CN110596233B - A real-time processing method for wire rope magnetic flux leakage imaging under continuous sampling - Google Patents

Abstract

The invention discloses a steel wire rope magnetic leakage imaging real-time processing method under continuous sampling, wherein magnetic leakage signals of a steel wire rope are acquired in sections during magnetic leakage signal acquisition, magnetic leakage imaging processing is carried out on each section of magnetic leakage signals by using a method combining primary screening and fine diagnosis, then a current magnetic leakage image is spliced with an existing spliced magnetic leakage image, wherein overlapped data sections are divided into four conditions to be processed, and the spliced magnetic leakage image which is to be obtained after splicing is completed each time is output and displayed in real time until all signals are processed. The invention can effectively improve the processing speed of magnetic flux leakage imaging, can avoid the phenomenon of misjudgment or misjudgment of the damage of the steel wire rope caused by signal segmentation, and realizes the real-time processing of the magnetic flux leakage imaging of the steel wire rope.

Description

A real-time processing method for wire rope magnetic flux leakage imaging under continuous sampling

technical field

The invention belongs to the technical field of steel wire rope damage diagnosis, and more specifically relates to a real-time processing method for magnetic flux leakage imaging of steel wire ropes under continuous sampling.

Background technique

Steel wire rope has the characteristics of high strength, high reliability, and high stability, and is widely used in various industrial scenarios to provide functions such as lifting, traction, and load-carrying. As the wire rope is usually used as a key component of large machinery, its working status will affect the operation status and safety performance of the entire equipment. Therefore, the fault diagnosis of wire rope is of great significance to ensure the stability of equipment and production safety. There are many methods for non-destructive testing of steel wire ropes. A common method is to collect the magnetic flux leakage signal on the surface of the steel wire rope and use the magnetic flux leakage image to diagnose the damage of the steel wire rope. Figure 1 is a schematic diagram of the principle of wire rope damage diagnosis based on magnetic flux leakage images. As shown in Figure 1, the magnetic flux leakage image of the defect on the surface of the steel wire rope is different from that of the normal steel wire rope surface, so the damage diagnosis of the steel wire rope can be carried out based on the magnetic flux leakage image. However, most of these methods are continuous batch data processing methods, which are difficult to be used for online monitoring.

Contents of the invention

The purpose of the present invention is to overcome the deficiencies in the prior art, provide a real-time processing method for magnetic flux leakage imaging of steel wire ropes under continuous sampling, collect the magnetic flux leakage signals of steel wire ropes in sections, and use the method of "primary screening" and "fine diagnosis" to analyze Segmented signals are processed by magnetic flux leakage imaging, and the overall magnetic flux leakage image is stitched and fused according to the processed imaging results, which can effectively improve the processing speed of magnetic flux leakage imaging, and can avoid misjudgment or missed judgment of wire rope damage caused by signal segmentation .

In order to achieve the purpose of the above invention, the real-time processing method for magnetic flux leakage imaging of steel wire rope under continuous sampling of the present invention comprises the following steps:

S1: Set up a magnetic sensor array, including M magnetic sensors, the M magnetic sensors are arranged at equal intervals along the circumference of the wire rope, and an annular armature is set outside the M magnetic sensors;

S2: Make the wire rope move relative to the axial direction of the magnetic sensor. The data acquisition system periodically samples the current signals of M magnetic sensors. The length of the sampling signal of each magnetic sensor in each sampling is L, and the sampling period is The setting needs to make two adjacent acquisition signals overlap, record the overlapping length as S, 0<S<L/2, record the sampling signal of the i-th steel wire rope as X _i , i=1,2,..., the sampling signal X _i is a data matrix with a size of M×L, wherein the data of the nth sampling point of the mth magnetic sensor is _Xi [m, n]; after each sampling, enter step S3;

S3: Perform magnetic leakage imaging on each segment of the sampled signal X _i , the specific method is as follows:

Set up two magnetic leakage imaging processing methods according to the needs, one is less computationally complex, which is recorded as magnetic leakage imaging processing method A, and the other is more computationally complex and has a higher accuracy rate, which is recorded as magnetic leakage imaging processing method B ; For each segment of sampled signal X _i , first use the magnetic flux leakage imaging processing method A to perform magnetic flux leakage imaging processing and damage diagnosis, and obtain a magnetic flux leakage image Y _i ^A with a size of M′×L, where M′ is a preset Magnetic flux leakage image width parameter, if the damage diagnosis result is no damage, then the magnetic leakage image Y _i ^A is used as the magnetic leakage image Y _i corresponding to the sampling signal _Xi , that is, Y _i =Y _i ^A , if the diagnosis result is damage , the magnetic leakage imaging processing method B is used to perform magnetic leakage imaging processing and damage diagnosis, and the obtained magnetic leakage image Y _i ^B with a size of M′×L is used as the magnetic leakage image Y _i corresponding to the sampling signal X _i , That is, Y _i =Y _i ^B , and mark the diagnosed damage area in the magnetic flux leakage image Y _i ;

S4: judge whether the serial number i=1 of the sampling signal X _i , if yes, enter step S5, otherwise enter step S6;

S5: Make the spliced magnetic flux leakage image Z ₁ =Y ₁ ;

S6: Stitching the current magnetic flux leakage image Y _i with the existing spliced magnetic flux leakage image Z _i-1 is divided into the following four situations:

If the damage diagnosis result of the overlapping data segment in the i-th segment magnetic leakage image Y _i is no damage, and the damage diagnosis result of the i-1 segment magnetic leakage image Y _i-1 is no damage, then the overlapping data segment Use its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i-1 , that is, the overlapped data segment P _i =Y _i-1 (:,L-S+1:L) obtained by processing, ":" indicates that in the corresponding dimension All elements of , "α:β" means from the αth element to the βth element in the corresponding dimension;

If the damage diagnosis result of the overlapping data segment in the i-th segment magnetic leakage image Y _i is that there is no damage, and the damage diagnosis result of the i-1 segment magnetic leakage image Y _i-1 is that there is damage, then the overlapping data segment uses Its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i-1 , that is, the overlapped data segment P _i =Y _i-1 (:,L-S+1:L) obtained through processing;

If the damage diagnosis result of the overlapping data segment in the i-th segment magnetic leakage image Y _i is that there is damage, and the damage diagnosis result of the i-1 segment magnetic leakage image Y _i-1 is that there is no damage, then the overlapping data segment uses Its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i , that is, the overlapped data segment P _i =Y _i (:,1:S) obtained through processing;

表示向下取整；If the damage diagnosis result of the overlapping data segment in the i-th magnetic leakage image Y _i is that there is damage, and the damage diagnosis result of the i-1th magnetic leakage image Y _i-1 is that there is damage, then the front of the overlapping data segment Half use its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i-1 , and the second half use its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i , that is, the overlapped data segment obtained by processing

Indicates rounding down;

Finally, according to the processing results of the above overlapping data segments, the current magnetic flux leakage image Y _i is spliced with the existing stitched magnetic flux leakage image Z _i-1 , and the size of the existing stitched magnetic flux leakage image Z _i-1 is M′×D , the expression of the new spliced magnetic flux leakage image Z _i is as follows:

Z _i ＝[Z _i-1 (:,1:DS)P _i Y _i (:,S+1:L)]

S7: output the obtained mosaic magnetic flux leakage image Z _i and display it in real time;

S8: judging whether the processing of the sampling signal is completed, if not, proceed to step S9, otherwise the processing ends;

S9: set i=i+1, return to step S3.

The real-time processing method of magnetic flux leakage imaging of steel wire rope under continuous sampling of the present invention collects the magnetic flux leakage signal of the steel wire rope in sections when the magnetic flux leakage signal is collected, and uses the method of combining "preliminary screening" and "fine diagnosis" for each segment of magnetic flux leakage signal. Magnetic imaging processing, and then splicing the current magnetic flux leakage image and the existing spliced magnetic flux leakage image, in which the overlapping data segments are divided into four cases for processing, and after each splicing is completed, the spliced magnetic flux leakage image to be obtained will be output and processed Displayed in real time until all signals are processed. Adopting the present invention can effectively improve the processing speed of magnetic flux leakage imaging, avoid misjudgment or missed judgment of steel wire rope damage caused by signal segmentation, and realize real-time processing of magnetic flux leakage imaging of steel wire ropes.

Description of drawings

Figure 1 is a schematic diagram of the principle of wire rope damage diagnosis based on magnetic flux leakage images;

Fig. 2 is the concrete embodiment flowchart of the real-time processing method of magnetic flux leakage imaging of steel wire rope under the continuous sampling of the present invention;

Fig. 3 is a schematic diagram of a magnetic sensor array in the present invention;

Fig. 4 is a flow chart of the magnetic flux leakage imaging processing method A in this embodiment;

Fig. 5 is a flow chart of the magnetic flux leakage imaging processing method B in this embodiment;

Fig. 6 is a schematic diagram of sampling signal overlap in the present invention;

Fig. 7 is a schematic diagram of a case 1 of overlapping data segments in the present invention;

Fig. 8 is a schematic diagram of the second case of overlapping data segments in the present invention;

Fig. 9 is a schematic diagram of the third case of overlapping data segments in the present invention;

Fig. 10 is a schematic diagram of Situation 4 of overlapping data segments in the present invention.

Detailed ways

Specific embodiments of the present invention will be described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention. It should be noted that in the following description, when detailed descriptions of known functions and designs may dilute the main content of the present invention, these descriptions will be omitted here.

Example

Fig. 2 is a flow chart of a specific embodiment of the real-time processing method for magnetic flux leakage imaging of steel wire ropes under continuous sampling according to the present invention. As shown in Figure 2, the specific steps of the real-time processing method for magnetic flux leakage imaging of steel wire rope under continuous sampling of the present invention include:

S201: Magnetic sensor array setup:

In order to collect the magnetic flux leakage signal of the steel wire rope, the present invention sets a magnetic sensor array for collecting the magnetic flux leakage signal in the radial direction of the steel wire rope. Fig. 3 is a schematic diagram of a magnetic sensor array in the present invention. As shown in FIG. 3 , the magnetic sensor array in the present invention includes M magnetic sensors, and the M magnetic sensors are arranged at equal intervals along the circumference of the wire rope, and an annular armature is arranged outside the M magnetic sensors.

S202: Steel wire rope magnetic flux leakage signal collection:

Make the wire rope move relative to the axial direction of the magnetic sensor, and the data acquisition system periodically samples the current signals of M magnetic sensors. The length of the sampling signal of each magnetic sensor in each sampling is L, and the setting of the sampling period requires Let the adjacent two acquisition signals overlap, record the overlapping length as S, 0<S<L/2, record the sampling signal of the i-th steel wire rope as X _i , i=1,2,..., the sampling signal X _i is the size is a data matrix of M×L, wherein the nth sampling point data of the mth magnetic sensor is _Xi [m,n], m=1,2,...,M, n=1,2,...,L. The present invention adopts a processing method of imaging while sampling, that is, after each sampling is finished, it enters step S203.

Usually, in order to facilitate the comparison of the steel wire rope scrap judgment standard, the sampling signal length L is set as the signal length corresponding to the wire rope lay length or its multiple, that is, L=λα, where α represents the wire rope lay length, and λ=1,2,…. The coincidence length S can be controlled by adjusting the relative motion speed of the steel wire rope and the signal sampling period. The coincidence length S usually needs to be greater than twice the maximum possible damage sample length, that is, f _max ≤ S<L/2, f _max means Maximum damage sample length.

S203: Segmented imaging of wire rope magnetic flux leakage signal:

Next, magnetic flux leakage imaging needs to be performed on each segment of sampling signal _Xi respectively. In order to achieve the purpose of saving imaging processing time, the present invention adopts a magnetic flux leakage imaging processing method combining "coarse screening" and "fine diagnosis". The specific method as follows:

Set up two magnetic leakage imaging processing methods according to the needs, one is less computationally complex, which is recorded as magnetic leakage imaging processing method A, and the other is more computationally complex and has a higher accuracy rate, which is recorded as magnetic leakage imaging processing method B . For each segment of sampled signal X _i , first use magnetic flux leakage imaging processing method A to perform magnetic flux leakage imaging processing and damage diagnosis, and obtain a magnetic flux leakage image Y _i ^A with a size of M′×L, where M′ is the preset leakage Magnetic image width parameter, if the result of the damage diagnosis is that there is no damage, then the magnetic leakage image Y _i ^A is used as the magnetic leakage image Y _i corresponding to the sampling signal _Xi , that is, Y _i =Y _i ^A , if the diagnosis result is that there is damage, Then use the magnetic leakage imaging processing method B to perform magnetic leakage imaging processing and damage diagnosis, and use the obtained magnetic leakage image Y _i ^B with a size of M′×L as the magnetic leakage image Y _i corresponding to the sampling signal X _i , namely Y _i =Y _i ^B , and the diagnosed damage area is marked in the magnetic flux leakage image Y _i .

Magnetic flux leakage imaging processing methods A and B can be set according to actual needs. In this embodiment, magnetic flux leakage imaging processing method A refers to the patent "Chengdu Zhongchai Technology Co., Ltd. A processing and imaging method for radial magnetic flux leakage signals of steel wire ropes: China , 201810789584.3.2018-11-30" recorded method. FIG. 4 is a flow chart of the magnetic flux leakage imaging processing method A in this embodiment. As shown in Figure 4, the specific steps of the magnetic flux leakage imaging processing method A in this embodiment include:

S401: Moving average:

For the sampling signal X _i [m] corresponding to each magnetic sensor in the sampling signal X _i (that is, the row vector of the sampling signal X _i data matrix), use the moving average method to obtain the trend line data X _i of each magnetic sensor sampling signal ′[m], subtract the trendline data X _i ′[m] from the sampling signal X _i [m] to obtain the data DS _i [m]. The data DS _i [m] of the M magnetic sensors are combined into a detrended sampling signal DS _i .

S402: Determine the resampling line:

Determine the strand wave texture line of the sampling signal DS _i , and then search for the resampling line with the highest degree of coincidence with the strand wave texture line in the sampling signal DS _i and with an oblique filter span of K.

S403: Data interpolation:

In the circumferential direction, interpolate each group of M magnetic flux leakage signals DS _i [n] in the sampling signal DS _i (that is, the column vector of the data matrix of the sampling signal DS _i ) to obtain a signal DI _i [n] with a length of M′, and repeat A signal DI _i with a size of M′×L is constructed, and a zero matrix with a size of M′×M′ is respectively connected before and after the signal DI _i to obtain a signal DR _i . Extract data along the corresponding resampling line in the signal DR _i , and make the resampling line go through all the data for filtering, remove the two M'×M' matrices before and after the signal DR _i , that is, extract the data of the L columns in the middle of the signal DR _i , to obtain a signal DF _i with a size of M′×L.

S404: Calculate the envelope:

Calculate the amplitude value of the envelope estimate for each channel of data DF _i [m′] in the signal DF _i , and store the obtained data in the matrix DE _i whose size is M′×L.

S405: Defect judgment:

Preset the defect judgment threshold th, define a matrix DB _i with a size of M′×L, traverse each element in the matrix DE _i , if its value is greater than or equal to the threshold th, it is determined that the element belongs to a defect, and the corresponding element in the matrix DB _i element is set to 1, otherwise it is set to 0.

S406: Find the Hadamard product:

Do the Hadamard product of matrix DE _i and matrix DB _i to get matrix DO _i , that is, the elements in matrix DO _i are the product of the corresponding elements of matrix DE _i and matrix DB _i .

S407: Generating a magnetic flux leakage image:

The magnetic flux leakage image Y _i ^A is obtained by imaging the matrix DO _i , where the maximum value of the element in the matrix DO _i corresponds to the maximum value of the gray scale, and the value 0 corresponds to the minimum value of the gray scale. It can be seen that the obtained magnetic flux leakage image Y _i ^A contains the information of the presence or absence, position and intensity of the magnetic flux leakage signal of local defects.

MFL processing method B is further improved on the basis of method A. FIG. 5 is a flow chart of the magnetic flux leakage imaging processing method B in this embodiment. As shown in Figure 5, the specific steps of the magnetic flux leakage imaging processing method B in this embodiment include:

S501: Moving average:

For the sampling signal X _i [m] corresponding to each magnetic sensor in the sampling signal X _i (that is, the row vector of the sampling signal X _i data matrix), use the moving average method to obtain the trend line data X _i of each magnetic sensor sampling signal ′[m], subtract the trendline data X _i ′[m] from the sampling signal X _i [m] to obtain the data DS _i [m]. The data DS _i [m] of the M magnetic sensors are combined into a detrended sampling signal DS _i .

S502: Determine the resampling line:

Determine the strand wave texture line of the sampling signal DS _i , and then search for the resampling line with the highest degree of coincidence with the strand wave texture line in the sampling signal DS _i and with an oblique filter span of K.

S503: Data interpolation:

In the circumferential direction, interpolate each group of M magnetic flux leakage signals DS _i [n] in the sampling signal DS _i (that is, the column vector of the data matrix of the sampling signal DS _i ) to obtain a signal DI _i [n] with a length of M′, and repeat A signal DI _i with a size of M′×L is constructed, and a zero matrix with a size of M′×M′ is respectively connected before and after the signal DI _i to obtain a signal DR _i . Extract data along the corresponding resampling line in the signal DR _i , and make the resampling line go through all the data for filtering, remove the two M'×M' matrices before and after the signal DR _i , that is, extract the data of the L columns in the middle of the signal DR _i , to obtain a signal DF _i with a size of M′×L.

S404: Calculate the envelope:

Calculate the amplitude value of the envelope estimate for each channel of data DF _i [m′] in the signal DF _i , and store the obtained data in the matrix DE _i whose size is M′×L.

S405: Median filtering:

Connect a zero matrix with a size of M′×M′ before and after the matrix DE _i to obtain the matrix DP _i , and perform median filtering on the signal corresponding to each magnetic sensor in the matrix DP _i (that is, the row vector of the matrix DP _i ) , to get the matrix DP _i ′. The influence of wire rope vibration can be removed by median filtering. Then remove the two M′×M′ matrices before and after the matrix DP _i , that is, extract the data of the L columns in the middle of the matrix DP _i , and obtain a matrix DD _i with a size of M′×L.

S406: Defect judgment:

Preset the defect judgment threshold th, define a matrix DB _i with a size of M′×L, traverse each element in the matrix DD _i , if its value is greater than or equal to the threshold th, it is determined that the element belongs to a defect, and the corresponding element in the matrix DD _i element is set to 1, otherwise it is set to 0.

S407: Find the Hadamard product:

Do the Hadamard product of matrix DD _i and matrix DB _i to get matrix DO _i , that is, the elements in matrix DO _i are the product of the corresponding elements of matrix DD _i and matrix DB _i .

S408: Generating a magnetic flux leakage image:

The magnetic flux leakage image Y _i ^A is obtained by imaging the matrix DO _i , where the maximum value of the element in the matrix DO _i corresponds to the maximum value of the gray scale, and the value 0 corresponds to the minimum value of the gray scale.

S204: Judging whether the serial number _i of the sampling signal X i=1, if yes, it means that the currently obtained magnetic flux leakage image Y _i is the magnetic flux leakage image of the first section of the steel wire rope, no splicing is required, and proceed to step S205, otherwise proceed to step S204 S206.

S205: Set the stitched magnetic flux leakage image Z ₁ =Y ₁ .

S206: Wire rope magnetic flux leakage image stitching:

Next, it is necessary to stitch the current magnetic flux leakage image Y _i with the existing spliced magnetic flux leakage image Z _i-1 . Because the present invention is in the process of collecting signals, the sampling signals of the two steel wire rope sections before and after overlap. Fig. 6 is a schematic diagram of overlapping sampling signals in the present invention. As shown in Figure 6, since the overlapping length of the sampling signals of the two steel wire ropes before and after in the present invention is S, the overlapping data segment can be represented by the following formula:

Q _i =X _i [m,n]=X _i-1 [m,L-S+n], 1≤n≤S, 1≤m≤M

In order to avoid misjudgment or missed judgment of damage results caused by improper splicing, it is first necessary to distinguish and select the overlapping data segments of the current i-th segment of magnetic flux leakage image Y _i and the i-1th segment of magnetic flux leakage image Y _i-1 . According to the difference in the damage diagnosis results of the i-th segment of the magnetic flux leakage image Y _i and the i-1 segment of the magnetic leakage image Y _i-1 of the overlapping data segment, the processing of the overlapping data segment is divided into four cases:

Fig. 7 is a schematic diagram of the first case of overlapping data segments in the present invention. As shown in Figure 7, if the damage diagnosis result of the overlapping data segment in the i-th magnetic leakage image Y _i is no damage, and the damage diagnosis result of the i-1th magnetic leakage image Y _i-1 is non-existent damage, then the coincident data segment uses its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i-1 , that is, the processed coincident data segment P _i =Y _i-1 (:,L-S+1:L), ":" means all elements in the corresponding dimension, and "α:β" means from the αth element to the βth element in the corresponding dimension.

Fig. 8 is a schematic diagram of the second case of overlapping data segments in the present invention. As shown in Figure 8, if the damage diagnosis result of the overlapping data segment in the i-th magnetic leakage image Y _i is no damage, and the damage diagnosis result of the i-1th magnetic leakage image Y _i-1 is damage , then the coincident data segment uses its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i-1 , that is, the processed coincident data segment P _i =Y _i-1 (:,L-S+1:L).

Fig. 9 is a schematic diagram of the third case of overlapping data segments in the present invention. As shown in Figure 9, if the damage diagnosis result of the overlapping data segment in the i-th magnetic leakage image Y _i is damage, and the damage diagnosis result of the i-1th magnetic leakage image Y _i-1 is no damage , then the coincident data segment uses its corresponding magnetic flux leakage image in the magnetic flux leakage image Y _i , that is, the processed coincident data segment P _i =Y _i (:,1:S).

表示向下取整。Fig. 10 is a schematic diagram of Situation 4 of overlapping data segments in the present invention. As shown in Figure 10, if the damage diagnosis result of the overlapping data segment in the i-th magnetic leakage image Y _i is damage, and the damage diagnosis result of the i-1th magnetic leakage image Y _i-1 is damage, Then the first half of the overlapping data segment uses its corresponding magnetic leakage image in the magnetic flux leakage image Y _i-1 , and the second half uses its corresponding magnetic leakage image in the magnetic flux leakage image Y _i , that is, the processed overlapping data segment

Indicates rounding down.

Finally, according to the processing results of the above overlapping data segments, the current magnetic flux leakage image Y _i is spliced with the existing stitched magnetic flux leakage image Z _i-1 , and the size of the existing stitched magnetic flux leakage image Z _i-1 is M′×D , the expression of the new spliced magnetic flux leakage image Z _i is as follows:

Z _i ＝[Z _i-1 (:,1:DS)P _i Y _i (:,S+1:L)]

S207: Real-time display of spliced magnetic flux leakage images:

The obtained spliced magnetic flux leakage image Z _i is output and displayed in real time.

S208: Determine whether the sampling signal has been processed. If not, that is, the data acquisition system still has a new sampling signal to be processed, go to step S209; otherwise, the processing ends.

S209: set i=i+1, return to step S203.

Although the illustrative specific embodiments of the present invention have been described above, so that those skilled in the art can understand the present invention, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, As long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

Claims (4)

1. A steel wire rope magnetic flux leakage imaging real-time processing method under continuous sampling is characterized by comprising the following steps:

s1: arranging a magnetic sensor array which comprises M magnetic sensors, wherein the M magnetic sensors are arranged at equal intervals along the circumferential direction of the steel wire rope, and annular armatures are arranged on the outer sides of the M magnetic sensors;

s2: the steel wire rope generates relative motion in the axial direction of the magnetic sensors, a data acquisition system periodically samples current signals of M magnetic sensors, the length of a sampling signal of each magnetic sensor in each sampling is L, the setting of a sampling period needs to enable the overlapping of two adjacent acquired signals, the overlapping length is S, S is more than 0 and less than L/2, the sampling signal of the ith section of the steel wire rope is X _i I =1,2, \ 8230;, sampling signal X _i Is a data matrix of size M × L, wherein the nth sampling point data of the mth magnetic sensor is X _i [m,n](ii) a After sampling is finished each time, the step S3 is carried out;

s3: sampling signal X for each segment _i Respectively carrying out magnetic flux leakage imaging, wherein the specific method comprises the following steps:

two magnetic flux leakage imaging processing methods are set as required, one of the magnetic flux leakage imaging processing methods is low in calculation complexity and is marked as a magnetic flux leakage imaging processing method A, and the other of the magnetic flux leakage imaging processing methods is high in calculation complexity and accuracy and is marked as a magnetic flux leakage imaging processing method B; for each section of sampling signal X _i Firstly, the magnetic leakage imaging processing method A is adopted to carry out magnetic leakage imaging processing and carry out damage diagnosis to obtain a magnetic leakage image Y with the size of M' multiplied by L _i ^A M' is a preset magnetic leakage image width parameter, and if the damage diagnosis result shows that no damage exists, the magnetic leakage image Y is subjected to magnetic leakage image detection _i ^A As a sampling signal X _i Corresponding leakage magnetic image Y _i I.e. Y _i ＝Y _i ^A If the diagnosis result shows that the damage exists, the magnetic leakage imaging processing method B is adopted to carry out magnetic leakage imaging processing and carry out damage diagnosis, and the obtained magnetic leakage image Y with the size of M' multiplied by L is obtained _i ^B As sampled signal X _i Corresponding leakage magnetic image Y _i I.e. Y _i ＝Y _i ^B And in the leakage magnetic image Y _i Marking out the diagnosed damage area;

s4: judging whether to sample the signal X _i If yes, go to step S5, otherwise go to step S6;

s5: make concatenation magnetic leakage image Z ₁ ＝Y ₁ ；

S6: the current leakage magnetic image Y _i With the existing spliced leaky magnetic image Z _i-1 Splicing is carried out, and the following four conditions are adopted:

if the overlapped data segment is in the i-th segment of the leakage magnetic image Y _i The damage diagnosis result in (1) is that no damage exists and the leakage magnetic image Y is in the i-1 segment _i-1 If there is no damage, the superimposed data segment is used in the leakage magnetic image Y _i-1 Corresponding leakage magnetic image, i.e. processed coincident data segment P _i ＝Y _i-1 (L-S + 1L), ": denotes all elements in the corresponding dimension," α: β "denotes the corresponding dimension from the α -th element to the β -th element;

if the overlapped data segment is in the i-th segment of the leakage magnetic image Y _i The damage diagnosis result in (1) is that no damage exists and the leakage magnetic image Y is in the i-1 segment _i-1 If there is a damage, the coincidence data segment is used in the leakage magnetic image Y _i-1 Corresponding leakage magnetic image, i.e. processed coincident data segment P _i ＝Y _i-1 (:,L-S+1:L)；

If the overlapped data segment is in the i-th segment of the leakage magnetic image Y _i The damage diagnosis result in (1) is that there is damage and the leakage magnetic image Y is in the i-1 segment _i-1 If there is no damage, the coincidence data segment is used in the leakage magnetic image Y _i Corresponding leakage magnetic image, i.e. processed coincident data segment P _i ＝Y _i (:,1:S)；

If the overlapped data segment is in the i-th segment of the leakage magnetic image Y _i The damage diagnosis result in (1) is that there is damage and the leakage magnetic image Y is in the i-1 th segment _i-1 If there is a damage, the first half of the superimposed data segment is used in the leakage flux image Y _i-1 Middle corresponding magnetic flux leakage image, latterSemi-using it in leakage magnetic image Y _i Corresponding leakage images, i.e. processed coincident data segments

Represents rounding down;

finally, according to the processing result of the overlapped data segments, the current magnetic leakage image Y is processed _i With the existing spliced leaky magnetic image Z _i-1 Splicing, recording the spliced magnetic leakage image Z _i-1 Is M' x D, a new spliced leakage flux image Z _i The expression is as follows:

Z _i ＝[Z _i-1 (:,1:D-S) P _i Y _i (:,S+1:L)]

s7: the obtained spliced magnetic leakage image Z _i Outputting and displaying in real time;

s8: judging whether the processing of the sampling signal is finished, if not, entering the step S9, otherwise, finishing the processing;

s9: let i = i +1, return to step S3.

2. The method for real-time processing of magnetic flux leakage imaging of steel wire rope under continuous sampling according to claim 1, wherein the length of the sampled signal L = λ α, α represents the lay length of steel wire rope, λ =1,2, \ 8230;, in step S2.

3. The method for real-time processing of magnetic flux leakage imaging of steel wire rope under continuous sampling according to claim 1, wherein the overlapping length S in the step S2 satisfies f _max ≤S＜L/2，f _max Representing the maximum lesion sample length.

4. The method for processing the leakage flux of the steel wire rope under the condition of continuous sampling according to claim 1, wherein the method for processing the leakage flux of the steel wire rope in the step S3 comprises the following specific steps:

1) For the sampling signal X _i The sampling signal X corresponding to each magnetic sensor _i [m]Trend line data X 'of sampling signals of each magnetic sensor are obtained by a method of moving average' _i [m]Sampling the signal X _i [m]Subtract trend line data X' _i [m]To obtain data DS _i [m](ii) a Data DS of M magnetic sensors _i [m]Combined into a trend-removed sampling signal DS _i ；

2) Determining a sampling signal DS _i Then sample the signal DS _i Searching a resampling line with the highest coincidence degree with the strand corrugation line and the oblique filtering span of K;

3) For the sampled signals DS in the circumferential direction _i In each group of M leakage signals DS _i [n]Interpolating to obtain a signal DI of length M _i [n]Reconstructing to obtain a signal DI with a size of M' × L _i In the presence of signal DI _i Respectively connecting a zero matrix with the size of M 'x M' in front and back to obtain a signal DR _i (ii) a At signal DR _i The data is extracted along the corresponding re-sampling line, and the re-sampling line traverses all the data for filtering to remove the signal DR _i Two matrices of M 'x M' one after the other, i.e. extracting the signal DR _i The data of the middle L columns obtain a signal DF with the size of M' multiplied by L _i ；

4) For signal DF _i In each path of data DF _i [m′]Respectively calculating the amplitude of the envelope estimation, and storing the obtained data in a matrix DE with the size of M' multiplied by L _i The preparation method comprises the following steps of (1) performing;

5) Presetting a defect judgment threshold th, defining a matrix DB of size M' × L _i Traversal matrix DE _i If the value of each element in the matrix is greater than or equal to the threshold th, the element is determined to belong to a defect, and the matrix DB is formed _i The middle corresponding element is set to 1, otherwise, the middle corresponding element is set to 0;

6) General matrix DE _i And matrix DB _i Obtaining the matrix DO by doing Hadamard product _i ；

7) For the matrix DO _i Imaging to obtain leakage magnetic image Y _i ^A Wherein the matrix DO _i The maximum value of the element in (1) corresponds to the maximum value of the gray scale, and the value is 0 pairThe minimum value of the corresponding gray scale;

the magnetic leakage imaging processing method B specifically comprises the following steps:

1) For the sampling signal X _i Obtaining trend line data X 'of sampling signals of each magnetic sensor by respectively using a moving average method for the sampling signals corresponding to each magnetic sensor' _i [m]Sampling the signal X _i [m]Subtract trend line data X' _i [m]To obtain data DS _i [m](ii) a Data DS of M magnetic sensors _i [m]Combined into a trend-removed sampling signal DS _i ；

2) Determining a sampling signal DS _i Then sample the signal DS _i Searching a resampling line with the highest coincidence degree with the strand corrugation line and the oblique filtering span of K;

3) Sampling signal DS in the circumferential direction _i In each group of M leakage signals DS _i [n]Interpolating to obtain a signal DI of length M _i [n]Reconstructing to obtain signal DI with size of M' x L _i In the presence of signal DI _i The front and the rear are respectively connected with a zero matrix with the size of M 'multiplied by M' to obtain a signal DR _i (ii) a At signal DR _i The data is extracted along the corresponding re-sampling line, and the re-sampling line traverses all the data for filtering to remove the signal DR _i Two matrices of M 'x M' one after the other, i.e. extracting the signal DR _i The data of the middle L columns obtain a signal DF with the size of M' multiplied by L _i ；

4) For signal DF _i In each path of data DF _i [m′]Respectively calculating the amplitude of the envelope estimation, and storing the obtained data in a matrix DE with the size of M' x L _i The preparation method comprises the following steps of (1) performing;

5) In the matrix DE _i Respectively connecting a zero matrix with the size of M 'x M' to obtain a matrix DP _i To the matrix DP _i Carrying out median filtering on signals corresponding to each magnetic sensor to obtain a matrix DP' _i (ii) a The median filtering can be adopted to remove the influence of the wire rope shaking; then removing the matrix DP _i Two matrices of M 'x M' one after the other, i.e. the extracted matrix DP _i The data of the middle L column is obtained to obtain the moment with the size of M' multiplied by LArray DD _i ；

6) Presetting a defect judgment threshold th, defining a matrix DB with a size of M' × L _i Traversal matrix DE _i If the value of each element in the matrix is greater than or equal to the threshold th, the element is determined to belong to a defect, and the matrix DB is formed _i The middle corresponding element is set to 1, otherwise, the middle corresponding element is set to 0;

7) Will matrix DE _i And matrix DB _i Obtaining the matrix DO by doing Hadamard product _i ；

8) For matrix DO _i Imaging to obtain leakage magnetic image Y _i ^A Wherein the matrix DO _i The maximum value of the element(s) in (1) corresponds to the maximum value of the gray scale, and the value 0 corresponds to the minimum value of the gray scale.

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