Multi-frequency array eddy current testing equipment and method thereof

Abstract

The invention discloses multi-frequency array eddy current detection equipment and a method thereof, belongs to the technical field of eddy current detection, and aims to find out an outlier in an extracted phase difference according to fluctuation intensity and fluctuation range of the phase difference and calibrate the outlier so as to efficiently prevent the defect of inaccurate phase difference detection caused by external noise fluctuation interference. According to the relation between the eddy current detection numerical value and the phase difference of the transverse pipeline, the similarity between the eddy current detection condition of the numerical cluster corresponding to each previous numerical value point and the eddy current detection condition of the numerical cluster where the outlier is located, and the action amplitude of each numerical value point in the numerical cluster on the outlier, finding out a previous numerical value similar to the outlier; and the outliers are calibrated, so that the precision of the phase difference can be improved, and the calculation of the wall thickness of the pipeline according to the phase difference is improved until the precision of detecting the local micro crack defect of the pipeline is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of eddy current detection, and in particular relates to a multi-frequency array eddy current detection device and a method thereof. Background Art

[0002] Multi-frequency array eddy current testing technology uses a multi-channel testing method, which can detect multiple defects at the same time, greatly improving the detection efficiency. At the same time, its detection results are highly accurate and can detect smaller defects.

[0003] In practical applications, the current multi-frequency array eddy current detection technology is often achieved using the existing technical solution published by the University of Electronic Science and Technology of China in June 2016, whose author is Lu Xiangyu and whose supervisor is Shi Yibing, and whose master's thesis is titled "Multi-frequency eddy current casing damage detector far-field unit and its data processing design". It mainly consists of 12 groups of sensors connected to a single-chip microcomputer distributed along the circumference of the inner wall of the transverse pipeline. The 12 groups of sensors are used to pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer is used to extract the phase difference based on the digitized far-field weak induction signals, and then calculate the pipeline wall thickness based on the phase difference, until the detection of local tiny crack defects in the pipeline is achieved.

[0004] However, when the digitized far-field weak induction signal is transmitted to the microcontroller, it is often affected by external noise interference. Just as the intensity of external magnetic field interference increases, some of the extracted phase differences are inaccurate, which is not conducive to calculating the pipeline wall thickness based on the phase difference, and finally achieving the accuracy of detecting local tiny crack defects in the pipeline. Summary of the invention

[0005] In order to solve the defects in the prior art, the present invention proposes a multi-frequency array eddy current detection device and method, which detects outliers in the extracted phase difference based on the fluctuation intensity and fluctuation range of the phase difference, and calibrates the outliers, which can effectively prevent the defect of inaccurate phase difference detection due to interference from external noise changes; based on the relationship between the eddy current detection value and the phase difference of the lateral pipeline, based on the similarity between the eddy current detection status of the value cluster corresponding to each past value point and the eddy current detection status of the value cluster where the outlier is located and the amplitude of the effect of each value point in the value cluster on the outlier, detects past values ​​close to the outlier, and calibrates the outlier, which can improve the accuracy of the phase difference, thereby improving the calculation of the pipeline wall thickness based on the phase difference, until the accuracy of the detection of local micro-crack defects in the pipeline is achieved.

[0006] The present invention uses the following technical solutions.

[0007] A multi-frequency array eddy current detection method, comprising:

[0008] 12 groups of sensors pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer extracts the phase difference according to the digitized far-field weak induction signals and performs processing, and then calculates the pipe wall thickness according to the processed phase difference;

[0009] The method of performing processing by extracting the phase difference based on the digitized far-field weak induction signal by the single chip microcomputer includes:

[0010] Step 1, obtain the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point;

[0011] Step 2, obtain the near-zone value of the phase difference to form a near-zone value cluster of the phase difference, analyze the value change of the near-zone value cluster of the random phase difference, obtain the outlier amplitude of the phase difference, select the outlier amplitude of the value to be analyzed, and obtain the outlier value;

[0012] Step 3, according to the difference of eddy current detection values ​​between the outlier and the previous values ​​in a predefined time period, obtain the initial similarity between the outlier and the previous values; according to the time distance of the phase difference in the outlier and the near-zone value cluster, obtain the time point effect factor of the random phase difference in the near-zone value cluster of the outlier; concentrate the initial similarity between the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final similarity between the outlier and the previous values, and select all the past values ​​close to the outlier; combine the final similarity between the outlier and all the past values ​​close to each other, the value of the past values ​​close to each other and the outlier amplitude of the past values ​​close to each other to obtain the actual value of the outlier;

[0013] Step 4, replace all outliers of the lateral pipeline with actual values, and obtain the phase difference of the lateral pipeline after replacement. The phase difference after replacement is the phase difference after treatment.

[0014] Furthermore, in Step 1, the phase difference of multiple detection points of the transverse pipeline is obtained, and the phase difference in the latest pre-defined period U1 is defined as the value to be analyzed, and the value that must be analyzed is defined as the past value;

[0015] The eddy current detection value in the predefined time period U2 before obtaining the arbitrary phase difference, the eddy current detection value includes the digitized far-field weak induction signal corresponding to the phase difference and the pipe wall thickness of the transverse pipe.

[0016] Further, in Step 2, the random phase difference and the B phase differences adjacent to the previous phase difference and the B phase differences adjacent to the next phase difference are initially formed into a near-zone value cluster of the phase difference, where B is a predefined index 1;

[0017] Then, the full range within the near-zone value cluster of the random phase difference is defined as the value variation range of the near-zone value cluster of the phase difference;

[0018] Then, the value fluctuation amplitude of the near-zone value cluster of the random phase difference is obtained according to the change of the adjacent phase difference in the near-zone value cluster of the phase difference;

[0019] The outlier amplitude of the phase difference is obtained by combining the numerical variation range of the nearby numerical clusters of the random phase difference and the numerical fluctuation amplitude of the nearby numerical clusters of the phase difference.

[0020] Furthermore, in Step 2, the method for obtaining the numerical fluctuation amplitude of the near-zone numerical cluster of the arbitrary phase difference specifically includes:

[0021] Operate the following equation:

[0022]

[0023] In the equation, x j represents the amplitude of the numerical fluctuation of the near-zone value cluster of the jth phase difference, p represents the number of phase differences contained in the near-zone value cluster of the phase difference, d j，k represents the value of the kth phase difference in the cluster of values ​​near the jth phase difference, d j，k+1 represents the value of the kth phase difference in the cluster of values ​​in the near zone of the jth phase difference;

[0024] Then, according to the value variation range of the nearby value cluster of the phase difference and the value fluctuation amplitude of the nearby value cluster of the phase difference, the outlier amplitude of the random phase difference is obtained.

[0025] Furthermore, in Step 2, the method for obtaining the outlier amplitude of the random phase difference specifically includes:

[0026] Operate the following equation:

[0027] c j =BZ(x j *s j )

[0028] In the equation, c j represents the outlier amplitude of the jth phase difference, x j represents the amplitude of the numerical fluctuation of the near-zone numerical cluster of the jth phase difference, s j The value variation range of the near-zone value cluster representing the phase difference, BZ(x j *s j ) represents the use of the Z-score method to evaluate x j *s j Implement standardized disposal;

[0029] Then, the values ​​to be analyzed whose outlier amplitudes are higher than the pre-defined index 2 among all the values ​​to be analyzed are selected and defined as outliers.

[0030] Furthermore, Step 3 specifically includes:

[0031] Step 3-1, according to the difference of eddy current detection values ​​between the outlier value and the past value in a predefined period, obtain the initial similarity between the outlier value and the past value;

[0032] Step 3-2, according to the time distance of the phase difference within the outlier and the nearby value cluster, obtain the time point effect factor of the random phase difference in the nearby value cluster of the outlier;

[0033] Step 3-3, concentrate the initial similarity between the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final similarity between the outlier and the previous values, and select all the previous values ​​close to the outlier;

[0034] Step 3-4, combine the final similarity between the outlier value and all similar past values, the value of the similar past values ​​and the outlier amplitude of the similar past values ​​to obtain the actual value of the outlier value.

[0035] Further, in Step 3-1, initially, the eddy current detection value of the random phase difference is obtained through Step 1, and the corresponding eddy current detection value at each time point in the predefined period before the random phase difference is obtained, and the eddy current detection value includes the corresponding digitized far-field weak induction signal of the detection position where the phase difference in the predefined period before the phase difference is located and the pipe wall thickness of the transverse pipe;

[0036] Next, a ∪ operation is performed on the random outliers and random past values, and on the digitized far-field weak sensing signals of the outliers and the past values, to obtain all digitized far-field weak sensing signals of the random outliers and the random past values;

[0037] Finally, the initial similarity between the outlier value and the past value is obtained based on the difference in eddy current detection values ​​in a pre-defined time period between the outlier value and the past value.

[0038] Furthermore, in Step 3-1, the method for obtaining the initial similarity between the random outlier value and the random past value specifically includes:

[0039] Operate the following equation:

[0040]

[0041] In the equation, T j,v represents the initial similarity between the jth outlier value and the vth previous value, P j,v Represents the far-field weak sensing signal of the jth outlier and the vth past value after all digitization, y j,k represents the pipe wall thickness of the kth transverse pipe within the eddy current detection value of the jth previous value, y v,krepresents the pipe wall thickness of the kth transverse pipe in the eddy current detection value of the vth outlier, C is the predefined indicator three, Represents the use of Z-score method to Perform standardized disposal.

[0042] Furthermore, in Step 3-2, the method for obtaining the time point effect factor of the random phase difference in the near-zone value cluster of the outlier specifically includes:

[0043] Operate the following equation:

[0044]

[0045] In the equation, g j,n The time point effect factor of the nth phase difference in the cluster of values ​​near the jth outlier, Δu j,n represents the time interval between the jth outlier and the nth phase difference in the nearby cluster, C is the predefined indicator three, Represents the use of Z-score method to Perform standardized disposal.

[0046] Furthermore, in Step 3-3, the method for obtaining the final similarity between the random outlier value and the random past value specifically includes:

[0047] Operate the following equation:

[0048]

[0049] In the equation, γ j,v represents the final similarity between the jth outlier and the vth previous value; p represents the number of phase differences contained in the cluster of values ​​in the nearby area of ​​the phase difference; T j,v,n represents the initial similarity between the jth outlier and the nth corresponding phase difference in the cluster of values ​​near the vth previous value; g j,v,n Represents the time point effect factor of the nth corresponding phase difference in the cluster of values ​​near the jth outlier and the vth previous value;

[0050] For random outliers, select the past values ​​whose final similarity to the outlier value is higher than the pre-defined index four among all past values ​​and define them as the similar past values ​​of the outlier value.

[0051] Furthermore, in Step 3-4, the method for obtaining the influencing factor of the random similar past values ​​of the random outlier value specifically includes:

[0052] Operate the following equation:

[0053]

[0054] In the equation, νj,v represents the contribution factor of the vth similar past value of the jth outlier, c j,v represents the outlier amplitude of the vth similar past value of the jth outlier value, and C is the pre-defined indicator three.

[0055] Furthermore, in Step 3-4, the method for obtaining the actual value of the random outlier specifically includes:

[0056]

[0057] In the equation, D j represents the actual value of the jth outlier, X j The number of non-outlier similar past values ​​representing the jth outlier, ν j，x represents the effect of the xth similar past value on the jth outlier value, γ j,x represents the final similarity between the jth outlier value and the xth similar past value, d j,x Represents the value of the xth similar past value of the jth outlier, and C is the pre-defined indicator three.

[0058] A multi-frequency array eddy current testing device, comprising:

[0059] 12 groups of sensors connected to the single chip microcomputer distributed along the circumference of the inner wall of the transverse pipe;

[0060] 12 sets of sensors are used to pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer is used to extract the phase difference according to the digitized far-field weak induction signals and perform processing, and then calculate the pipe wall thickness according to the processed phase difference;

[0061] The modules running on the microcontroller include:

[0062] A detection module, which is used to obtain the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point;

[0063] An outlier module is used to obtain the near-zone value of the phase difference to form a near-zone value cluster of the phase difference, analyze the value change of the near-zone value cluster of the random phase difference, obtain the outlier amplitude of the phase difference, select the outlier amplitude of the value to be analyzed, and obtain the outlier value;

[0064] A proximity module is used to obtain the initial proximity of the outlier and the previous values ​​according to the difference in eddy current detection values ​​between the outlier and the previous values ​​in a predefined time period; obtain the time point effect factor of the random phase difference in the near-zone value cluster of the outlier according to the time distance of the phase difference in the outlier and the near-zone value cluster; concentrate the initial proximity of the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final proximity of the outlier and the previous values, and select all the past values ​​close to the outlier; combine the final proximity of the outlier and all the past values ​​close to each other, the value of the past values ​​close to each other and the outlier amplitude of the past values ​​close to each other to obtain the actual value of the outlier;

[0065] The replacement module is used to replace all outliers of the lateral pipeline with actual values, and obtain the phase difference of the lateral pipeline after replacement. The phase difference after replacement is the phase difference after treatment.

[0066] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0067] According to the fluctuation intensity and fluctuation range of the phase difference, the outliers in the extracted phase difference are detected, and the outliers are calibrated, which can effectively avoid the defect of inaccurate phase difference detection due to the interference of external noise fluctuations; according to the relationship between the eddy current detection value and the phase difference of the lateral pipeline, according to the similarity of the eddy current detection status of the value cluster corresponding to each past value point and the eddy current detection status of the value cluster where the outlier is located and the amplitude of the influence of each value point in the value cluster on the outlier, the past values ​​close to the outlier are detected, and the outliers are calibrated, which can improve the accuracy of the phase difference, and also improve the calculation of the pipeline wall thickness based on the phase difference, until the accuracy of the detection of local micro-crack defects in the pipeline is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 is a flow chart of the multi-frequency array eddy current detection method described in the present invention;

[0069] Figure 2 It is a partial structural diagram of the multi-frequency array eddy current detection equipment described in the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the present invention clearer, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely express the technical solution of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. According to the spirit of the present invention, other embodiments obtained by technicians in this field without making creative work are all within the protection scope of the present invention.

[0071] like Figure 1As shown, a multi-frequency array eddy current detection method described in the present invention includes:

[0072] 12 groups of sensors pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer extracts the phase difference according to the digitized far-field weak induction signals and performs processing. Then, the thickness of the pipeline wall is calculated according to the processed phase difference, until the detection of local micro crack defects in the pipeline is achieved.

[0073] The method of performing processing by extracting the phase difference based on the digitized far-field weak induction signal by the single chip microcomputer includes:

[0074] Step 1, obtain the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point;

[0075] The multi-frequency array eddy current detection of the transverse pipe includes 12 groups of sensors moving on the inner wall of the transverse pipe during the test cycle, so that the 12 groups of sensors perform detection at different detection locations, that is, to pick up far-field weak induction signals at different detection locations and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer then extracts the corresponding phase differences of different detection locations according to the digitized far-field weak induction signals at different detection locations for processing, and then calculates the pipe wall thickness of the corresponding transverse pipe at different detection locations according to the phase differences of different detection locations after processing.

[0076] In a preferred but non-limiting embodiment of the present invention, in Step 1, the relationship between the overall phase difference and the eddy current detection value of the transverse pipeline is obtained according to the phase difference of different detection positions. Initially, the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point are obtained. The method is as follows:

[0077] Obtain the phase difference of multiple detection points of the transverse pipeline, define the phase difference in the latest pre-defined period U1 as the value to be analyzed, and define the value that must be analyzed as the previous value;

[0078] The eddy current detection value in the predefined time period U2 before obtaining the random phase difference includes the digitized far-field weak induction signal and the pipe wall thickness of the transverse pipe corresponding to the phase difference. The phase difference, the digitized far-field weak induction signal and the pipe wall thickness of the transverse pipe are arranged in the order of their formation.

[0079] In a preferred but non-limiting embodiment of the present invention, in Step 1, the time periods U1 and U2 are pre-defined as five seconds and one second respectively.

[0080] Therefore, the phase difference of multiple detection points on the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point are obtained through the above method.

[0081] Step 2, obtain the near-zone value of the phase difference to form a near-zone value cluster of the phase difference, analyze the value change of the near-zone value cluster of the random phase difference, obtain the outlier amplitude of the phase difference, select the outlier amplitude of the value to be analyzed, and obtain the outlier value;

[0082] However, due to the external noise fluctuations, the digitized far-field weak induction signal transmitted to the single-chip microcomputer will cause the extracted phase difference to fluctuate suddenly in a large range, resulting in a large difference in the extracted phase difference of a horizontal pipeline. Therefore, the outliers in the extracted phase difference are identified based on the effect of external noise fluctuations on the phase difference.

[0083] During the detection of multiple detection points in the transverse pipeline, due to the interference of external noise, the phase difference cannot reflect the actual phase difference of the transverse pipeline. Therefore, it is necessary to identify the outliers affected by the external noise changes in the extracted phase difference.

[0084] While the single-chip microcomputer extracts the phase difference based on the digitized far-field weak induction signal, the phase difference will increase when the value of the digitized far-field weak induction signal increases. After the increase stage, the carbon emissions will gradually spread to other places, and the detected phase difference will also gradually decrease. Therefore, the normal phase difference fluctuation is very stable. When there is external noise interference, the intensity of the digitized far-field weak induction signal transmitted to the single-chip microcomputer will be weakened. Therefore, after the increase in the detected phase difference, the extracted phase difference will suddenly decrease due to external noise interference. Therefore, it is possible to analyze whether the phase difference is outlier (phase difference interfered by noise) through the change in the value of the phase difference over a period of time.

[0085] In a preferred but non-limiting embodiment of the present invention, in Step 2, the random phase difference and the B phase differences adjacent to the previous phase difference and the B phase differences adjacent to the next phase difference are initially formed into a near-range value cluster of the phase difference, where B is a predefined index 1;

[0086] In a preferred but non-limiting embodiment of the present invention, in Step 2, the pre-defined index B is five.

[0087] Then, the full range within the near-zone value cluster of the random phase difference is defined as the value variation range of the near-zone value cluster of the phase difference;

[0088] The numerical variation range of a numerical cluster is the range of the numerical values ​​in the numerical cluster, that is, the difference between the highest and lowest values ​​in the numerical cluster.

[0089] Then, the value fluctuation amplitude of the near-zone value cluster of the random phase difference is obtained according to the change of the adjacent phase difference in the near-zone value cluster of the phase difference;

[0090] The numerical fluctuation amplitude of a numerical cluster represents the change of all adjacent numerical values. The lower the change of all adjacent numerical values, the less significant the overall fluctuation of the numerical cluster is, and the lower the numerical fluctuation amplitude of the numerical cluster is.

[0091] The outlier amplitude of the phase difference is obtained by combining the numerical variation range of the nearby numerical clusters of the random phase difference and the numerical fluctuation amplitude of the nearby numerical clusters of the phase difference.

[0092] In a preferred but non-limiting embodiment of the present invention, in Step 2, the method for obtaining the numerical fluctuation amplitude of the near-zone numerical cluster of arbitrary phase difference specifically includes:

[0093] Operate the following equation:

[0094]

[0095] In the equation, x j represents the amplitude of the numerical fluctuation of the near-zone value cluster of the jth phase difference, p represents the number of phase differences contained in the near-zone value cluster of the phase difference, d j，k represents the value of the kth phase difference in the cluster of values ​​near the jth phase difference, d j，k+1 represents the value of the kth phase difference in the cluster of values ​​in the near zone of the jth phase difference;

[0096] Then, according to the value variation range of the nearby value cluster of the phase difference and the value fluctuation amplitude of the nearby value cluster of the phase difference, the outlier amplitude of the random phase difference is obtained.

[0097] During a period of time, the higher the continuous phase difference variation, the higher the numerical fluctuation amplitude of the phase difference, and the higher the phase difference outlier amplitude; the higher the full range of the synchronized phase difference, the higher the numerical variation range of the phase difference, and the higher the phase difference outlier amplitude.

[0098] In a preferred but non-limiting embodiment of the present invention, in Step 2, the method for obtaining the outlier amplitude of the random phase difference specifically includes:

[0099] Operate the following equation:

[0100] c j =BZ(x j *s j )

[0101] In the equation, c j represents the outlier amplitude of the jth phase difference, x j represents the amplitude of the numerical fluctuation of the near-zone numerical cluster of the jth phase difference, s j The value variation range of the near-zone value cluster representing the phase difference, BZ(x j *s j) represents the use of the Z-score method to evaluate x j *s j Implement standardized disposal;

[0102] Then, the values ​​to be analyzed whose outlier amplitudes are higher than the pre-defined index 2 among all the values ​​to be analyzed are selected and defined as outliers.

[0103] In a preferred but non-limiting embodiment of the present invention, in Step 2, the pre-defined index 2 is one-half.

[0104] So the outliers are obtained through the above method.

[0105] Step 3, according to the difference of eddy current detection values ​​between the outlier and the previous values ​​in a predefined time period, obtain the initial similarity between the outlier and the previous values; according to the time distance of the phase difference in the outlier and the near-zone value cluster, obtain the time point effect factor of the random phase difference in the near-zone value cluster of the outlier; concentrate the initial similarity between the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final similarity between the outlier and the previous values, and select all the past values ​​close to the outlier; combine the final similarity between the outlier and all the past values ​​close to each other, the value of the past values ​​close to each other and the outlier amplitude of the past values ​​close to each other to obtain the actual value of the outlier;

[0106] Under the same eddy current detection conditions, the phase difference should be similar. Therefore, based on the similarity of the eddy current detection conditions, the past values ​​close to the outlier are found, and based on the past values, the actual phase difference at the corresponding time point of the outlier is calculated.

[0107] In a preferred but non-limiting embodiment of the present invention, Step 3 specifically includes:

[0108] Step 3-1, according to the difference of eddy current detection values ​​between the outlier value and the past value in a predefined period, obtain the initial similarity between the outlier value and the past value;

[0109] The phase difference at the detection point is related to the corresponding digitized far-field weak induction signal and the wall thickness of the lateral pipe. Therefore, it is necessary to find out the similar past values ​​that can reflect the regular phase difference of the outlier based on the similarity between the past values ​​and the traffic conditions of the outlier.

[0110] In a preferred but non-limiting embodiment of the present invention, in Step 3-1, initially, an eddy current detection value of an arbitrary phase difference is obtained through Step 1, and the corresponding eddy current detection value at each time point in a predefined period before the arbitrary phase difference is obtained, and the eddy current detection value includes the corresponding digitized far-field weak induction signal of the detection position where the phase difference is located in the predefined period before the phase difference and the pipe wall thickness of the transverse pipe;

[0111] Next, a ∪ operation is performed on the random outliers and random past values, and on the digitized far-field weak sensing signals of the outliers and the past values, to obtain all digitized far-field weak sensing signals of the random outliers and the random past values;

[0112] When facing the same detection location, for random outliers and random past values, the closer the eddy current detection values ​​in the pre-defined time period are, the greater the similarity between the outliers and past values.

[0113] The similarity between random outliers and random past values ​​in the predefined time period is characterized by the similarity between the digitized far-field weak induction signals and the similarity between the wall thickness of the lateral pipeline. Therefore, for random outliers and random past values, the lower the difference in the wall thickness of the lateral pipeline, the greater the initial similarity between the outliers and the past values.

[0114] Finally, the initial similarity between the outlier value and the past value is obtained based on the difference in eddy current detection values ​​in a pre-defined time period between the outlier value and the past value.

[0115] In a preferred but non-limiting embodiment of the present invention, in Step 3-1, the method for obtaining the initial similarity between the random outlier value and the random past value specifically includes:

[0116] Operate the following equation:

[0117]

[0118] In the equation, T j,v represents the initial similarity between the jth outlier value and the vth previous value, P j,v Represents the far-field weak sensing signal of the jth outlier and the vth past value after all digitization, y j,k represents the pipe wall thickness of the kth transverse pipe within the eddy current detection value of the jth previous value, y v,k represents the pipe wall thickness of the kth transverse pipe in the eddy current detection value of the vth outlier, C is the predefined indicator three, Represents the use of Z-score method to Perform standardized disposal.

[0119] and The closer the pipe wall thicknesses of each transverse pipe in the near-zone value cluster representing the jth outlier and the vth past value are, the closer the eddy current detection values ​​of the jth outlier and the vth past value are, and therefore the greater the initial similarity between the jth outlier and the vth past value.

[0120] The value of the predefined index three may be one, which is used to make the divisor in the equation non-zero.

[0121] Step 3-2, according to the time distance of the phase difference within the outlier and the nearby value cluster, obtain the time point effect factor of the random phase difference in the nearby value cluster of the outlier;

[0122] However, because the phase difference at each time point (the time point is the time point when the corresponding phase difference is formed) in the near-zone value cluster of the outlier has different effects on the outlier, the closer the time distance (that is, the duration between the time points) of the phase difference, the higher the amplitude of the effect of the corresponding eddy current detection value on the outlier, and thus the time point effect factor of the phase difference is higher.

[0123] In a preferred but non-limiting embodiment of the present invention, in Step 3-2, the method for obtaining the time point effect factor of the random phase difference in the near-zone value cluster of the outlier specifically includes:

[0124] Operate the following equation:

[0125]

[0126] In the equation, g j,n The time point effect factor of the nth phase difference in the cluster of values ​​near the jth outlier, Δu j,n represents the time interval between the jth outlier and the nth phase difference in the nearby cluster, C is the predefined indicator three, Represents the use of Z-score method to Perform standardized disposal.

[0127] Step 3-3, concentrate the initial similarity between the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final similarity between the outlier and the previous values, and select all the previous values ​​close to the outlier;

[0128] When facing random outliers and random past values, the final similarity is reflected in: the initial similarity represented by the similarity of the eddy current detection values. In the near-zone value cluster of random outliers and random past values, the higher the initial similarity of each corresponding phase difference, the higher the final similarity. It is also reflected in: the time point effect factor of each corresponding phase difference obtained by time distance. When the initial similarity of each corresponding phase difference is large, the time distance with the outlier time point is not large, so the initial similarity of the corresponding phase difference at the time point has a higher representation amplitude of the final similarity.

[0129] In a preferred but non-limiting embodiment of the present invention, in Step 3-3, the method for obtaining the final similarity between the random outlier value and the random past value specifically includes:

[0130] Operate the following equation:

[0131]

[0132] In the equation, γ j,v represents the final similarity between the jth outlier and the vth previous value; p represents the number of phase differences contained in the cluster of values ​​in the nearby area of ​​the phase difference; T j,v,n represents the initial similarity between the jth outlier and the nth corresponding phase difference in the cluster of values ​​near the vth previous value; g j,v,n Represents the time point effect factor of the nth corresponding phase difference in the cluster of values ​​near the jth outlier and the vth previous value.

[0133] and It means that in the cluster of values ​​near the j-th outlier and the v-th previous value, the time point effect factor of the n-th corresponding phase difference is taken as the importance, and the initial similarity of all corresponding phase differences in the cluster of values ​​near the j-th outlier and the v-th previous value is averaged after the attached importance is executed to form the final similarity between the j-th outlier and the v-th previous value.

[0134] For random outliers, select the past values ​​whose final similarity to the outlier value is higher than the pre-defined index four among all past values ​​and define them as the similar past values ​​of the outlier value.

[0135] Step 3-4, combine the final similarity between the outlier value and all similar past values, the value of the similar past values ​​and the outlier amplitude of the similar past values ​​to obtain the actual value of the outlier value.

[0136] If the past values ​​are subject to considerable external noise interference, the past values ​​will also be inaccurate. Therefore, according to Step 2, the outlier amplitudes of the adjacent past values ​​of the random outlier are calculated. The higher the outlier amplitudes of the adjacent past values, the lower the amplitude of the influence of the adjacent past values ​​on the actual value of the outlier during the calculation period, that is, the lower the influence factor.

[0137] In a preferred but non-limiting embodiment of the present invention, in Step 3-4, the method for obtaining the influencing factor of the random similar past value of the random outlier value specifically includes:

[0138] Operate the following equation:

[0139]

[0140] In the equation, ν j,v represents the contribution factor of the vth similar past value of the jth outlier, c j,v represents the outlier amplitude of the vth similar past value of the jth outlier value, and C is the pre-defined indicator three.

[0141] Among all the similar past values ​​of random outliers, the outliers should be removed first, because the similar past values ​​of the outliers will interfere with the actual value of the outliers.

[0142] According to Step 2, select the non-outlier similar past values ​​among all similar past values.

[0143] The actual value of the outlier is obtained by using the value of the similar past value. Therefore, for any similar past value, the higher the similar amplitude of the outlier, it means that the similar past value can reflect the actual value of the outlier to a greater extent, and the formation ratio of the actual value of the outlier is also higher; in addition, the similar past values ​​should also reflect the phase difference, that is, the lower the outlier amplitude of the similar past values, the greater the effect of the similar past values ​​on the actual value of the outlier, and the formation ratio of the actual value of the outlier is also higher. Therefore, the actual phase difference of the outlier can be calculated based on the values ​​of all non-outlier similar past values, the similar amplitude of the outlier and the influence factor of the similar past values.

[0144] In a preferred but non-limiting embodiment of the present invention, in Step 3-4, the method for obtaining the actual value of the random outlier specifically includes:

[0145]

[0146] In the equation, D j represents the actual value of the jth outlier, X j The number of non-outlier similar past values ​​representing the jth outlier, ν j，x represents the effect of the xth similar past value on the jth outlier value, γ j,x represents the final similarity between the jth outlier value and the xth similar past value, d j,x Represents the value of the xth similar past value of the jth outlier, and C is the pre-defined indicator three.

[0147] and All the similar past values ​​representing the jth outlier are treated as importance by the action factor and the similar amplitude, and the values ​​of all the non-outlier similar past values ​​are averaged after the attached importance, forming the actual value of the jth outlier. The horizontal pipe is the casing.

[0148] Therefore, the actual value of any outlier is obtained through the above method.

[0149] Step 4, replace all outliers of the lateral pipeline with actual values, and obtain the phase difference of the lateral pipeline after replacement. The phase difference after replacement is the phase difference after treatment.

[0150] Through the above method, a multi-frequency array eddy current detection method is achieved.

[0151] like Figure 2 As shown, a multi-frequency array eddy current detection device shown in the present invention includes:

[0152] 12 groups of sensors connected to the single chip microcomputer distributed along the circumference of the inner wall of the transverse pipe;

[0153] 12 sets of sensors are used to pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer is used to extract the phase difference according to the digitized far-field weak induction signals and perform processing. Then, the thickness of the pipeline wall is calculated according to the processed phase difference, until the detection of local micro crack defects in the pipeline is achieved.

[0154] The modules running on the microcontroller include:

[0155] A detection module, which is used to obtain the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point;

[0156] An outlier module is used to obtain the near-zone value of the phase difference to form a near-zone value cluster of the phase difference, analyze the value change of the near-zone value cluster of the random phase difference, obtain the outlier amplitude of the phase difference, select the outlier amplitude of the value to be analyzed, and obtain the outlier value;

[0157] A proximity module is used to obtain the initial proximity of the outlier and the previous values ​​according to the difference in eddy current detection values ​​between the outlier and the previous values ​​in a predefined time period; obtain the time point effect factor of the random phase difference in the near-zone value cluster of the outlier according to the time distance of the phase difference in the outlier and the near-zone value cluster; concentrate the initial proximity of the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final proximity of the outlier and the previous values, and select all the past values ​​close to the outlier; combine the final proximity of the outlier and all the past values ​​close to each other, the value of the past values ​​close to each other and the outlier amplitude of the past values ​​close to each other to obtain the actual value of the outlier;

[0158] The replacement module is used to replace all outliers of the lateral pipeline with actual values, and obtain the phase difference of the lateral pipeline after replacement. The phase difference after replacement is the phase difference after treatment.

[0159] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0160] According to the fluctuation intensity and fluctuation range of the phase difference, the outliers in the extracted phase difference are detected, and the outliers are calibrated, which can effectively avoid the defect of inaccurate phase difference detection due to the interference of external noise fluctuations; according to the relationship between the eddy current detection value and the phase difference of the lateral pipeline, according to the similarity of the eddy current detection status of the value cluster corresponding to each past value point and the eddy current detection status of the value cluster where the outlier is located and the amplitude of the influence of each value point in the value cluster on the outlier, the past values ​​close to the outlier are detected, and the outliers are calibrated, which can improve the accuracy of the phase difference, and also improve the calculation of the pipeline wall thickness based on the phase difference, until the accuracy of the detection of local micro-crack defects in the pipeline is achieved.

[0161] Finally, it should be explained that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not deviate from the spirit and scope of the present invention should be covered within the protection space of the claims of the present invention.

Claims

1. A multi-frequency array eddy current detection method, characterized in that: include: 12 groups of sensors pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer extracts the phase difference according to the digitized far-field weak induction signals and performs processing, and then calculates the pipe wall thickness according to the processed phase difference; The method of performing processing by extracting the phase difference based on the digitized far-field weak induction signal by the single chip microcomputer includes: Step 1, obtain the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point; Step 2, obtain the near-zone value of the phase difference to form a near-zone value cluster of the phase difference, analyze the value change of the near-zone value cluster of the random phase difference, obtain the outlier amplitude of the phase difference, select the outlier amplitude of the value to be analyzed, and obtain the outlier value; Step 3, according to the difference of eddy current detection values ​​between the outlier and the previous values ​​in a predefined time period, obtain the initial similarity between the outlier and the previous values; according to the time distance of the phase difference in the outlier and the near-zone value cluster, obtain the time point effect factor of the random phase difference in the near-zone value cluster of the outlier; concentrate the initial similarity between the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final similarity between the outlier and the previous values, and select all the past values ​​close to the outlier; combine the final similarity between the outlier and all the past values ​​close to each other, the value of the past values ​​close to each other and the outlier amplitude of the past values ​​close to each other to obtain the actual value of the outlier; Step 4, replace all outliers of the lateral pipeline with actual values, and obtain the phase difference of the lateral pipeline after replacement. The phase difference after replacement is the phase difference after treatment.

2. The multi-frequency array eddy current detection method according to claim 1, characterized in that: In Step 1, the phase difference of multiple detection points of the horizontal pipeline is obtained, and the phase difference in the latest pre-defined period U1 is defined as the value to be analyzed, and the value that must be analyzed is defined as the previous value; The eddy current detection value in the predefined time period U2 before obtaining the arbitrary phase difference, the eddy current detection value includes the digitized far-field weak induction signal corresponding to the phase difference and the pipe wall thickness of the transverse pipe.

3. The multi-frequency array eddy current detection method according to claim 2, characterized in that: In Step 2, the random phase difference and the B phase differences adjacent to the previous phase difference and the B phase differences adjacent to the next phase difference are initially combined to form a near-range value cluster of the phase difference, where B is a predefined index 1; Then, the full range within the near-zone value cluster of the random phase difference is defined as the value variation range of the near-zone value cluster of the phase difference; Then, the value fluctuation amplitude of the near-zone value cluster of the random phase difference is obtained according to the change of the adjacent phase difference in the near-zone value cluster of the phase difference; The outlier amplitude of the phase difference is obtained by combining the numerical variation range of the nearby numerical clusters of the random phase difference and the numerical fluctuation amplitude of the nearby numerical clusters of the phase difference.

4. The multi-frequency array eddy current detection method according to claim 3, characterized in that: In Step 2, the method for obtaining the numerical fluctuation amplitude of the near-zone numerical cluster of arbitrary phase difference specifically includes: Operate the following equation: In the equation, x j represents the amplitude of the numerical fluctuation of the near-zone value cluster of the jth phase difference, p represents the number of phase differences contained in the near-zone value cluster of the phase difference, d j，k represents the value of the kth phase difference in the cluster of values ​​near the jth phase difference, d j，k+1 represents the value of the kth phase difference in the cluster of values ​​in the near zone of the jth phase difference; Then, according to the value variation range of the nearby value cluster of the phase difference and the value fluctuation amplitude of the nearby value cluster of the phase difference, the outlier amplitude of the random phase difference is obtained.

5. The multi-frequency array eddy current detection method according to claim 4, characterized in that: In Step 2, the method for obtaining the outlier amplitude of the random phase difference specifically includes: Operate the following equation: c j =BZ(x j *s j ) In the equation, c j represents the outlier amplitude of the jth phase difference, x j represents the amplitude of the numerical fluctuation of the near-zone numerical cluster of the jth phase difference, s j The value variation range of the near-zone value cluster representing the phase difference, BZ(x j *s j ) represents the use of the Z-score method to evaluate x j *s j Implement standardized disposal; Then, the values ​​to be analyzed whose outlier amplitudes are higher than the pre-defined index 2 among all the values ​​to be analyzed are selected and defined as outliers.

6. The multi-frequency array eddy current detection method according to claim 5, characterized in that: Step 3 specifically includes: Step 3-1, according to the difference of eddy current detection values ​​between the outlier value and the past value in a predefined period, obtain the initial similarity between the outlier value and the past value; Step 3-2, according to the time distance of the phase difference within the outlier and the nearby value cluster, obtain the time point effect factor of the random phase difference in the nearby value cluster of the outlier; Step 3-3, concentrate the initial similarity between the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final similarity between the outlier and the previous values, and select all the previous values ​​close to the outlier; Step 3-4, combine the final similarity between the outlier value and all similar past values, the value of the similar past values ​​and the outlier amplitude of the similar past values ​​to obtain the actual value of the outlier value.

7. The multi-frequency array eddy current detection method according to claim 6, characterized in that: In Step 3-1, initially, the eddy current detection value of the random phase difference is obtained through Step 1, and the corresponding eddy current detection value at each time point in the predefined period before the random phase difference is obtained, and the eddy current detection value includes the corresponding digitized far-field weak induction signal of the detection position where the phase difference is located in the predefined period before the phase difference and the pipe wall thickness of the transverse pipe; Next, a ∪ operation is performed on the random outliers and random past values, and on the digitized far-field weak sensing signals of the outliers and the past values, to obtain all digitized far-field weak sensing signals of the random outliers and the random past values; Finally, the initial similarity between the outlier value and the past value is obtained based on the difference in eddy current detection values ​​in a pre-defined time period between the outlier value and the past value.

8. The multi-frequency array eddy current detection method according to claim 7, characterized in that: In Step 3-1, the method for obtaining the initial similarity between the random outlier value and the random past value specifically includes: Operate the following equation: In the equation, T j,v represents the initial similarity between the jth outlier value and the vth previous value, P j,v Represents the far-field weak sensing signal of the jth outlier and the vth past value after all digitization, y j,k represents the pipe wall thickness of the kth transverse pipe within the eddy current detection value of the jth previous value, y v,k represents the pipe wall thickness of the kth transverse pipe in the eddy current detection value of the vth outlier, C is the predefined indicator three, Represents the use of Z-score method to Implement standardized disposal; In Step 3-2, the method for obtaining the time point effect factor of the random phase difference in the near-zone value cluster of the outlier specifically includes: Operate the following equation: In the equation, g j,n The time point effect factor of the nth phase difference in the cluster of values ​​near the jth outlier, Δu j,n represents the time interval between the jth outlier and the nth phase difference in the nearby cluster, C is the predefined indicator three, Represents the use of Z-score method to Perform standardized disposal.

9. The multi-frequency array eddy current detection method according to claim 8, characterized in that: In Step 3-3, the method for obtaining the final similarity between the random outlier value and the random past value specifically includes: Operate the following equation: In the equation, γ j,v represents the final similarity between the jth outlier and the vth previous value; p represents the number of phase differences contained in the cluster of values ​​in the nearby area of ​​the phase difference; T j,v,n represents the initial similarity between the jth outlier and the nth corresponding phase difference in the cluster of values ​​near the vth previous value; g j,v,n Represents the time point effect factor of the nth corresponding phase difference in the cluster of values ​​near the jth outlier and the vth previous value; For random outliers, select the past values ​​whose last similarity with the outlier value is higher than the pre-defined index 4 among all past values ​​and define them as the outlier's similar past values; In Step 3-4, the method for obtaining the influencing factor of the random close past values ​​of the random outlier value specifically includes: Operate the following equation: In the equation, ν j,v represents the contribution factor of the vth similar past value of the jth outlier, c j,v represents the outlier amplitude of the vth similar past value of the jth outlier, and C is the pre-defined indicator three; In Step 3-4, the method for obtaining the actual value of the random outlier includes: In the equation, D j represents the actual value of the jth outlier, X j The number of non-outlier similar past values ​​representing the jth outlier, ν j，x represents the effect of the xth similar past value on the jth outlier value, γ j,x represents the final similarity between the jth outlier value and the xth similar past value, d j,x Represents the value of the xth similar past value of the jth outlier, and C is the pre-defined indicator three.

10. A multi-frequency array eddy current testing device, characterized in that: include: 12 groups of sensors connected to the single chip microcomputer distributed along the circumference of the inner wall of the transverse pipe; 12 sets of sensors are used to pick up far-field weak induction signals and transmit them to the single-chip microcomputer after digitization. The single-chip microcomputer is used to extract the phase difference according to the digitized far-field weak induction signals and perform processing, and then calculate the pipe wall thickness according to the processed phase difference; The modules running on the microcontroller include: A detection module, which is used to obtain the phase difference of multiple detection positions of the transverse pipeline and the eddy current detection value corresponding to the phase difference at the same time point; An outlier module is used to obtain the near-zone values ​​of the phase difference to form a near-zone value cluster of the phase difference, analyze the value change of the near-zone value cluster of the random phase difference, obtain the outlier amplitude of the phase difference, select the outlier amplitude of the value to be analyzed, and obtain the outlier value; A proximity module is used to obtain the initial proximity of the outlier and the previous values ​​according to the difference in eddy current detection values ​​between the outlier and the previous values ​​in a predefined time period; obtain the time point effect factor of the random phase difference in the near-zone value cluster of the outlier according to the time distance of the phase difference in the outlier and the near-zone value cluster; concentrate the initial proximity of the outlier and the previous values, the time point effect factor of the phase difference in the near-zone value cluster of the outlier, obtain the final proximity of the outlier and the previous values, and select all the past values ​​close to the outlier; combine the final proximity of the outlier and all the past values ​​close to each other, the value of the past values ​​close to each other and the outlier amplitude of the past values ​​close to each other to obtain the actual value of the outlier; The replacement module is used to replace all outliers of the lateral pipeline with actual values, and obtain the phase difference of the lateral pipeline after replacement. The phase difference after replacement is the phase difference after treatment.

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