Ferromagnetic component pulsed eddy current detection imaging method and system

Abstract

The invention belongs to the technical field of pulsed eddy current nondestructive testing, and particularly discloses a ferromagnetic component pulsed eddy current detection imaging method and system, and the detection imaging method comprises the following steps: collecting a pulsed eddy current signal of a ferromagnetic component, carrying out logarithmic processing on the pulsed eddy current signal, and then carrying out secondary filtering processing; carrying out dimension reduction processing on the signal after the secondary filtering processing; calculating an amplitude standard deviation of the signal after dimension reduction processing of 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; and calculating a pixel value based on a processing result obtained by Min-Max standardization, and carrying out homogenization processing on the pixel value to obtain a pulsed eddy current image. According to the invention, rapid imaging can be realized aiming at the pulsed eddy current detection signal of the ferromagnetic component, so that defects can be identified and preliminarily positioned.

Description

Technical Field

[0001] The present application belongs to the field of pulsed eddy current nondestructive testing technology, and more specifically, 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, it has rich frequency components and a large signal penetration depth, 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, which can penetrate thicker covering layers and realize wall thinning detection of metal materials under large lift-off.

[0003] The current pulsed eddy current detection is generally used for fixed-point thickness measurement or simple scanning detection. In terms of defect characterization, a single characteristic quantity is generally used to characterize the defect. However, this method is often unable to quantitatively characterize the defect size, and is unable to characterize the spatial information of the defect. At present, the pulsed eddy current imaging detection method is mainly aimed at non-ferromagnetic components. For ferromagnetic components, since there are no characteristic quantities such as lift-off intersections and zero crossings, their imaging detection is more difficult. Therefore, there is an urgent need for a pulsed eddy current signal detection imaging method for ferromagnetic components to help solve the above problems. Summary of the invention

[0004] In view of the defects of the prior art, the purpose of this application is to provide a pulse eddy current detection imaging method and system for ferromagnetic components, aiming to solve the problem of how to achieve rapid imaging of pulse 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 of 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 the dimensionality reduction processing in each time dimension, and selects the effective 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 average processing on the pixel values ​​to obtain a pulsed eddy current image.

[0011] Compared with the prior art, the above technical solution conceived by the present application includes pulse eddy current signal filtering, data dimension 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 and help defect identification and preliminary positioning.

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

[0013] S101 performs median filtering on the pulse 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 that is less than the minimum value of the pulsed eddy current signal.

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

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

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

[0019]

[0020] Where V' i V is the value of the ith induced voltage in the effective imaging interval after Min-Max normalization. i is the value of the ith induced voltage in the effective imaging interval, V max is the maximum value within 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 detection imaging method for ferromagnetic components as described in any one of the above items is also disclosed, and the system includes:

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

[0028] A first processing module, used for performing logarithmic processing on the pulsed eddy current signal and then performing 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 the dimensionality reduction processing in each time dimension, and select the effective imaging interval based on the amplitude standard deviation;

[0031] A third processing module, used for performing 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 average 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 prior art:

[0034] 1. The detection method of the present application realizes eddy current pulse imaging by coordinating pulse eddy current signal filtering, data dimension reduction, selection of effective interval based on amplitude standard deviation, calculation of pixel value and pixel averaging. Multiple links cooperate to realize rapid imaging of pulse eddy current detection signals of ferromagnetic components, which helps defect identification and preliminary positioning.

[0035] 2. The detection method provided in the present application utilizes secondary filtering to further reduce noise and improve the signal-to-noise ratio. Since the amount of raw data of the pulse eddy current is large, the dimensionality reduction processing method can effectively improve the imaging efficiency, improve the 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 the noise, the present application can select the interval with the largest amplitude difference between different signals according to the amplitude standard deviation, so that the imaging effect is more intuitive, thereby improving the accuracy and intuitiveness of the imaging; the present application also further improves the imaging quality through standardization and equalization processing.

[0036] 3. The PAA algorithm used in this application can divide the data into equal lengths, without the need to calculate complex covariance matrices or eigenvectors, and is relatively efficient and simple; the PAA algorithm can use a low-dimensional data sequence to approximate the basic form of a high-dimensional data sequence, and can reduce pulse eddy current imaging data to any amount of data, 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 It is a flow chart of the pulsed eddy current detection imaging method for ferromagnetic components provided in the embodiments of the present application;

[0039] Figure 2 is a schematic diagram of a pulsed eddy current scanning experiment provided in an embodiment of the present application;

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

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

[0042] Figure 5 is a 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 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 solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

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

[0047] In addition, references throughout this specification to "one embodiment"; "one embodiment", "an example" or similar language indicate that a particular feature, structure, or characteristic described in conjunction 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 detection imaging method for the ferromagnetic components made of the Q345 material. Figure 2 As shown in the figure, it is a schematic diagram of the pulse eddy current scanning experiment in this embodiment. The ferromagnetic component is 1800mm long, 900mm wide and 8mm thick. The material is Q345 low-alloy high-strength structural steel. The spherical hole defect is located at the center of the tested piece and is 10mm×3.4mm in size. The scanning pulse eddy current probe is 60mm away from the surface of the test piece. The probe adopts a differential structure inside. During the test, a pulse signal is used for excitation. The encoder completes signal acquisition every 10mm.

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

[0050] S1 collects pulsed eddy current signals from ferromagnetic components, performs logarithmic processing on the pulsed eddy current signals, and then performs secondary filtering processing.

[0051] After collecting pulsed eddy current and other spatial scanning signals, 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 original signal in the Cartesian rectangular coordinate system. The logarithmic coordinate system can "magnify" small-scale data and "compress" large-scale data, such as Figure 3As shown in Figure 1, converting the pulsed eddy current detection signal to the single logarithmic domain can amplify the amplitude change of the attenuation segment signal 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 processed for data dimension reduction based on the PAA (Piecwise Aggregate Approximation) algorithm. In this embodiment, a single pulse eddy current signal contains 30720 data points. The huge amount of data will lead to low signal processing efficiency, and multiple pulse eddy current data need to be processed during the imaging process. Therefore, it is necessary to first perform data dimension reduction on the signal to improve the 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 = {Q1, Q2, ..., Q n} can be replaced by another time series P = {P1, P2, ..., P m}, where n>m. Let m=n / k, where k is the segment step length, 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 the data size to any amount. 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, 5120, which is divisible by 30720, is selected as the target data size in this embodiment. 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 different signal amplitudes in each time dimension, and select the effective imaging interval based on the standard deviation result. Since the difference between defective and non-defective 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 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] According to the characteristics of pulsed eddy current signals, the analysis is generally performed in the signal attenuation area. Since part of the detection signal in this embodiment falls into the negative half area, the signal will first increase and then gradually attenuate after crossing this interval. Therefore, there are two attenuation areas in the detection signal of this embodiment. Considering that the first attenuation area is less affected by noise, this embodiment chooses to intercept the effective imaging interval in the first attenuation area. Assume that the time when the amplitude standard deviation in the first attenuation area begins to increase is T1, and the time when it decreases to the minimum value is T2, then 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 interval is subjected to Min-Max normalization processing. The processing formula is as follows:

[0063]

[0064] Among them, V ’ i V is the value of the ith induced voltage in the effective imaging interval after Min-Max normalization. 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 restrictions 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 the effect of smooth color transition and pulsed eddy current imaging. The image obtained 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 150mm away from the starting scanning position.

[0071] According to another aspect of the present application, a system for implementing the ferromagnetic component pulse eddy current detection imaging method in any of the above embodiments is also disclosed, the system comprising:

[0072] A signal acquisition module, used for acquiring 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 standardization processing on the data within the effective imaging interval;

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

[0078] It should be understood that the above-mentioned system is used to execute the methods in the above-mentioned embodiments. The implementation principles and technical effects of the corresponding program modules in the system are similar to those described in the above-mentioned methods. 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 method in the above embodiment, the embodiment of the present application provides a network device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor may call the logic instructions in the memory to execute the method in the above embodiment.

[0080] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units 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 a computer device (which can be a personal computer, a server, or a network device, etc.) to perform 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 understandable that the processor in the embodiment of the present application can be a central processing unit (CPU), or 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 can 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, and the software modules 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 a 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 may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may 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 disk (SSD)), etc.

[0086] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0087] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A pulsed eddy current detection imaging method for ferromagnetic components, characterized in that: The method comprises the following steps: S1 collects pulsed eddy current signals of 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 the dimensionality reduction processing in each time dimension, and selects the effective imaging interval based on the amplitude standard deviation; 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 average processing on the pixel values ​​to obtain a pulsed eddy current image.

2. The pulsed eddy current detection imaging method according to claim 1, characterized in that: In step S1, the steps of secondary filtering processing include: S101 performs median filtering on the pulse 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, characterized in that: 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, characterized in that: 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 processing can be divided by the pulsed eddy current signal.

6. The pulsed eddy current detection imaging method according to claim 1, characterized in that: The calculation formula for Min-Max normalization is: Among them, V ’ i V is the value of the ith induced voltage in the effective imaging interval after Min-Max normalization. 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.

7. The pulsed eddy current detection imaging method according to claim 1, characterized in that: In step S5, the formula for calculating the pixel value is: RGB value =V′ i ×cloudScale 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.

8. The pulsed eddy current detection imaging method according to claim 1, characterized in that: 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. The pulsed eddy current detection imaging method according to claim 1, characterized in that: 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.

10. A system for implementing the ferromagnetic component pulse eddy current detection imaging method according to any one of claims 1 to 9, characterized in that: include: A signal acquisition module, used for acquiring pulsed eddy current signals of ferromagnetic components; A first processing module, used for performing logarithmic processing on the pulsed eddy current signal and then performing 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 the dimensionality reduction processing in each time dimension, and select the effective imaging interval based on the amplitude standard deviation; A third processing module, used for performing 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 average processing on the pixel values ​​to obtain a pulsed eddy current image.

Images