CN108918654B - Method for processing and imaging radial magnetic flux leakage signal of steel wire rope - Google Patents
Method for processing and imaging radial magnetic flux leakage signal of steel wire rope Download PDFInfo
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Abstract
The invention relates to a method for processing and imaging a radial magnetic flux leakage signal of a steel wire rope, and belongs to the field of detection of local defects of the steel wire rope. The method is based on the oblique filtering and the enveloping surface, and can effectively filter the spike wave signals and improve the signal-to-noise ratio on the premise of ensuring that the local defect signals are not greatly attenuated; and the impact signal of one local defect can be imaged into a continuous pixel, so that the problem of double-point imaging is avoided, and the existence and the position information of the local defect are more accurately determined.
Description
Technical Field
The invention relates to the field of detection of local defects of a steel wire rope, in particular to a method for processing and imaging a radial magnetic flux leakage signal of the steel wire rope.
Background
The steel wire rope has the characteristics of high strength, high reliability, high stability and the like, is widely applied to various industrial scenes, and has the functions of lifting, traction, bearing and the like. Since the steel wire rope is usually used as a key component of a large machine, the working state of the steel wire rope will affect the running condition and safety performance of the whole equipment. Therefore, the fault diagnosis of the steel wire rope is of great significance to ensure the stability of equipment and the production safety.
The external environment in which the steel wire rope works can cause local defects through the actions of friction, collision, corrosion and the like. Such defects will affect the performance of the steel cord to some extent. Information of local defects is often used as one of the indicators reflecting the health of the steel cord.
There are many methods for detecting local defects in steel cords. One common method is to collect the leakage magnetic signal on the surface of the steel wire rope (principle is shown in fig. 1). In various signal acquisition methods, the Hall sensor arrays distributed at equal intervals in the circumferential direction are used for effective and visual equal-displacement sampling. At present, there are a variety of processing methods for the signals collected by this method, some methods analyze and process the signals directly, and some methods image the signals and analyze and process the images. In the imaging method, filtering of a strake wave signal and imaging of a local defect signal can have two problems.
Disclosure of Invention
The invention aims to provide a method for processing and imaging a radial magnetic flux leakage signal of a steel wire rope, which can effectively filter a strand wave signal, eliminate double-point imaging and improve the signal-to-noise ratio on the premise of ensuring that a local defect signal is not greatly attenuated.
The above object of the present invention is achieved by the following technical solutions:
a method for processing and imaging a radial magnetic flux leakage signal of a steel wire rope comprises the following steps: s1, acquiring radial magnetic flux leakage signals of a steel wire rope to obtain X groups of Y magnetic flux leakage data, and storing the X groups of Y magnetic flux leakage data in an array D; s2: respectively using an averaging method to obtain a trend line of the magnetic leakage data for each path of magnetic leakage data in the array D, and subtracting the trend line from the original data to obtain an array DS; s3: determining a resampling line of the span M of the oblique filtering in the array DS, and enabling the resampling line to be overlapped with the strand corrugation line as much as possible; s4: interpolating each group of Y leakage magnetic data in the array DS in the circumferential direction by using an interpolation method, enabling an interpolation result to contain M data to form a new array DI, respectively connecting a zero matrix with the size of M X M in front of and behind the array DI, defining the new array as DR, extracting data along a re-sampling line in the array DR, enabling the re-sampling line to traverse all data for filtering, removing two M matrices in front of and behind the array DR, and extracting data with the length of X in the middle of the array to form a new array DF; s5: and respectively solving the amplitude of the envelope estimation for each path of data in the array DF, and storing new data in the array DE.
Further, the method further comprises step S6: determining a threshold th, defining an array DB with the same size as the DE, and judging each numerical value in the array DE; if the value is greater than or equal to th, setting the corresponding element in the array DB as 1, otherwise, setting the corresponding element as 0; and imaging the array DB, wherein the value 1 corresponds to the maximum gray value, the value 0 corresponds to the minimum gray value, and black pixels in the obtained image represent the local defects of the steel wire rope.
Further, the method also comprises a step S7 of performing Hadamard product on the array DB and the array DE to obtain a new matrix DO; s8: and imaging the array DO, wherein the maximum value in the DO corresponds to the maximum gray value, and the numerical value 0 corresponds to the minimum gray value.
Further, in the step S2, a smoothing method is respectively used for each path of magnetic leakage data to obtain a trend line of the magnetic leakage data, and then the trend line is subtracted from the original data, specifically:
DS y [n]＝D y [n]-T y [n]
wherein D is y Is the original y-th data, T y Is the trend line of the data of the path, N is the span of the moving average, DS y And for the Y-th path of data after trend removal, after all the Y-path data are processed, the array DS after trend removal is formed again.
Further, the step S4 is to extract data along the resampling line in the array DR, filter all data traversed by the resampling line, remove two M × M matrices before and after the array DR, and extract data with length X in the middle of the array, and the method for forming the new array DF specifically includes: in an array DR, a resampling line is started from the xth group data to the xth + M group data, the M data are stored in an array Temp, a trend line is obtained for the data in Temp by a smoothing method, the trend line is subtracted from the data in Temp to obtain trend-removed data, and then the processed data Temp' is written back to the original position along the resampling line:
Temp'[n]＝Temp[n]-T Temp [n]
and changing X from 1 to X to obtain a new re-sampling line, repeating the processing process until the re-sampling line traverses all the magnetic leakage data, and after the processing is finished, removing two M matrixes before and after the array and extracting data with the length of X in the middle of the array from M +1 to M + X to form a new array DF, wherein the DF is of the size of M X.
Further, the step S6 can be described as:
further, the step S7 can be described as: DO (x, y) = DB (x, y) × DE (x, y).
In conclusion, the invention has the following beneficial effects:
the imaging method is based on the oblique filtering and the enveloping surface, and can effectively filter the strand wave signals and improve the signal-to-noise ratio on the premise of ensuring that local defect signals are not greatly attenuated; and the impact signal of a local defect can be imaged into a continuous pixel, so that the problem of double-point imaging is avoided, and the existence and the position information of the local defect are more accurately determined.
Drawings
FIG. 1 is a schematic view of the magnetic flux leakage principle of the embodiment of the present invention;
fig. 2 is a schematic diagram of resampling according to an embodiment of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be described below with reference to the accompanying drawings.
A method for processing and imaging a radial magnetic flux leakage signal of a steel wire rope comprises the following steps:
s1, collecting radial magnetic flux leakage signals of the steel wire rope to obtain X groups of Y magnetic flux leakage data, and storing the X groups of Y magnetic flux leakage data in an array D.
And moving the Hall sensor array which is distributed at equal intervals in the circumferential direction along the steel wire rope. The method is used for collecting radial magnetic flux leakage signals of the steel wire rope at equal intervals to obtain Y-path magnetic flux leakage data D1, D2 and D3 \8230andDY. And then the Y-path data is stored in an array D. If a total of X sets of data are collected, array D includes Y rows and X columns, the size of which is Y X.
S2: and respectively obtaining the trend line of the magnetic leakage data by using a moving average method for each path of magnetic leakage data in the array D, and subtracting the trend line from the original data to obtain the array DS.
Firstly, obtaining a trend line of data by respectively using a moving average method for each path of data of an array D, and then subtracting the trend line from the original data:
DS y [n]＝D y [n]-T y [n]
wherein D is y Is the original y-th data, T y Is the trend line of the data of the path, N is the span of the moving average, DS y The data of the y-th path after trend removing. And after all the Y-path data are processed, the array DS with the trend removed is formed again.
S3: and determining a resampling line with the span M of the oblique filtering in the array DS, so that the resampling line is superposed with the strand corrugation line as much as possible.
A diagonal filtering span M is determined so that the resample lines in fig. 2 coincide as much as possible with the strand-corrugated lines.
S4: and interpolating each group of Y leakage magnetic data in the array DS in the circumferential direction by using an interpolation method to enable an interpolation result to contain M data to form a new array DI, respectively connecting a zero matrix with the size of M X M before and after the array DI, defining the new array as DR, extracting data along a resampling line in the array DR, enabling the resampling line to traverse all the data for filtering, removing two M matrices before and after the array DR, and extracting data with the length of X in the middle of the array to form a new array DF.
And (3) interpolating Y data in the original group of data in the circumferential direction by using an interpolation method, so that an interpolation result contains M data. After interpolation, the Y-path data is expanded into M-paths, and the new data forms an array DI. The size of DI is M × X.
A zero matrix with the size of M multiplied by M is respectively connected to the front and the back of the array DI, and a new array with the size of M multiplied by (X + 2M) is defined as DR. Data is extracted along the re-sampling line in fig. 2 in array DR, re-sampled and filtered. Specifically, the M data passed by one resampling line (starting at the xth data and ending at the xth + M data) are stored in the array Temp. Solving a trend line of the data in Temp by a moving average method, subtracting the trend line of the data in Temp to obtain trend-removed data, and then writing the processed data Temp' back to an original position along a resampling line:
Temp'[n]＝Temp[n]-T Temp [n]
changing X to obtain a new resampling line, and repeating the processing process until the resampling line traverses all the leakage flux data (X is from 1 to X). After the processing is finished, removing two M × M matrixes before and after the array, and extracting data (from M +1 to M + X) with the length of X in the middle of the array to form a new array DF. The size of DF is M X.
S5: and respectively solving the amplitude of the envelope estimation for each path of data in the array DF, and storing new data in the array DE.
S6: determining a threshold th, defining an array DB with the same size as the DE, and judging each numerical value in the array DE; if the value is greater than or equal to th, setting the corresponding element in the array DB as 1, otherwise, setting the corresponding element as 0; and imaging the array DB, wherein the value 1 corresponds to the maximum gray value, the value 0 corresponds to the minimum gray value, and black pixels in the obtained image represent the local defects of the steel wire rope. The presence and location of defects can be determined from the image.
The method can be described as:
and S7, performing Hadamard product on the array DB and the array DE to obtain a new matrix DO.
DO(x,y)＝DB(x,y)×DE(x,y)
S8: imaging the array DO, wherein the maximum value in the DO corresponds to the maximum value of the gray scale, and the value 0 corresponds to the minimum value of the gray scale; the image contains information on the presence or absence of a local defect, the position, and the intensity of the leakage magnetic signal.
Claims (5)
1. A method for processing and imaging a radial magnetic flux leakage signal of a steel wire rope is characterized by comprising the following steps:
s1, acquiring radial magnetic flux leakage signals of a steel wire rope to obtain X groups of Y magnetic flux leakage data, and storing the X groups of Y magnetic flux leakage data in an array D;
s2: respectively using a smoothing method to obtain a trend line of the magnetic leakage data for each path of magnetic leakage data in the array D, and then subtracting the trend line from the original data to obtain an array DS;
s3: determining a resampling line of the span M of the oblique filtering in the array DS, and enabling the resampling line to be overlapped with the strand corrugation line as much as possible;
s4: interpolating each group of Y leakage magnetic data in the array DS in the circumferential direction by using an interpolation method, enabling an interpolation result to contain M data to form a new array DI, respectively connecting a zero matrix with the size of M X M in front of and behind the array DI, defining the new array as DR, extracting data along a re-sampling line in the array DR, enabling the re-sampling line to traverse all data for filtering, removing two M matrices in front of and behind the array DR, and extracting data with the length of X in the middle of the array to form a new array DF;
s5: respectively solving the amplitude of the envelope estimation for each path of data in the array DF, and storing new data in the array DE;
s6: determining a threshold th, defining an array DB with the same size as the DE, and judging each numerical value in the array DE; if the numerical value is larger than or equal to th, setting the corresponding element in the array DB as 1, otherwise setting the corresponding element as 0, imaging the array DB, wherein the numerical value 1 corresponds to the maximum gray value, the numerical value 0 corresponds to the minimum gray value, and the black pixel in the obtained image represents the local defect of the steel wire rope;
s7, performing Hadamard product on the array DB and the array DE to obtain a new matrix DO;
s8: and imaging the array DO, wherein the maximum value in the DO corresponds to the maximum gray value, and the numerical value 0 corresponds to the minimum gray value.
2. The method for processing and imaging the radial magnetic flux leakage signal of the steel wire rope according to claim 1, wherein in the step S2, a trend line of the magnetic flux leakage data is obtained by respectively using a moving average method for each magnetic flux leakage data, and then the trend line is subtracted from the original data, specifically:
DS y [n]＝D y [n]-T y [n]
wherein D is y Is the original y-th data, T y Is the trend line of the way data, N is the span of the moving average, DS y And for the Y-th path of data after trend removal, after all the Y-path data are processed, the array DS after trend removal is formed again.
3. The method for processing and imaging the radial magnetic flux leakage signal of the steel wire rope according to claim 2, wherein the step S4 is to extract data along a resampling line in an array DR, filter all data traversed by the resampling line, remove two M × M matrices before and after the array DR, extract data with a length X in the middle of the array, and form a new array DF, specifically: in an array DR, a resampling line is started from the xth data and ended from the xth data to the xth + M data, the passed M data are stored in an array Temp, a trend line is calculated for the data in the array Temp by a smoothing method, the trend line is subtracted from the data in the array Temp to obtain trend-removed data, and then the processed data array Temp' is written back to an original position along the resampling line:
Temp'[n]＝Temp[n]-T Temp [n]
and changing X from 1 to X to obtain a new re-sampling line, repeating the processing process until the re-sampling line traverses all the magnetic leakage data, and after the processing is finished, removing two M matrixes before and after the array and extracting data with the length of X in the middle of the array from M +1 to M + X to form a new array DF, wherein the DF is of the size of M X.
4. The method for processing and imaging the radial magnetic flux leakage signal of the steel wire rope according to claim 3, wherein the step S6 is described as follows:
5. the method for processing and imaging the radial magnetic flux leakage signal of the steel wire rope according to claim 4, wherein the step S7 is described as follows: DO (x, y) = DB (x, y) × DE (x, y).
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| CN110596233B (en) * | 2019-08-27 | 2022-11-22 | 电子科技大学 | Steel wire rope magnetic flux leakage imaging real-time processing method under continuous sampling |
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