CN113984886A - Method for improving thread defect detection precision - Google Patents
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Abstract
The invention discloses a method for improving thread defect detection precision, which comprises the following steps: s1, combining the eddy current sensor and the giant magnetoresistance sensor in an arc structure to form an array eddy current sensor; s2, mounting the array eddy current sensor on the detection sensing head part of the floating probe to form a sensing structure; s3, acquiring defect characteristics of the detected thread area; s4, acquiring defect information in the thread structure; s5, the defect characteristics and the defect information are weighted and fused, the invention is suitable for the technical field of thread defect detection, an automatic detection device is adopted to realize uniform rotation of the array eddy current sensor around the thread, the sensor performs uniform circular motion to carry out circumferential scanning on the thread, the detection part is comprehensive, the detection precision is high, the missed detection is not easy, the detection precision and the working efficiency can be effectively improved, and meanwhile, the automatic detection device is simple and rapid to operate, and the working efficiency is greatly improved.
Description
Technical Field
The invention belongs to the technical field of thread defect detection, and particularly relates to a method for improving thread defect detection precision.
Background
The thread structure part is an element widely applied to the connection, fastening and other aspects of equipment or parts, and is generally applied to various industries such as aviation, railway, oil and gas, transportation and the like. The thread structure has the advantages that the thread structure plays a role in connection and fastening when in use, and generally receives forces under the conditions of axial tension or compression, radial shear, bending stress and the like under a load state, wherein the tensile stress or the compressive stress received by the thread structure along the axial direction is the main stress condition, and plays a vital role in the industrial use process. Because the inside of the thread structure generates and has some defects in the production process or the subsequent use process, the thread structure is damaged or fails under the action of stress, and serious life and property loss can be caused. Therefore, the defects of the thread structure can be found in advance, the safety and reliability reduction caused by the damage of the thread structure can be prevented and stopped in time, and the normal operation of the equipment is ensured. The regular nondestructive detection of the thread structure is an indispensable detection link and is an important task in mechanical manufacturing, maintenance and repair.
The methods such as a ray detection method, an ultrasonic detection method, a magnetic powder detection method and the like have the inconvenience factors of high detection cost, complicated working procedures, surface cleaning and the like in the actual thread defect detection process. Although the eddy current detection method can solve the inconvenience factor of the method, the detection may be missed for some defects smaller than the diameter of the detection coil, and the detection sensitivity of the two sides of the coil is poor in the detection of the thread with the arc-shaped curved surface structure.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for improving the thread defect detection precision.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for improving thread defect detection precision comprises the following steps:
s1, combining the eddy current sensor and the giant magnetoresistance sensor in an arc structure to form an array eddy current sensor;
s2, mounting the array eddy current sensor on the detection sensing head part of the floating probe to form a sensing structure;
s3, acquiring defect characteristics of the detected thread area;
s4, acquiring defect information in the thread structure;
s5 performs weighted fusion of the defect feature and the defect information.
Preferably, in step S1, the exciting coil in the differential measurement sensor serves as an exciting source for eddy current sensing and also serves as a magnetic field exciting source for giant magnetoresistance detection, and the differential measurement sensor and the giant magnetoresistance sensor are combined in an arc-shaped spatial structure to ensure better surface adhesion in the curved surface structure of the thread.
Preferably, in step S2, the detecting sensor part of the floating probe has angular adjustability, the external motor drives the whole sensing part to make a circular motion around the screw structure, the array eddy current sensor advances along the screw structure under the action of the screw structure, and the probe mounting beam can adjust the mounting angle of the array eddy current sensor for detecting some screw structures with angular inclinations.
Preferably, in step S3, a sinusoidal excitation signal with a certain frequency is loaded into the excitation coil, the frequency of the excitation signal needs to be calculated according to the structural parameters of the thread and the electromagnetic properties of the material, the differential signal receiving coil is firstly filtered and amplified through an adaptive signal after the signal is output, feature extraction is performed on the obtained defect signal on the basis of establishing a mathematical model of the thread eddy current, a signal at a peak in a defect detection signal curve is extracted to perform discrete fourier transform, and the defect feature of the thread region detected by the eddy current sensor is obtained according to the obtained relationship among the signal feature, the model analysis and the fitting by fitting the defect size and using a voltage peak, a peak time, a zero-crossing frequency and a peak frequency relational expression.
Preferably, in step S4, the giant magnetoresistance sensor detects the magnetic field generated by the eddy current sensing excitation, performs signal filtering, amplification and other processing on the sensing signal on the basis of a mathematical detection model and a magnetic coupling noise model, and extracts data features according to the detected mathematical model and an actual calibration model to obtain defect information in the thread structure.
Preferably, in step S5, when both defect information are known, the defect signals are weighted and fused according to different detection characteristics of the eddy current sensor and the giant magnetoresistance sensor with respect to the thread defect, so as to improve the sensitivity of defect detection and accurately provide information such as the size, position, and type of the defect.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
according to the invention, the array eddy current sensor is rotated around the screw thread at a constant speed by adopting the automatic detection device, the sensor performs constant-speed circular motion to scan the screw thread in the circumferential direction, the detection part is comprehensive, the detection precision is high, the omission is not easy, the phenomena of large detection error and low efficiency caused by manual operation are avoided, the detection precision and the working efficiency can be effectively improved, meanwhile, the automatic detection device is simple and rapid to operate, and the working efficiency is greatly improved.
Drawings
FIG. 1 is a flow chart of a method of improving thread defect detection accuracy of the present invention;
FIG. 2 is a schematic view of a differential measurement eddy current sensor in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram of a sensing device combining eddy current sensing and giant magnetoresistance sensing according to an embodiment of the present invention;
FIG. 4 is a flowchart of a signal correlation processing algorithm according to an embodiment of the present invention;
fig. 5 is a schematic view of an automatic detection device according to an embodiment of the invention.
Detailed Description
The following further describes a specific embodiment of the method for improving the thread defect detection accuracy according to the present invention with reference to fig. 1 to 5. A method of improving the accuracy of thread defect detection of the present invention is not limited to the description of the following embodiments.
Example 1:
this embodiment provides a specific implementation of a method for improving the thread defect detection accuracy, as shown in fig. 1 to 5, including the following steps:
s1, combining the eddy current sensor and the giant magnetoresistance sensor in an arc structure to form an array eddy current sensor;
s2, mounting the array eddy current sensor on the detection sensing head part of the floating probe to form a sensing structure;
s3, acquiring defect characteristics of the detected thread area;
s4, acquiring defect information in the thread structure;
s5 performs weighted fusion of the defect feature and the defect information.
Further, as shown in fig. 2, 1 and 3 are differential signal receiving coils of the sensing probe, 2 is an excitation coil of the sensing probe, and in step S1, the excitation coil of the differential measurement sensor is used as an excitation source for eddy current sensing and also as a magnetic field excitation source for giant magnetoresistance detection, and the differential measurement sensor and the giant magnetoresistance sensor are combined in an arc-shaped spatial structure to ensure better surface adhesion in the curved surface structure of the thread.
Further, in step S2, the detecting sensor part of the floating probe has angular adjustability, the external motor drives the whole sensing part to make circular motion around the screw structure, the array eddy current sensor advances along the screw structure under the action of the screw structure, and the probe mounting beam can adjust the mounting angle of the array eddy current sensor for detecting some screw structures with angular inclinations.
Further, in step S3, a sinusoidal excitation signal with a certain frequency is loaded into the excitation coil, the frequency of the excitation signal needs to be calculated according to the structural parameters of the thread and the electromagnetic properties of the material, the differential signal receiving coil 1 firstly performs adaptive signal filtering and amplification after the signal is output, performs feature extraction on the obtained defect signal on the basis of establishing a mathematical model of the thread eddy current, extracts a signal at a peak in a defect detection signal curve to perform discrete fourier transform, and fits the defect size and obtains the defect feature of the thread region detected by the eddy current sensor according to the obtained relationship among the signal feature, the model analysis and the fitting by using a voltage peak value, a peak time, a zero-crossing frequency and a peak frequency relational expression.
Further, in step S4, the giant magnetoresistance sensor detects the magnetic field generated by the eddy current sensing excitation, performs signal filtering, amplification and other processing on the sensing signal on the basis of a mathematical detection model and a magnetic coupling noise model, and extracts data features according to the detected mathematical model and an actual calibration model to obtain defect information in the thread structure.
Further, in step S5, when both the defect information are known, the defect signals are weighted and fused according to the different detection characteristics of the eddy current sensor and the giant magnetoresistance sensor with respect to the thread defect, so as to improve the sensitivity of defect detection and accurately provide information such as the size, position, and type of the defect.
Working principle, as shown in fig. 1-5:
the differential eddy current sensor adopts a differential measurement type eddy current sensing probe, the detection work part of the differential eddy current sensor is completed by two measuring coils, and the excitation work is completed by only one coil. The difference measurement type probe is internally designed and manufactured with two identical induction coils and connected with the same-name end, wherein the connection of the same-name end refers to the connection of the leading-out part and the leading-in part of the two coils. Therefore, the interference of the external environment can be cancelled, and the sensitivity and the resolution ratio during detection are improved.
In the detection process, a sinusoidal alternating current signal is applied to the middle exciting coil for excitation, and the defect detection work is completed by the induction coils on the two sides. According to the law of electromagnetic induction, when the exciting coil is electrified with alternating current
When the magnetic field is applied, an alternating magnetic field is generated around the coil
It can generate induced current on the surface of the tested piece in the magnetic field
I.e. the electrical eddy current. At the same time, the electric eddy current
Again can produceNew alternating magnetic field
And
the direction is opposite, thereby causing the equivalent impedance of the detection coil of the probe to change correspondingly.
When the surface and the inside of the thread are free of defects, the eddy current formed near the surface is uniformly distributed. When the difference measurement type eddy current probe scans the position where the detected conductor has no defects such as cracks, the absolute value voltage of the vector sum of the magnetic fields induced by the two induction coils and the signal difference is theoretically zero. This is the most fundamental reason for the improved sensitivity after differential connection. When the difference measurement type eddy current probe scans the position where the thread defect exists, the eddy current flows along the direction of the defect due to the change of the structural property of the thread, and the magnetic field distribution of the measured thread is disturbed. When only one of the induction coils at the two sides scans the defect position, the amplitude, the phase and the like of the characteristic signal induced by the measuring coil are changed, and the induction signal output by the induction coil only contains defect information. However, in the detection process of some fine defects and thread curved surface defects, the differential eddy current sensing detection precision is low, and a giant magnetoresistance sensing system is introduced to improve the thread defect detection precision. In a giant magnetoresistance detection system, a novel giant magnetoresistance sensor is used for replacing a detection coil as a detection device, and an excitation coil in eddy current detection is used as a change excitation source of an external magnetic field, so that the detection frequency range can be from DC to 1MHz, and the detection precision is improved; the change of the magnetic field can be directly detected, the detection result is more convenient to analyze and can be visually displayed, the detection result is not limited by the radius of the detection coil any more, and the detection capability of depth defects and fine defects is improved. The giant magnetoresistance sensing technology and the eddy current detection technology are combined, the space structures of the giant magnetoresistance sensing technology and the eddy current detection technology are designed into arc structures corresponding to the threads, so that the shapes of the surfaces of the threads can be better attached, and the precision of thread defect detection is improved due to mutual supplement of the two sensing technologies.
In the signal processing related algorithm, the two technologies need to be respectively subjected to signal processing and finally the defect signals need to be fused, so that the detection advantages of the two technologies are exerted, and the defect detection precision is improved. In the eddy current defect detection, besides displaying a strip chart and an impedance plane chart, a mathematical model for calculating the thread eddy current is required to be established, the time domain characteristic and the amplitude-frequency characteristic of a detection signal are analyzed, drift noise in the signal is removed by adopting methods such as self-adaptive filtering and the like, a signal at a peak in a defect detection curve is extracted to be subjected to discrete Fourier transform, the defect size is fitted, a voltage peak value, peak time, zero-crossing frequency and peak frequency relational expression is utilized, a two-dimensional matrix of the defect characteristic is obtained by applying an interpolation algorithm, the matrix is subjected to isoline imaging, and the information such as the defect size, position, shape, burial depth and the like is reflected by the size, position, shape and isoline numerical value of an abnormal region in an image. A hardware signal processing circuit designed in giant magnetoresistance detection is used for carrying out anti-interference analysis and simulation, and a magnetic coupling noise model is established. The signal line is subjected to laminated wiring to inhibit magnetic coupling noise on a signal loop, an amplification circuit built by the integrated operational amplifier is subjected to comparative analysis of an oscillation model on the basis of considering the parasitic effect of a PCB (printed circuit board), and the signal is optimized by combining an expression form and a Bode diagram of a transfer function. Meanwhile, self-adaptive filtering is carried out on giant magnetic sensing signals, and the characteristics of the signals are analyzed by combining the established thread mathematical model. After the defect signals of the two technologies are obtained, the information such as the area, the position and the like of the defect is weighted and summarized according to the detection characteristics of the two technologies to obtain the final high-precision defect information.
The array eddy current sensor is rotated around the screw thread at a constant speed by adopting an automatic detection device, the sensor performs constant-speed circular motion to scan the screw thread in the circumferential direction, the detection part is comprehensive, the detection precision is high, and the missing detection is not easy. The automatic detection device has the advantages that the phenomena of large detection error and low efficiency caused by manual operation are avoided, the detection precision and the working efficiency can be effectively improved, and meanwhile, the automatic detection device is simple and rapid to operate, and the working efficiency is greatly improved.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (6)
1. A method for improving thread defect detection precision is characterized by comprising the following steps:
s1, combining the eddy current sensor and the giant magnetoresistance sensor in an arc structure to form an array eddy current sensor;
s2, mounting the array eddy current sensor on the detection sensing head part of the floating probe to form a sensing structure;
s3, acquiring defect characteristics of the detected thread area;
s4, acquiring defect information in the thread structure;
s5 performs weighted fusion of the defect feature and the defect information.
2. A method of improving thread defect detection accuracy as defined in claim 1, wherein: in step S1, the excitation coil in the difference measurement sensor is used as an excitation source for eddy current sensing and also as a magnetic field excitation source in giant magnetoresistance detection, and the difference measurement sensor and the giant magnetoresistance sensor are combined in an arc-shaped spatial structure to ensure better curved surface adhesion in the curved surface structure of the thread.
3. A method of improving thread defect detection accuracy as defined in claim 1, wherein: in the step S2, the detecting sensor part of the floating probe has angle adjustability, the external motor drives the whole sensing part to make circular motion around the screw structure, the array eddy current sensor advances along the screw structure under the action of the screw structure, and the probe mounting beam can adjust the mounting angle of the array eddy current sensor for detecting some screw structures with angle inclination.
4. A method of improving thread defect detection accuracy as defined in claim 1, wherein: in the step S3, a sinusoidal excitation signal with a certain frequency is loaded into the excitation coil, the frequency of the excitation signal needs to be calculated according to the structural parameters of the thread and the electromagnetic properties of the material, the differential signal receiving coil firstly performs adaptive signal filtering and amplification after signal output, feature extraction is performed on the obtained defect signal on the basis of establishing a mathematical model of the thread eddy current, a signal at a peak in a defect detection signal curve is extracted to perform discrete fourier transform, and the defect feature of the thread region detected by the eddy current sensor is obtained according to the relationship among the obtained signal feature, model analysis and fitting by fitting the defect size and using the voltage peak, the peak time, the zero-crossing frequency and the peak frequency relational expression.
5. A method of improving thread defect detection accuracy as defined in claim 1, wherein: in step S4, the giant magnetoresistance sensor detects the magnetic field generated by the excitation of the eddy current sensor, performs signal filtering, amplification and other processing on the sensing signal based on a mathematical detection model and a magnetic coupling noise model, and extracts data features according to the detection mathematical model and the actual calibration model to obtain defect information in the thread structure.
6. A method of improving thread defect detection accuracy as defined in claim 1, wherein: in step S5, when both the defect information are known, the defect signals are weighted and fused according to the different detection characteristics of the eddy current sensor and the giant magnetoresistance sensor with respect to the thread defect, so as to improve the sensitivity of defect detection and accurately provide information such as the size, position, and type of the defect.
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| CN116399942A (en) * | 2023-06-07 | 2023-07-07 | 西南石油大学 | Online detection method for full circumferential defects of differential vortex coiled tubing |
| CN116735700A (en) * | 2023-08-08 | 2023-09-12 | 国机传感科技有限公司 | Pipeline defect stress composite detection sensor and detection method |
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