Ferromagnetic component pulsed eddy current testing imaging method and system

Abstract

The application belongs to the technical field of pulse eddy current nondestructive testing, and specifically discloses a ferromagnetic component pulse eddy current detection imaging method and system. The detection imaging method comprises the following steps: collecting a pulse eddy current signal of a ferromagnetic component, performing logarithmic processing on the pulse eddy current signal, and then performing secondary filtering processing; performing dimension reduction processing on the signal after the secondary filtering processing; calculating the amplitude standard deviation of the signal after the dimension reduction processing in each time dimension, and selecting an effective imaging interval based on the amplitude standard deviation; performing Min-Max standardization processing on the data in the effective imaging interval; calculating a pixel value based on the processing result obtained by the Min-Max standardization, and performing homogenization processing on the pixel value, so as to obtain a pulse eddy current image. The application can realize fast imaging on the pulse eddy current detection signal of the ferromagnetic component, so as to identify and preliminarily position defects.

Description

Technical Field

[0001] The present application belongs to the field of pulsed eddy current non-destructive testing technology, and more specifically, relates to a pulsed eddy current testing imaging method and system for ferromagnetic components. Background Art

[0002] As a branch of eddy current testing, pulsed eddy current has the following characteristics compared to ordinary eddy current testing: on the one hand, its frequency components are rich and the signal penetration depth is large, which can realize deep defect detection of metal materials under small lift-off; on the other hand, the magnetic field intensity excited by the excitation coil is large and can penetrate thicker covering layers, realizing wall thinning detection of metal materials under large lift-off.

[0003] Current pulsed eddy current testing is generally used for fixed-point thickness measurement or simple scanning inspection. For defect characterization, a single characteristic quantity is generally used. However, this method is often unable to quantitatively characterize the defect size and cannot represent the spatial information of the defect. Current pulsed eddy current imaging testing methods are mainly used for non-ferromagnetic components. For ferromagnetic components, imaging detection is more difficult due to the lack of characteristic quantities such as lift-off intersections and zero-crossing points. Therefore, a pulsed eddy current signal detection imaging method for ferromagnetic components is urgently needed to help solve the above problems. Summary of the Invention

[0004] In response to the defects of the existing technology, the purpose of this application is to provide a pulsed eddy current detection imaging method and system for ferromagnetic components, aiming to solve the problem of how to achieve rapid imaging of the pulsed eddy current detection signals of ferromagnetic components, so as to identify and preliminarily locate the defects of ferromagnetic components based on images.

[0005] To achieve the above-mentioned purpose, the present application provides a method for pulsed eddy current detection and imaging of ferromagnetic components, comprising the following steps:

[0006] S1 collects pulsed eddy current signals from ferromagnetic components, performs logarithmic processing on the pulsed eddy current signals, and then performs secondary filtering processing;

[0007] S2 performs dimensionality reduction processing on the signal after secondary filtering;

[0008] S3 calculates the amplitude standard deviation of the signal after dimensionality reduction processing in each time dimension, and selects a valid imaging interval based on the amplitude standard deviation;

[0009] S4 performs Min-Max normalization processing on the data within the effective imaging interval;

[0010] S5 calculates pixel values ​​based on the processing results obtained by Min-Max normalization, and performs averaging processing on the pixel values ​​to obtain a pulsed eddy current image.

[0011] Compared with the existing technology, the above technical solution conceived by this application includes pulse eddy current signal filtering, data dimensionality reduction, selection of valid intervals based on amplitude standard deviation, calculation of pixel values ​​and the final imaging link, which can achieve rapid imaging of pulse eddy current detection signals of ferromagnetic components, helping defect identification and preliminary positioning.

[0012] Furthermore, in step S1, the secondary filtering process includes:

[0013] S101 performs median filtering on the pulsed eddy current signal after logarithmic processing by using median filtering;

[0014] S102 performs secondary filtering on the signal after median filtering using the SG filtering method.

[0015] Furthermore, when the signal amplitude is less than 0, the amplitude is assigned to a positive number less than the minimum value of the pulsed eddy current signal.

[0016] Furthermore, the PAA algorithm is used to perform dimensionality reduction on the signal after secondary filtering.

[0017] Furthermore, the data volume of the signal after the dimensionality reduction process can be divided by the pulsed eddy current signal.

[0018] Furthermore, the calculation formula for Min-Max normalization is:

[0019]

[0020] where V' i is the value of the ith induced voltage in the effective imaging interval after Min-Max normalization, V i is the value of the ith induced voltage in the effective imaging interval, V max is the maximum value in the effective imaging range, V min is the minimum value within the effective imaging range.

[0021] Furthermore, in step S5, the formula for calculating the pixel value is:

[0022] RGB value =V′ i =cloudScale

[0023] Among them RGB value Represents the pixel value, cloudScale is the range of color scale, V' i is the value of the ith induced voltage in the effective imaging interval after Min-Max normalization.

[0024] Furthermore, in step S5, the step of averaging the pixel values ​​includes: performing interpolation processing between adjacent pixels, hiding the borders between image grids, making the colors transition smoothly, and completing pulsed eddy current imaging.

[0025] Furthermore, in step S3, the method for selecting the effective imaging interval based on the amplitude standard deviation is: obtaining the time T1 when the amplitude standard deviation starts to increase and the time T2 when the amplitude standard deviation decreases to the minimum value, and taking the interval [T1, T2] as the effective imaging interval.

[0026] According to another aspect of the present application, a system for implementing the pulsed eddy current imaging method for ferromagnetic components as described in any of the above is also disclosed, the system comprising:

[0027] A signal acquisition module, used to collect pulsed eddy current signals of ferromagnetic components;

[0028] A first processing module is used to perform logarithmic processing on the pulsed eddy current signal and then perform secondary filtering processing;

[0029] The second processing module is used to perform dimensionality reduction processing on the signal after the secondary filtering processing;

[0030] An effective imaging interval selection module is used to obtain the amplitude standard deviation of the signal after dimensionality reduction processing in each time dimension, and select the effective imaging interval based on the amplitude standard deviation;

[0031] A third processing module is used to perform Min-Max normalization processing on the data within the effective imaging interval;

[0032] The imaging module is used to calculate pixel values ​​based on the processing results obtained by Min-Max normalization and perform averaging processing on the pixel values ​​to obtain a pulsed eddy current image.

[0033] In general, the above technical solutions conceived by this application have the following technical advantages compared with the existing technology:

[0034] 1. The detection method of this application coordinates pulse eddy current signal filtering, data dimensionality reduction, selection of valid intervals based on amplitude standard deviation, calculation of pixel values, and pixel averaging to achieve eddy current pulse imaging. Multiple links work together to achieve rapid imaging of pulse eddy current detection signals of ferromagnetic components, helping to identify and initially locate defects.

[0035] 2. The detection method provided in this application uses secondary filtering to further reduce noise and improve the signal-to-noise ratio. Since the amount of original pulse eddy current data is large, the dimensionality reduction processing method can effectively improve imaging efficiency, improve processing efficiency, and reduce the consumption of computing resources; since the relevant information of the test piece is mainly manifested in the early stage of the signal, and the late signal is almost completely submerged by noise, this application can select the interval with the largest amplitude difference between different signals based on the amplitude standard deviation, making the imaging effect more intuitive, thereby improving the accuracy and intuitiveness of the imaging; this application also further improves the imaging quality through standardization and equalization processing.

[0036] 3. This application uses the PAA algorithm to divide the data into equal lengths, without the need to calculate complex covariance matrices or eigenvectors, which is relatively efficient and simple; the PAA algorithm can use low-dimensional data sequences to approximate the basic form of high-dimensional data sequences, and can reduce pulsed eddy current imaging data to any data volume, saving storage space and processing time; in addition, the PAA algorithm can retain the overall size and trend information of the data and reduce the impact of noise.

[0037] 4. In this application, Min-Max normalization is used to perform linear transformation on the original data, mapping the values ​​to between |0, 1|, removing the unit restriction of the data and improving the imaging effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of the pulsed eddy current imaging method for ferromagnetic components provided in an embodiment of the present application;

[0039] Figure 2 Schematic diagram of the pulsed eddy current scanning experiment provided in the embodiments of the present application;

[0040] Figure 3 is the pulsed eddy current detection signal after logarithmic processing provided in the embodiment of the present application;

[0041] Figure 4 is the pulsed eddy current detection signal after median filtering and SG filtering provided in the embodiment of the present application;

[0042] Figure 5 is the filtered signal after dimensionality reduction processing by the PAA algorithm provided in the embodiment of the present application;

[0043] Figure 6 is the standard deviation of the different signal amplitudes in each time dimension provided in the embodiments of the present application;

[0044] Figure 7 This is the pulsed eddy current imaging result provided in the examples of this application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0046] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise specifically defined.

[0047] Additionally, references throughout this specification to "one embodiment," "one embodiment," "an example," or similar language indicate that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, appearances of the phrase "in one embodiment," "in one embodiment," and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.

[0048] This embodiment provides a pulsed eddy current imaging method for detecting ferromagnetic components made of the above-mentioned Q345 material. Figure 2 Figure 2 shows a schematic diagram of the pulsed eddy current scanning test in this embodiment. The ferromagnetic component is 1800 mm long, 900 mm wide, and 8 mm thick, made of Q345 low-alloy, high-strength structural steel. A spherical hole defect measuring 10 mm x 3.4 mm is located at the center of the test piece. The scanning pulsed eddy current probe is 60 mm from the test piece surface. The probe utilizes a differential structure internally, using pulse signals for excitation. An encoder acquires signals every 10 mm.

[0049] like Figure 1 The following steps are shown:

[0050] S1 collects the pulsed eddy current signal of the ferromagnetic component, performs logarithmic processing on the pulsed eddy current signal, and then performs secondary filtering processing.

[0051] After collecting spatial scanning signals such as pulsed eddy current, the signals are processed logarithmically. Since the eddy current diffusion characteristic time of ferromagnetic components is relatively long, the time domain signal segment reflecting its characteristics is very weak. Therefore, it is difficult to obtain effective information from the unprocessed pulsed eddy current raw signal in the Cartesian coordinate system. However, logarithmic coordinates can "amplify" small-scale data and "compress" large-scale data, such as Figure 3As shown in Figure 2, converting the pulsed eddy current detection signal into the single logarithmic domain can amplify the signal amplitude change in the attenuation section that needs to be observed. Therefore, the signal needs to be logarithmically processed first. For the case where the signal amplitude is less than 0, it is all assigned to a very small positive number that is less than the minimum value in the pulsed eddy current signal, such as e -7 .

[0052] The signal is then filtered based on the median filter and SG (Savitzky Golay) filter method. First, the signal is filtered with a 501-order median filter. Since there are still many noise "burrs" in the signal after the median filter, the effect of eliminating the noise is limited. On this basis, an SG filter with an order of 3 and a window length of 501 is selected to perform secondary filtering on the signal to further improve the signal-to-noise ratio. The signal after filtering is as follows Figure 4 shown.

[0053] S2 performs dimensionality reduction processing on the signal after secondary filtering.

[0054] After filtering is completed, the signal is subjected to data dimensionality reduction processing based on the PAA (Piecwise Aggregate Approximation) algorithm. In this embodiment, a single pulsed eddy current signal contains 30,720 data points. The huge amount of data will lead to low signal processing efficiency, and multiple pulsed eddy current data need to be processed during the imaging process. Therefore, it is necessary to first perform data dimensionality reduction on the signal to improve imaging efficiency. The PAA (Piecwise Aggregate Approximation) algorithm is a segmented aggregation approximation algorithm that uses a low-dimensional data sequence to approximate the basic form of a high-dimensional data sequence. The algorithm first divides the original sequence into m subsequences of equal length, and then replaces each subsequence with the mean of the subsequence. The specific implementation process is as follows:

[0055] Assume that the length of the pulsed eddy current detection signal time series Q is n = {Q1, Q2, ..., Q n} can be replaced by another time series P = {P1, P2, ..., P m} represents n>m. Let m=n / k, where k is the segment step size, m is rounded down, and if it cannot be divided evenly, the undivided part is merged into the previous segment, P i Satisfy the following formula:

[0056]

[0057] The PAA algorithm can be used to reduce it to any data size. However, if the data size is too small, some important feature information will be lost, resulting in the reconstructed data sequence being unable to accurately reflect the main morphological features of the original sequence. Considering that the PAA algorithm divides the data into equal lengths, in this embodiment, 5120, which is divisible by 30720, is selected as the target data size. The signal after PAA processing is as follows: Figure 5 shown.

[0058] S3 calculates the amplitude standard deviation of the signal after dimensionality reduction processing in each time dimension, and selects the effective imaging interval based on the amplitude standard deviation.

[0059] Calculate the standard deviation of the different signal amplitudes in each time dimension, and select the effective imaging interval based on the standard deviation results. Since the difference between the presence and absence of defect signals is only manifested in the early stage of the signal, and the difference is small in the later stage of the signal, it is possible to consider selecting the effective interval first and then imaging. This embodiment selects the effective imaging interval based on the standard deviation of the different signal amplitudes in each time dimension. The calculation results of the amplitude standard deviation in different time dimensions are as follows: Figure 6 shown.

[0060] Due to the characteristics of pulsed eddy current signals, analysis is generally performed in the signal attenuation region. Since the detection signal in this embodiment partially falls into the negative half region, the signal initially increases and then gradually attenuates after crossing this region. Therefore, the detection signal in this embodiment has two attenuation regions. Considering that the first attenuation region is less affected by noise, this embodiment selects the effective imaging interval within the first attenuation region. Let T1 be the time when the amplitude standard deviation begins to increase in the first attenuation region, and T2 be the time when it decreases to its minimum value. The effective imaging interval is [T1, T2].

[0061] S4 performs Min-Max normalization processing on the data of the effective imaging interval.

[0062] In order to remove the unit limitation of the data and ensure the reliability of the results, the signal within the valid range is subjected to Min-Max normalization processing. The processing formula is as follows:

[0063]

[0064] Among them, V ’ i is the value of the ith induced voltage in the effective imaging interval after Min-Max normalization, V i is the value of the ith induced voltage in the effective imaging interval, V max is the maximum value in the effective imaging range, V min is the minimum value within the effective imaging range.

[0065] Min-Max normalization linearly transforms the original data, maps the values ​​to [0, 1], and removes the unit restriction of the data, which can improve the imaging effect.

[0066] S5 calculates pixel values ​​based on the processing results obtained by Min-Max normalization, and performs average processing on the pixel values ​​to obtain a pulsed eddy current image.

[0067] The formula for calculating pixel value is as follows:

[0068] RGB value =V i ×cloudScale (3)

[0069] Among them, RGB value Represents the pixel value, and cloudScale is the range of color scale.

[0070] Then the pixel values ​​are averaged. The specific steps include: bilinear interpolation between adjacent pixels to make the overall color of the image more uniform, hiding the borders between the image grids, eliminating obvious dividing lines and color blocks, so that the entire image is displayed only in smooth colors, thereby achieving a smooth color transition effect and pulsed eddy current imaging. The obtained image is as follows Figure 7 As shown in the figure, it can be identified that the defect is located in area A, and the defect appears about 150 mm away from the starting scanning position.

[0071] According to another aspect of the present application, a system for implementing the pulsed eddy current imaging method for ferromagnetic components as described in any of the above embodiments is also disclosed. The system includes:

[0072] A signal acquisition module, used to collect pulsed eddy current signals of ferromagnetic components;

[0073] The first processing module is used to perform logarithmic processing on the pulsed eddy current signal and then perform secondary filtering processing;

[0074] The second processing module is used to perform dimensionality reduction processing on the signal after the secondary filtering processing;

[0075] An effective imaging interval selection module is used to obtain the amplitude standard deviation of the signal after dimensionality reduction processing in each time dimension, and select the effective imaging interval based on the amplitude standard deviation;

[0076] The third processing module is used to perform Min-Max normalization processing on the data within the effective imaging interval;

[0077] The imaging module is used to calculate pixel values ​​based on the processing results obtained by Min-Max normalization and perform average processing on the pixel values ​​to obtain a pulsed eddy current image.

[0078] It should be understood that the above-mentioned system is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the system are similar to those described in the above-mentioned method. The working process of the system can refer to the corresponding process in the above-mentioned method and will not be repeated here.

[0079] Based on the methods in the above embodiments, embodiments of the present application provide a network device that may include: a processor, a communications interface, a memory, and a communication bus, wherein the processor, the communications interface, and the memory communicate with each other via the communication bus. The processor may invoke logic instructions in the memory to execute the methods in the above embodiments.

[0080] In addition, the logical instructions in the above-mentioned memory can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0081] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0082] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0083] It is understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0084] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0085] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0086] It will be understood that the various numerical numbers involved in the embodiments of the present application are merely distinctions for the convenience of description and are not intended to limit the scope of the embodiments of the present application.

[0087] Those skilled in the art can understand that the above description is only the preferred embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A pulsed eddy current imaging method for ferromagnetic components, characterized in that: The method comprises the following steps: S1 collects pulsed eddy current signals from ferromagnetic components, performs logarithmic processing on the pulsed eddy current signals, and then performs secondary filtering processing; S2 performs dimensionality reduction processing on the signal after secondary filtering; S3 calculates the amplitude standard deviation of the signal after dimensionality reduction processing in each time dimension, and obtains the time T1 when the amplitude standard deviation starts to increase and the time T2 when the amplitude standard deviation decreases to the minimum value, and takes the interval [T1, T2] as the effective imaging interval; S4 performs Min-Max normalization processing on the data within the effective imaging interval; S5 calculates pixel values ​​based on the processing results obtained by Min-Max normalization, and performs averaging processing on the pixel values ​​to obtain a pulsed eddy current image.

2. The pulsed eddy current detection imaging method according to claim 1, wherein: In step S1, the steps of secondary filtering processing include: S101 performs median filtering on the pulsed eddy current signal after logarithmic processing by using median filtering; S102 performs secondary filtering on the signal after median filtering using the SG filtering method.

3. The pulsed eddy current detection imaging method according to claim 2, wherein: In step S101 , when the signal amplitude is less than 0, the amplitude is assigned a positive number that is less than the minimum value of the pulsed eddy current signal.

4. The pulsed eddy current detection imaging method according to claim 1, wherein: In step S2, the PAA algorithm is used to perform dimensionality reduction processing on the filtered signal after the secondary filtering processing.

5. The pulsed eddy current detection imaging method according to claim 4, characterized in that: The data volume of the signal after the dimension reduction process is divisible by the pulsed eddy current signal.

6. The pulsed eddy current detection imaging method according to claim 1, wherein: The calculation formula for Min-Max normalization is: in, V ’ i The first i The value of the induced voltage after Min-Max normalization, V i The first i The value of the induced voltage, V max is the maximum value within the effective imaging range, V min is the minimum value within the effective imaging range.

7. The pulsed eddy current imaging method according to claim 1, wherein: In step S5, the formula for calculating the pixel value is: in, represents the pixel value, is the range of color level changes, V ’ i The first i The value of the induced voltage after Min-Max normalization.

8. The pulsed eddy current imaging method according to claim 1, wherein: In step S5, the step of averaging the pixel values ​​includes: performing interpolation processing between adjacent pixels, hiding the borders between image grids, making the colors transition smoothly, and completing pulsed eddy current imaging.

9. A system for implementing the pulsed eddy current imaging method for ferromagnetic components according to any one of claims 1 to 8, characterized in that: include: A signal acquisition module, used to collect pulsed eddy current signals of ferromagnetic components; A first processing module is used to perform logarithmic processing on the pulsed eddy current signal and then perform secondary filtering processing; The second processing module is used to perform dimensionality reduction processing on the signal after the secondary filtering processing; An effective imaging interval selection module is used to obtain the amplitude standard deviation of the signal after dimensionality reduction processing in each time dimension, and obtain the time T1 when the amplitude standard deviation begins to increase and the time T2 when the amplitude standard deviation decreases to the minimum value, and take the interval [T1, T2] as the effective imaging interval; A third processing module is used to perform Min-Max normalization processing on the data within the effective imaging interval; The imaging module is used to calculate pixel values ​​based on the processing results obtained by Min-Max normalization and perform averaging processing on the pixel values ​​to obtain a pulsed eddy current image.

Images