be obtained under different conditions, thereby improving the accuracy and repeatability of measurement. The application of the compressed sensing theory greatly reduces the data acquisition requirement, and simultaneously maintains the high precision of the reconstruction result. The dynamic adjustment and correction mechanism enables the system to respond to real-time monitoring results quickly and optimize measurement strategies.
In the present embodiment, the setting of the preset value is generally based on the following factors:
The number of ultrasound transducers depends on the size and complexity of the monitored target and the signal coverage required.
It is often provided that the number may vary from a few to tens.
In this embodiment, it is assumed that 5 ultrasonic transducers are provided.
Radius of rotation-depending on the size of the monitored target and the depth of monitoring required.
It is often provided that the radius may vary from a few centimetres to a few metres.
In this example, it is assumed that the setting is 0.2 m.
Rotational angular velocity, the time resolution affecting signal acquisition.
It is often set that the speed may vary from a few degrees per second to tens of degrees.
In this embodiment, it is assumed that the setting is 10 degrees/sec.
Preset angle: affecting the distribution density of the monitored points.
It is generally provided that the angle range may be from 0 to 360 degrees, the specific angle being determined by the monitoring requirements.
In this embodiment, it is assumed that the entire 360 degree range is used for monitoring.
And the preset standard signal intensity is used for comparing with the real-time signal intensity to determine whether the number of the ultrasonic transducers needs to be adjusted.
It is typically set according to the system sensitivity and the expected signal strength.
In this embodiment, it is assumed that 1000mV is set.
And the preset standard signal stability is used for comparing with the real-time signal stability to determine whether the rotation angular velocity needs to be adjusted.
Typically set according to signal stability requirements.
In this embodiment, it is assumed that 50mV is set.
And the preset standard peak value range is used for comparing with the maximum value of the real-time signal intensity and adjusting the preset angle.
It is typically set according to the expected fluctuation range of the signal.
In this example, it is assumed that the maximum value is 1500mV and the minimum value is 500mV.
And the preset standard conductivity range is used for comparing with the real-time conductivity and adjusting the rotation radius or angle.
It is generally set according to the desired conductivity characteristics of the material.
In this embodiment, it is assumed that the maximum value is set to 0.01S/m and the minimum value is set to 0.001S/m.
The preset angle correction ratio a4 is an adjustment ratio for calculating an angle, and the preset radius adjustment ratio a5 is an adjustment ratio for calculating a radius.
It is usually set according to the system response speed and the adjustment accuracy requirement.
In this embodiment, these ratios are determined experimentally according to the specific application, and the preset angle correction ratio a4 and the preset radius adjustment ratio a5 are set to 0.1, respectively.
The benefits of this arrangement in this embodiment are:
the use of 5 ultrasonic transducers can provide adequate signal coverage while avoiding excessive complexity of the system.
A preset radius of rotation of 0.2 meters allows for full monitoring of medium sized supercapacitors.
The rotational angular velocity of 10 degrees/second provides good time resolution while avoiding signal blurring that may be caused by too fast rotation.
The preset standard signal intensity and the preset standard signal stability are set in a reasonable range, so that the sensitivity of the system to signal changes can be ensured, and meanwhile, excessive adjustment is avoided.
By setting a preset standard peak value range, the system can adaptively adjust and monitor a preset angle and concentrate on an area with abnormal signal intensity.
The setting of the preset standard conductivity range allows the system to identify and adjust conductivity anomalies, improving measurement accuracy.
The preset angle correction proportion and the preset radius adjustment proportion are set, so that the system can carry out fine adjustment according to real-time data, and the monitoring strategy is optimized.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
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Inventor after: Yang Yanju Inventor after: Meng Yan Inventor after: Qu Lili Inventor after: Cheng Chunlei Inventor after: Li Hailu Inventor after: Li Xiaoping Inventor before: Yang Yanju Inventor before: Meng Yan Inventor before: Zhai Lili Inventor before: Cheng Chunlei Inventor before: Li Hailu Inventor before: Li Xiaoping |