CN110568059B - Method and device for nondestructive testing of steel wire rope - Google Patents

Abstract

The invention provides a nondestructive testing method and a nondestructive testing device for a steel wire rope, wherein the method comprises the following steps of: acquiring a magnetic flux signal of a steel wire rope to be detected through a magnetic flux detection sensor, and acquiring a magnetic leakage signal of the steel wire rope to be detected through a magnetic field intensity detection sensor; preprocessing the magnetic flux signal and the magnetic leakage signal, obtaining a magnetic flux characteristic value according to the preprocessed magnetic flux signal, and obtaining a magnetic leakage characteristic value according to the preprocessed magnetic leakage signal; obtaining the defect width of the steel wire rope to be tested according to the magnetic flux characteristic value and the magnetic leakage characteristic value; comparing the defect width of the detected steel wire rope with a preset width threshold value; if the defect width is larger than or equal to a preset width threshold value, obtaining the section loss of the steel wire rope to be detected according to the magnetic flux characteristic value; and if the defect width is smaller than the preset width threshold, obtaining the section loss of the steel wire rope to be detected according to the magnetic flux characteristic value and the magnetic leakage characteristic value. The invention can identify all types of defects of the detected steel wire rope, and has high quantitative accuracy of section loss.

Description

Method and device for nondestructive testing of steel wire rope

technical field

The invention belongs to the technical field of wire rope detection, and in particular relates to a method and device for nondestructive detection of wire ropes by detecting magnetic flux and leakage magnetic field.

Background technique

Steel wire ropes are widely used in industrial, civil, military and other fields. With the use of time, various damages to the steel wire rope are inevitable, which will significantly reduce the strength, toughness, plasticity and other mechanical properties of the material, and seriously affect its safe use, so regular inspections are required. Among them, the loss of section loss of wire rope defects directly affects the quality of wire rope, so the quantitative detection of section loss of wire rope defects is the most important.

Electromagnetic detection method is the most commonly used and effective method, which includes two conditions of saturation excitation and non-saturation excitation. Among them, under unsaturated excitation conditions, there are strict requirements for detection sensors, environment and methods, and accurate quantitative results cannot be obtained; under saturated excitation conditions, the shortcomings of unsaturated excitation conditions can be avoided and the accuracy of quantitative detection can be improved. , and better applied to actual detection.

Under the condition of saturation excitation, it can be divided into two methods: flux detection and flux leakage detection. The magnetic flux detection mainly detects the change of the magnetic flux of the measured object, and the magnetic flux includes the main magnetic flux, the leakage magnetic flux and the magnetic yoke magnetic flux. The advantage of this method is that when the axial width of the detected defect is large, the detected flux value is directly related to the cross-sectional loss area of the measured object, so the cross-sectional loss of the measured object can be directly calculated through the detected flux value. However, when the axial width of the defect is small, the detected flux value is not only related to the cross-sectional loss area of the measured object, but also related to the axial width of the defect, which presents a complex nonlinear relationship and cannot quantitatively detect the cross-section. loss area, or its detection accuracy is very low. Magnetic flux leakage detection mainly detects the magnetic flux leakage intensity on the surface of the object to be measured through the sensor array. The advantage of this method is that it has a high recognition rate for defects with small axial width. However, for defects with large axial width, the information of the defects cannot be accurately identified, and the amount of cross-section loss cannot be quantitatively detected. It needs to be quantitatively analyzed through complex calculation methods such as neural networks. This method can only identify surface defects, not internal defects. This method requires a large number of standard defects to train a specific artificial neural network for classification and recognition. If the wire rope type is changed, the artificial neural network needs to be retrained.

Therefore, the current electromagnetic detection method cannot quantitatively detect the cross-section loss of all defects in the wire rope, and the detection accuracy is very low and the calculation is complicated.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a method and device for non-destructive testing of steel wire ropes, which aim to identify all types of defects of the tested steel wire ropes by combining magnetic flux detection and magnetic flux leakage detection, and improve the quantitative accuracy of cross-section loss.

The present invention is realized in this way, a kind of non-destructive testing method of steel wire rope, the method comprises the following steps:

Step S10, obtaining the magnetic flux signal of the steel wire rope under test through a magnetic flux detection sensor, and obtaining the magnetic flux leakage signal of the steel wire rope under test through the magnetic field strength detection sensor;

Step S20, preprocessing the magnetic flux signal and magnetic flux leakage signal of the tested wire rope, obtaining the magnetic flux characteristic value of the defect of the tested wire rope according to the preprocessed magnetic flux signal, and obtaining the magnetic flux characteristic value of the tested wire rope defect according to the preprocessed magnetic flux signal. Obtain the magnetic flux leakage characteristic value of the tested wire rope defect;

Step S30, obtaining the defect width of the tested wire rope according to the magnetic flux characteristic value and the magnetic leakage characteristic value;

Step S40, comparing the defect width of the tested wire rope with a preset width threshold;

If the defect width of the tested wire rope is greater than or equal to the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope defect;

If the defect width of the tested wire rope is smaller than the preset width threshold, the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value of the defect of the tested wire rope.

A further technical solution of the present invention is that, in step S20, the step of preprocessing the magnetic flux signal of the tested wire rope includes:

Perform outlier elimination, noise filtering, and baseline elimination on the magnetic flux signal of the tested wire rope;

Wherein, the step of removing outliers on the magnetic flux signal of the tested wire rope includes:

Perform wild point elimination on the magnetic flux signal Y of the wire rope to be tested, and set Y(i) as the i-th magnetic flux acquisition signal, so there is △Y=|Y(i)-Y(i+1)|, where, △Y is the absolute value of the magnetic flux signal difference between two adjacent magnetic flux signal collection points; for any i, if there is △Y≤M, M is the preset threshold, if there is a point Yi: |Y (i)-Y(i-1)|>M, and |Y(i)-Y(i+1)|>M, then:

The signal Y ₁ (i) is obtained after the wild point elimination process;

The steps of performing noise filtering on the magnetic flux signal of the wire rope under test include:

Noise filtering is performed on the magnetic flux signal of the tested wire rope by using adaptive filtering or wavelet transform or smoothing filtering or empirical mode decomposition, wherein the smoothing filter is used to filter the magnetic flux signal of the tested wire rope. The formula for noise filtering for:

where n is the number of data to be averaged, and N is the total number of sampling points;

The steps of performing baseline elimination on the magnetic flux signal of the tested wire rope include:

Use envelope spectrum extraction or wavelet decomposition or window average or empirical mode decomposition to perform baseline elimination on the magnetic flux signal of the tested steel wire rope, wherein, use empirical mode decomposition to perform baseline elimination on the magnetic flux signal of the tested steel wire rope The steps include:

Find out all the maximum and minimum points of the signal data sequence Y ₂ (i), and use the cubic spline function to fit them as the upper and lower envelopes of the original sequence; the upper envelope and the mean of the lower envelope is m1; subtracting m1 from the data sequence _Y2 (i) yields a new sequence _Y3 (i) minus the low frequency, that is, _Y3 (i)= _Y2 (i)-m1.

A further technical solution of the present invention is that the magnetic flux characteristic value includes at least one or more of the peak-to-peak value, width, average value, area, and mean square error of each defect waveform of the wire rope to be tested. The steps of obtaining the magnetic flux characteristic value of the tested wire rope defect from the magnetic flux signal include:

Setting a preset threshold value, extracting sampling points greater than the preset threshold value, and the preset threshold value is obtained through the test of the actual minimum defect of the wire rope under test;

According to the position information of the extracted sampling points, N points are intercepted on the left and right of the waveform axis to obtain each defect waveform, where N is obtained through the test of the actual maximum defect of the tested wire rope;

Extract the peak-to-peak value, width, average value, area and mean square error of each defect waveform.

A further technical solution of the present invention is that, in step S20, the step of preprocessing the flux leakage signal of the wire rope under test includes:

Perform outlier elimination, noise filtering, baseline elimination, and strand wave noise filtering on each channel of the tested wire rope magnetic flux leakage signal;

Wherein, the step of removing outliers for each magnetic flux leakage signal of the tested wire rope includes:

Perform wild point elimination for each channel of magnetic flux leakage signal X, and set X _i,j as the jth sampling value of the ith Hall sensor, so there is △X=|X _i,j —X _i,(j+1) | , where ΔX is the absolute value of the difference between the two adjacent sampling values of the ith Hall sensor; for any i, j, if there is ΔX≤F, F is the preset threshold, at this time:

The signal X _i,j is obtained after the wild point elimination process;

The steps of performing noise filtering on each magnetic flux leakage signal of the tested steel wire rope include:

Adaptive filtering or wavelet transform or smoothing filtering or empirical mode decomposition is used to perform noise filtering on each channel of magnetic flux leakage signal of the tested wire rope; wherein, smoothing filtering is used to filter the noise of each channel of magnetic flux leakage signal of the tested wire rope. The calculation formula is:

Among them, n is the number of data for averaging, N is the total number of sampling points, and k is the number of magnetic field intensity detection sensors that collect the flux leakage signal of the wire rope under test;

The steps of performing baseline elimination on each channel of magnetic flux leakage signal of the tested steel wire rope include:

Envelope spectrum extraction or wavelet decomposition or window average or empirical mode decomposition is used to perform baseline elimination on the MFL signal of each channel of the tested wire rope; wherein, the empirical mode decomposition is used to analyze the MFL signal of each channel of the tested wire rope. The steps for signal baseline cancellation include:

Find out all the maximum and minimum points of the original magnetic flux leakage signal data sequence X, and use the cubic spline function to fit them into the upper and lower envelopes of the original sequence, the upper envelope and The mean value of the lower envelope is m1; subtract m1 from the original data sequence to obtain a new sequence X ₁ minus the low frequency, that is, X ₁ =X-m1;

The steps of filtering out the strand-wave noise for each channel of magnetic flux leakage signal of the tested steel wire rope include:

Wavelet decomposition or empirical mode decomposition or adaptive filtering or gradient method is used to filter out the stray wave noise of each magnetic flux leakage signal of the tested wire rope, wherein the gradient method is used to The steps of filtering the signal to the strand noise include:

The gradient method is used to realize the first-order differentiation of the image. For the image X ₁ (x, y), its gradient at the coordinate (x, y) is represented by a two-dimensional column vector:

The modulus of this vector is:

The multi-channel flux leakage signal is summed to obtain the flux leakage sum signal X2.

A further technical solution of the present invention is that in the step S20, the magnetic flux leakage characteristic value of the tested wire rope at least includes the peak-to-peak value, width, average value, area, and mean square error of each defect waveform of the tested wire rope, so The step of obtaining the magnetic flux leakage characteristic value of the tested wire rope defect according to the preprocessed magnetic flux leakage signal includes:

The local maximum value method is used to locate the defect, and a preset threshold is set to determine whether it is a defect, wherein the preset threshold is obtained by testing the actual minimum defect of the wire rope;

Taking the found defect position as the center point, intercept L points on the left and right of the waveform axis to obtain each defect waveform, where L is obtained through the test of the actual wire rope maximum defect;

Extract the peak-to-peak value, width, average value, area and mean square error of each defect waveform of the tested wire rope.

A further technical solution of the present invention is that, in the step S30, the step of obtaining the defect width of the tested wire rope according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value includes:

Input the waveform width, waveform area and the waveform width and waveform area of the magnetic flux characteristic value into the defect width calculation equation or neural network to obtain the defect width of the tested wire rope.

A further technical solution of the present invention is that, in the step S40, if the defect width of the tested wire rope is greater than or equal to the preset width threshold, the measured wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope. The steps for measuring the cross-sectional loss of the wire rope include:

If the defect width of the tested wire rope is greater than or equal to the preset width threshold, the peak-to-peak value of the waveform, the waveform area, the waveform average value, and the waveform mean square error in the magnetic flux characteristic value are input into the defect cross-section loss amount magnetic flux calculation Equation or neural network to obtain the section loss of the tested wire rope defect.

A further technical solution of the present invention is that, in the step S40, if the defect width of the tested wire rope is smaller than the preset width threshold, then according to the magnetic flux characteristic value and the magnetic leakage characteristic value of the tested wire rope to obtain The step of measuring the cross-section loss of the steel wire rope includes:

If the defect width of the tested wire rope is smaller than the preset width threshold, the peak-to-peak value of the waveform, the waveform area, the waveform average value, the waveform mean square error and the peak-to-peak value of the waveform in the magnetic flux characteristic value of the magnetic flux characteristic value , waveform area, waveform average value, and waveform mean square error are input into the calculation equation or neural network for the loss of the defect section, and the section loss of the tested wire rope is obtained.

In order to achieve the above purpose, the present invention also proposes a non-destructive testing device for steel wire rope, the device includes a magnetic flux detection sensor, a magnetic field intensity detection sensor, and a signal acquisition and processing system, wherein,

The magnetic flux detection sensor is used for acquiring the magnetic flux signal of the tested wire rope, and the magnetic field strength detection sensor is used for acquiring the magnetic flux leakage signal of the tested wire rope;

The signal acquisition and processing system includes a signal acquisition unit, a signal preprocessing unit, a eigenvalue calculation unit, and a defect section loss quantitative analysis unit, wherein,

The signal preprocessing unit is used for preprocessing the magnetic flux signal and the magnetic flux leakage signal of the wire rope under test;

The characteristic value calculation unit is used to obtain the magnetic flux characteristic value of the tested wire rope defect according to the preprocessed magnetic flux signal, and obtain the magnetic flux leakage characteristic value of the tested wire rope defect according to the preprocessed magnetic flux leakage signal;

The defect section loss quantitative analysis unit is used to obtain the defect width of the tested wire rope according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value;

The defect section loss quantitative analysis unit is further configured to compare the defect width of the tested wire rope with a preset width threshold;

If the defect width of the tested wire rope is greater than or equal to the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope defect;

If the defect width of the tested wire rope is smaller than the preset width threshold, the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value of the defect of the tested wire rope.

A further technical solution of the present invention is to further include an excitation structure for exciting the tested steel wire rope to saturation or near saturation.

The beneficial effects of the wire rope nondestructive testing method and device of the present invention are as follows: the present invention obtains the magnetic flux signal of the tested steel wire rope through the magnetic flux detection sensor, and obtains the magnetic flux leakage signal of the tested steel wire rope through the magnetic field strength detection sensor through the above technical scheme; Preprocess the magnetic flux signal and magnetic flux leakage signal of the tested wire rope, obtain the magnetic flux characteristic value of the tested wire rope defect according to the preprocessed magnetic flux signal, and obtain the magnetic flux characteristic value according to the preprocessed magnetic flux leakage signal. The magnetic flux leakage characteristic value of the defect of the tested wire rope; the defect width of the tested wire rope is obtained according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value; the defect width of the tested wire rope is compared with the preset width threshold. ; If the defect width of the tested wire rope is greater than or equal to the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope defect; If the defect width of the wire rope is smaller than the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value and magnetic flux leakage characteristic value of the defect of the tested wire rope, combined with the magnetic flux detection and magnetic flux leakage detection. , not only can identify all types of defects in the tested wire rope, but also has the advantages of high cross-section loss quantitative accuracy, simple quantitative method, and no need for complex calculation methods or training fitting samples.

Description of drawings

Fig. 1 is the schematic flow chart of the preferred embodiment of the non-destructive testing method carried out by the wire rope of the present invention;

Fig. 2 is the structural representation of the nondestructive testing device for steel wire rope of the present invention;

3 is a schematic structural diagram of a magnetic flux detection sensor in the non-destructive testing device for steel wire ropes of the present invention;

Fig. 4 is the structural representation of the magnetic flux leakage detection sensor in the non-destructive testing device for steel wire rope of the present invention;

FIG. 5 is a schematic structural diagram of a signal acquisition and processing system in the non-destructive testing device for steel wire ropes of the present invention.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

Considering that the current electromagnetic detection method cannot quantitatively detect the cross-section loss of all the defects of the wire rope, and the detection accuracy is very low and the calculation is complicated, the present invention proposes a non-destructive detection method and device for the wire rope by detecting the magnetic flux and the leakage magnetic field. , By detecting the magnetic flux and leakage magnetic field, the present invention can not only identify all defect types including internal defects of the wire rope to be tested, but also has the advantages of higher quantitative accuracy of cross-section loss and simple calculation.

Specifically, please refer to FIG. 1 , which is a schematic flowchart of a preferred embodiment of a method for nondestructive testing of a wire rope of the present invention.

As shown in Figure 1, in this embodiment, the non-destructive testing method for the steel wire rope includes the following steps:

In step S10, the magnetic flux signal of the tested steel wire rope is acquired by the magnetic flux detection sensor, and the magnetic flux leakage signal of the tested steel wire rope is acquired by the magnetic field strength detection sensor.

It can be understood that, in this embodiment, the system structure of the entire detection device to which the wire rope nondestructive detection method is applied includes an excitation structure 1 , a sensor 2 , and a signal acquisition and processing system 3 as shown in FIG. 2 . Wherein, the excitation structure 1 can adopt a traditional saturation excitation structure, including but not limited to: static excitation, AC excitation, etc. As shown in FIG. 2 , the excitation structure 1 excites the wire rope to saturation or near saturation. The sensor 2 shown in FIG. 2 includes a magnetic flux detection sensor and a magnetic field strength detection sensor, wherein the magnetic flux detection sensor includes but is not limited to: a fluxgate sensor, an induction coil, and the like. As shown in FIG. 3 , the magnetic flux detection sensor 201 is located inside the detection device, and the magnetic flux detection includes but is not limited to: main magnetic flux, leakage magnetic flux, magnetic yoke magnetic flux, and the like. Magnetic field strength detection sensors include but are not limited to: Hall sensors, magnetoresistance sensors, giant magnetoresistance sensors, tunnel magnetoresistance sensors, and the like. As shown in FIG. 4 , the magnetic field intensity detection sensor array 202 is distributed on the surface of the steel wire rope, and the magnetic field intensity detection includes but is not limited to: three-dimensional magnetic field intensity in different directions. As shown in FIG. 5 , the signal acquisition and processing system includes a signal acquisition unit 301 , a signal preprocessing unit 302 , an eigenvalue calculation unit 303 and a defect section loss quantitative analysis unit 304 .

It can be understood that, in this embodiment, the magnetic flux signal of the tested wire rope can be obtained first through the magnetic flux detection sensor, and then the magnetic flux leakage signal of the tested wire rope can be obtained through the magnetic field intensity detection sensor, or the magnetic field intensity detection sensor can be used first. The sensor obtains the magnetic flux leakage signal of the tested wire rope, and then obtains the magnetic flux signal of the tested wire rope through the magnetic flux detection sensor, or obtains the magnetic flux signal of the tested wire rope through the magnetic flux detection sensor, and simultaneously obtains the magnetic flux signal of the tested wire rope through the magnetic flux detection sensor. The magnetic flux leakage signal of the tested steel wire rope is acquired, which is not limited in this embodiment.

Step S20, preprocessing the magnetic flux signal and magnetic flux leakage signal of the tested wire rope, obtaining the magnetic flux characteristic value of the defect of the tested wire rope according to the preprocessed magnetic flux signal, and obtaining the magnetic flux characteristic value of the tested wire rope defect according to the preprocessed magnetic flux signal. Obtain the magnetic flux leakage characteristic value of the tested wire rope defect.

In this embodiment, the step of preprocessing the magnetic flux signal of the tested wire rope includes: performing outlier elimination, noise filtering, and baseline removal on the magnetic flux signal of the tested wire rope.

The signal-to-noise ratio of the magnetic flux signal can be improved by performing outlier elimination, noise filtering, and baseline elimination on the magnetic flux signal of the tested wire rope, which is more conducive to signal feature extraction.

Specifically, the step of removing outliers for the magnetic flux signal of the tested wire rope includes:

Perform wild point elimination on the magnetic flux signal Y of the wire rope to be tested, and set Y(i) as the i-th magnetic flux acquisition signal, so there is △Y=|Y(i)-Y(i+1)|, where, △Y is the absolute value of the magnetic flux signal difference between two adjacent magnetic flux signal collection points; for any i, if there is △Y≤M, M is a preset threshold, where the preset threshold can be According to the sensitivity setting of the magnetic flux sensor, if there is a point Yi with: |Y(i)-Y(i-1)|>M, and |Y(i)-Y(i+1)|>M, then:

The signal Y ₁ (i) is obtained after the wild point elimination process.

The steps of performing noise filtering on the magnetic flux signal of the wire rope under test include:

Noise filtering is performed on the magnetic flux signal of the tested wire rope by using adaptive filtering or wavelet transform or smoothing filtering or empirical mode decomposition, wherein the smoothing filter is used to filter the magnetic flux signal of the tested wire rope. The formula for noise filtering for:

Among them, n in the formula is the number of data to be averaged, and N is the total number of sampling points.

It should be noted that, in this embodiment, performing noise filtering on the magnetic flux signal of the wire rope under test includes but is not limited to methods such as adaptive filtering, wavelet transform, smoothing filtering, or empirical mode decomposition.

The steps of performing baseline elimination on the magnetic flux signal of the tested wire rope include:

Use envelope spectrum extraction or wavelet decomposition or window average or empirical mode decomposition to perform baseline elimination on the magnetic flux signal of the tested steel wire rope, wherein, use empirical mode decomposition to perform baseline elimination on the magnetic flux signal of the tested steel wire rope The steps include:

Find out all the maximum and minimum points of the signal data sequence Y ₂ (i), and use the cubic spline function to fit them as the upper and lower envelopes of the original sequence; the upper envelope and the mean of the lower envelope is m1; subtracting m1 from the data sequence _Y2 (i) yields a new sequence _Y3 (i) minus the low frequency, that is, _Y3 (i)= _Y2 (i)-m1.

It should be noted that, in this embodiment, the method for baseline elimination of the magnetic flux signal of the wire rope under test includes, but is not limited to, envelope spectrum extraction, wavelet decomposition, window averaging, or empirical mode decomposition.

In this embodiment, for the preprocessed magnetic flux signal, the magnetic flux characteristic value of the defect can be obtained through the magnetic flux characteristic value analysis method, and the magnetic flux characteristic value at least includes the peak-to-peak value of each defect waveform of the tested wire rope , one or more of width, average value, area, and mean square error, and the step of obtaining the magnetic flux characteristic value of the tested wire rope defect according to the preprocessed magnetic flux signal includes:

Setting a preset threshold value, extracting sampling points greater than the preset threshold value, and the preset threshold value is obtained through the test of the actual minimum defect of the wire rope under test;

Specifically, the preset threshold can be set as an appropriate threshold according to the peak-to-peak value of the magnetic flux waveform of the minimum defect of the wire rope to be tested;

According to the position information of the extracted sampling points, N points are intercepted on the left and right of the waveform axis to obtain each defect waveform, where N is obtained through the test of the actual maximum defect of the tested wire rope;

Extract the peak-to-peak value, width, average value, area and mean square error of each defect waveform.

Further, in this embodiment, in step S20, the step of preprocessing the flux leakage signal of the wire rope under test includes:

Perform outlier elimination, noise filtering, baseline elimination, and strand wave noise filtering for each channel of magnetic flux leakage signal of the tested steel wire rope. Thereby, the signal-to-noise ratio of the flux leakage signal can be improved, which is more conducive to the feature extraction of the signal.

It can be understood that, in this embodiment, the magnetic flux leakage signal of the wire rope to be tested can be acquired by using a single-channel magnetic field strength detection sensor or a multi-channel magnetic field strength detection sensor array, which is convenient for subsequent signal processing or quantitative process expression. For example, a single magnetic sensor in the magnetic field intensity detection sensor array is one channel or one channel.

Specifically, in this embodiment, the step of removing outliers for each channel of magnetic flux leakage signal of the wire rope under test includes:

Perform wild point elimination for each channel of magnetic flux leakage signal X, and set X _i,j as the jth sampling value of the ith Hall sensor, so there is △X=|X _i,j —X _i,(j+1) | , where ΔX is the absolute value of the difference between two adjacent sampling values of the ith Hall sensor; for any i, j, if there is ΔX≤F, F is the preset threshold, where the preset threshold The threshold can be set according to the sensitivity of the magnetic flux leakage sensor, at this time:

The signal X _i,j is obtained after the outlier elimination process.

In the present embodiment, the step of performing noise filtering on each channel of magnetic flux leakage signal of the steel wire rope under test includes:

Adaptive filtering or wavelet transform or smoothing filtering or empirical mode decomposition is used to perform noise filtering on each channel of magnetic flux leakage signal of the tested wire rope; wherein, smoothing filtering is used to filter the noise of each channel of magnetic flux leakage signal of the tested wire rope. The calculation formula is:

Among them, n is the number of data for averaging, N is the total number of sampling points, and k is the number of magnetic field intensity detection sensors that collect the flux leakage signal of the wire rope under test.

It can be understood that, in this embodiment, the method for performing noise filtering on each channel of magnetic flux leakage signal of the wire rope under test includes but is not limited to methods such as adaptive filtering, wavelet transform, smooth filtering, or empirical mode decomposition. Not limited.

In the present embodiment, the steps of performing baseline elimination on each channel of magnetic flux leakage signal of the steel wire rope under test include:

Envelope spectrum extraction or wavelet decomposition or window average or empirical mode decomposition is used to perform baseline elimination on the MFL signal of each channel of the tested wire rope; wherein, the empirical mode decomposition is used to analyze the MFL signal of each channel of the tested wire rope. The steps for signal baseline cancellation include:

Find out all the maximum and minimum points of the original magnetic flux leakage signal data sequence X, and use the cubic spline function to fit them into the upper and lower envelopes of the original sequence, the upper envelope and The mean value of the lower envelope is m1; subtract m1 from the original data sequence to obtain a new sequence X ₁ minus the low frequency, that is, X ₁ =X-m1.

It can be understood that, in this embodiment, the method for removing the baseline of each MFL signal of the wire rope under test includes but is not limited to methods such as envelope spectrum extraction, wavelet decomposition, window averaging, or empirical mode decomposition. The invention is not limited to this.

In the present embodiment, the step of filtering out the strand noise of each channel of magnetic flux leakage signal of the steel wire rope under test includes:

Wavelet decomposition or empirical mode decomposition or adaptive filtering or gradient method is used to filter out the stray wave noise of each magnetic flux leakage signal of the tested wire rope, wherein the gradient method is used to The steps of filtering the signal to the wave noise include:

The gradient method is used to realize the first-order differentiation of the image. For the image X ₁ (x, y), its gradient at the coordinate (x, y) is represented by a two-dimensional column vector:

The modulus of this vector is:

The multi-channel flux leakage signal is summed to obtain the flux leakage sum signal X2.

It can be understood that, in this embodiment, the method for filtering the strand noise of each channel of the flux leakage signal of the wire rope under test includes but is not limited to wavelet decomposition or empirical mode decomposition or adaptive filtering or gradient method. The invention is not limited to this.

In this embodiment, for the preprocessed magnetic flux leakage signal, the magnetic flux leakage characteristic value of the defect can be obtained by using the magnetic flux leakage characteristic value analysis method, and the magnetic flux leakage characteristic value of the tested wire rope at least includes each The peak-to-peak value, width, average value, area, and mean square error of the defect waveform.

Specifically, the step of obtaining the magnetic flux leakage characteristic value of the tested wire rope defect according to the preprocessed magnetic flux leakage signal includes:

The local maximum value method is used to locate the defect, and a preset threshold is set to determine whether it is a defect, wherein the preset threshold is obtained by testing the actual minimum defect of the wire rope;

Taking the found defect position as the center point, intercept L points on the left and right of the waveform axis to obtain each defect waveform, where L is obtained through the test of the actual wire rope maximum defect;

Extract the peak-to-peak value, width, average value, area, and mean square error of each defect waveform of the tested wire rope.

Specifically, in this embodiment, an appropriate preset threshold can be set according to the peak-to-peak value of the flux leakage waveform of the minimum defect of the wire rope to be tested. When the local maximum point of the collected magnetic flux signal is greater than or equal to the preset threshold, it is determined that this is a defect, Among them, the method of local maxima is to obtain local maxima by comparing the collected point fields.

In step S30, the defect width of the tested wire rope is obtained according to the characteristic value of the magnetic flux and the characteristic value of the magnetic flux leakage.

After the magnetic flux characteristic value and the magnetic flux leakage characteristic value are obtained, the defect width of the tested wire rope can be obtained according to the magnetic flux characteristic value and the magnetic leakage characteristic value.

Specifically, the step of obtaining the defect width of the tested wire rope according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value includes:

Input the waveform width, waveform area and the waveform width and waveform area of the magnetic flux characteristic value into the defect width calculation equation or neural network to obtain the defect width of the tested wire rope.

Among them, a simple calculation method is: obtain the waveform width SW of the magnetic flux characteristic value, the waveform width FW of the magnetic flux leakage characteristic value, and the lift-off DL of the magnetic flux leakage sensor, and the defect width W=(SW+FW-DL)/ 2. If a more accurate defect width needs to be obtained, calculation equations or neural networks can be obtained by testing several standard defect samples or by simulation.

Step S40, comparing the defect width of the tested wire rope with a preset width threshold.

If the defect width of the tested wire rope is greater than or equal to the preset width threshold, the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope defect.

Specifically, if the defect width of the tested wire rope is greater than or equal to the preset width threshold, the peak-to-peak value of the waveform, the waveform area, the waveform average value, and the waveform mean square error in the magnetic flux characteristic value are input into the loss of the defect section The magnetic flux calculation equation or neural network is used to obtain the section loss of the tested wire rope defect.

Wherein, the preset width threshold can be obtained by subtracting the length of the excitation probe and the width of the excitation magnetic pole.

Among them, a simple calculation method is: to obtain the peak-to-peak value VPP of the waveform in the characteristic value of the magnetic flux, the section loss of the tested wire rope defect LS=k1×VPP+LB1, where k1 and LB1 pass the test of several standard defects samples or simulations.

If the defect width of the tested wire rope is smaller than the preset width threshold, the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value of the defect of the tested wire rope.

Specifically, if the defect width of the tested steel wire rope is smaller than the preset width threshold, the peak-to-peak value of the waveform, the waveform area, the waveform average value, the waveform mean square error and the magnetic flux leakage feature value in the magnetic flux characteristic value are determined. The peak-to-peak value of the waveform, the waveform area, the average value of the waveform, and the mean square deviation of the waveform are input into the calculation equation or neural network for the loss of the defect section, and the section loss of the tested wire rope is obtained.

Among them, a simple calculation method: obtain the waveform peak-to-peak value SVPP in the magnetic flux characteristic value, the waveform peak-to-peak value FVPP in the magnetic flux leakage characteristic, and the cross-sectional loss of the defect LS=k2×(SVPP+FVPP×s)+LB2, Among them, k2, s and LB2 are obtained by testing several standard defect samples or by simulation.

The beneficial effect of the non-destructive testing method of the steel wire rope of the present invention is that the present invention obtains the magnetic flux signal of the steel wire rope under test through the magnetic flux detection sensor through the above technical scheme, and obtains the magnetic flux leakage signal of the steel wire rope under test through the magnetic field strength detection sensor; The magnetic flux signal and magnetic flux leakage signal of the tested wire rope are preprocessed, and the magnetic flux characteristic value of the tested wire rope defect is obtained according to the preprocessed magnetic flux signal, and the tested wire rope defect is obtained according to the preprocessed magnetic flux leakage signal. The magnetic flux leakage characteristic value of the defect of the wire rope; obtain the defect width of the tested wire rope according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value; compare the defect width of the tested wire rope with the preset width threshold; if The defect width of the tested wire rope is greater than or equal to the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope defect; The defect width is less than the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value of the tested wire rope defect. Combined with the magnetic flux detection and the magnetic flux leakage detection, not only It can identify all types of defects in the tested wire rope, and has the advantages of high cross-section loss quantitative accuracy, simple quantitative method, and no need for complex calculation methods or training fitting samples.

In order to achieve the above purpose, the present invention also proposes a wire rope non-destructive testing device, please refer to FIGS. 2 to 5 again. As shown in FIGS. 2 to 5 , the wire rope non-destructive testing device of the present invention includes an excitation structure 1 as shown in FIG. 2 . , sensor 2, signal acquisition and processing system 3. Wherein, the excitation structure 1 can adopt a traditional saturation excitation structure, including but not limited to: static excitation, AC excitation, etc. As shown in FIG. 2 , the excitation structure 1 excites the wire rope to saturation or near saturation. The sensor 2 shown in FIG. 2 includes a magnetic flux detection sensor and a magnetic field strength detection sensor, wherein the magnetic flux detection sensor includes but is not limited to: a fluxgate sensor, an induction coil, and the like. As shown in FIG. 3 , the magnetic flux detection sensor 201 is located inside the detection device, and the magnetic flux detection includes but is not limited to: main magnetic flux, leakage magnetic flux, magnetic yoke magnetic flux, and the like. Magnetic field strength detection sensors include but are not limited to: Hall sensors, magnetoresistance sensors, giant magnetoresistance sensors, tunnel magnetoresistance sensors, and the like. As shown in FIG. 4 , the magnetic field intensity detection sensor array 202 is distributed on the surface of the steel wire rope, and the magnetic field intensity detection includes but is not limited to: three-dimensional magnetic field intensity in different directions. As shown in FIG. 5 , the signal acquisition and processing system includes a signal acquisition unit 301 , a signal preprocessing unit 302 , an eigenvalue calculation unit 303 and a defect section loss quantitative analysis unit 304 .

Wherein, the magnetic flux detection sensor is used to obtain the magnetic flux signal of the steel wire rope under test, and the magnetic field strength detection sensor is used to obtain the magnetic flux leakage signal of the steel wire rope under test;

The signal acquisition and processing system includes a signal acquisition unit, a signal preprocessing unit, a eigenvalue calculation unit, and a defect section loss quantitative analysis unit, wherein,

The signal preprocessing unit is used for preprocessing the magnetic flux signal and the magnetic flux leakage signal of the wire rope under test;

The characteristic value calculation unit is used to obtain the magnetic flux characteristic value of the tested wire rope defect according to the preprocessed magnetic flux signal, and obtain the magnetic flux leakage characteristic value of the tested wire rope defect according to the preprocessed magnetic flux leakage signal;

The defect section loss quantitative analysis unit is used to obtain the defect width of the tested wire rope according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value;

The defect section loss quantitative analysis unit is further configured to compare the defect width of the tested wire rope with a preset width threshold;

If the defect width of the tested wire rope is greater than or equal to the preset width threshold, then the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value of the tested wire rope defect;

If the defect width of the tested wire rope is smaller than the preset width threshold, the cross-sectional loss of the tested wire rope is obtained according to the magnetic flux characteristic value and the magnetic flux leakage characteristic value of the defect of the tested wire rope.

The beneficial effects of the wire rope non-destructive testing device of the present invention are: the wire rope non-destructive testing device of the present invention combines magnetic flux detection and magnetic flux leakage detection, not only can identify all types of defects of the tested wire rope, but also has high quantitative accuracy of cross-section loss, the quantitative method is simple, and does not Requires the advantage of complex computational methods or training fitted samples.

The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the protection of the present invention. within the range.

Claims (10)

1. A nondestructive testing method for a steel wire rope is characterized by comprising the following steps:

step S10, acquiring a magnetic flux signal of the steel wire rope to be detected through a magnetic flux detection sensor, and acquiring a magnetic leakage signal of the steel wire rope to be detected through a magnetic field intensity detection sensor;

step S20, preprocessing the magnetic flux signal and the magnetic flux leakage signal of the detected steel wire rope, obtaining the magnetic flux characteristic value of the defect of the detected steel wire rope according to the preprocessed magnetic flux signal, and obtaining the magnetic flux leakage characteristic value of the defect of the detected steel wire rope according to the preprocessed magnetic flux leakage signal;

step S30, obtaining the defect width of the tested steel wire rope according to the magnetic flux characteristic value and the magnetic leakage characteristic value;

step S40, comparing the defect width of the detected steel wire rope with a preset width threshold value;

if the defect width of the steel wire rope to be detected is larger than or equal to the preset width threshold value, obtaining the section loss of the steel wire rope to be detected according to the magnetic flux characteristic value of the defect of the steel wire rope to be detected;

and if the defect width of the detected steel wire rope is smaller than the preset width threshold, obtaining the section loss of the detected steel wire rope according to the magnetic flux characteristic value and the magnetic leakage characteristic value of the defect of the detected steel wire rope.

2. The nondestructive testing method for the steel wire rope according to claim 1, wherein the step of preprocessing the magnetic flux signal of the steel wire rope to be tested in step S20 includes:

carrying out outlier rejection, noise filtering and baseline elimination on the magnetic flux signal of the steel wire rope to be detected;

the step of removing the wild points of the magnetic flux signals of the detected steel wire rope comprises the following steps:

removing wild points of the magnetic flux signal Y of the steel wire rope to be detected, and setting Y (i) as the ith magnetic flux acquisition signal, so that a difference value of Delta Y ═ Y (i) to Y (i +1) |, wherein the Delta Y is the absolute value of the difference value of the magnetic flux signals of two adjacent magnetic flux signal acquisition points; for any i, if Δ Y is less than or equal to M, M is a preset threshold, and if the point Yi exists: y (i) -Y (i-1) | > M, and Y (i) -Y (i +1) | > M, when:

obtaining a signal Y after the wild point elimination processing₁(i)；

The step of carrying out noise filtering on the magnetic flux signal of the steel wire rope to be detected comprises the following steps:

and performing noise filtering on the magnetic flux signal of the steel wire rope to be detected by adopting self-adaptive filtering, wavelet transformation, smoothing filtering or empirical mode decomposition, wherein a calculation formula for performing noise filtering on the magnetic flux signal of the steel wire rope to be detected by adopting smoothing filtering is as follows:

wherein N is the number of data for averaging, and N is the total number of sampling points;

the step of eliminating the magnetic flux signal of the tested steel wire rope by the base line comprises the following steps:

performing baseline elimination on the magnetic flux signal of the steel wire rope to be detected by adopting envelope spectrum extraction or wavelet decomposition or window averaging or empirical mode decomposition, wherein the step of performing baseline elimination on the magnetic flux signal of the steel wire rope to be detected by adopting empirical mode decomposition comprises the following steps of:

finding the signal data sequence Y₂(i) Fitting all the maximum value points and minimum value points to an upper envelope line and a lower envelope line of the original sequence by a cubic spline function respectively; the mean value of the upper envelope curve and the lower envelope curve is m 1; data sequence Y₂(i) Subtracting m1 to obtain a new sequence Y with low frequency subtracted₃(i)，I.e. Y₃(i)＝Y₂(i)－m1。

3. The nondestructive testing method for the steel wire rope according to claim 2, wherein the magnetic flux characteristic value at least includes one or more of a peak-to-peak value, a width, an average value, an area and a mean square error of each defect waveform of the steel wire rope to be tested, and the step of obtaining the magnetic flux characteristic value of the defect of the steel wire rope to be tested according to the preprocessed magnetic flux signal includes:

setting a preset threshold value, and extracting sampling points larger than the preset threshold value, wherein the preset threshold value is obtained through the test of the minimum defect of the actually tested steel wire rope;

according to the extracted sampling point position information, intercepting N points on the left and right of the waveform axial direction to obtain each defect waveform, wherein N is obtained through the test of the maximum defect of the actually tested steel wire rope;

and extracting the peak value, the width, the average value, the area and the mean square error of each defect waveform.

4. The steel wire rope nondestructive testing method according to claim 1, wherein in step S20, the step of preprocessing the magnetic leakage signal of the steel wire rope to be tested comprises:

performing outlier rejection, noise filtering, baseline elimination and strand noise filtering on each path of magnetic flux leakage signals of the steel wire rope to be detected;

the step of eliminating the magnetic leakage signals of each path of the detected steel wire rope comprises the following steps:

eliminating the wild points of each path of magnetic leakage signal X, and setting X_i,jIs the jth sampled value of the ith Hall sensor, so that Δ X ═ X_i,j—X_i,(j+1)The absolute value of the difference between two adjacent sampling values of the ith Hall sensor is delta X; if any i, j has a value of DeltaX less than or equal to F, F is a preset threshold value, and then:

obtaining a signal X after the outlier rejection_i,j；

The step of carrying out noise filtering on each path of leakage magnetic signal of the tested steel wire rope comprises the following steps:

each path of magnetic leakage signal of the steel wire rope to be tested is subjected to noise filtering by adopting self-adaptive filtering or wavelet transformation or smoothing filtering or empirical mode decomposition; the calculation formula for carrying out noise filtering on each path of magnetic leakage signal of the detected steel wire rope by adopting smooth filtering is as follows:

wherein N is the number of data for averaging, N is the number of total sampling points, and k is the number of magnetic field intensity detection sensor paths for collecting the magnetic leakage signal of the steel wire rope to be detected;

the step of eliminating the baseline of each path of magnetic leakage signal of the tested steel wire rope comprises the following steps:

performing baseline elimination on each path of magnetic flux leakage signal of the steel wire rope to be detected by adopting envelope spectrum extraction or wavelet decomposition or window averaging or empirical mode decomposition; the step of eliminating the baseline of each path of magnetic leakage signal of the tested steel wire rope by adopting empirical mode decomposition comprises the following steps:

finding out all maximum value points and minimum value points of the original magnetic leakage signal data sequence X, and respectively fitting the maximum value points and minimum value points into an upper envelope line and a lower envelope line of the original sequence by using a cubic spline function, wherein the mean value of the upper envelope line and the lower envelope line is m 1; subtracting m1 from the original data sequence to obtain a new sequence X with low frequency subtracted₁I.e. X₁＝X－m1；

The step of filtering the strand wave noise of each path of magnetic leakage signal of the tested steel wire rope comprises the following steps:

adopt wavelet decomposition or empirical mode decomposition or adaptive filtering or gradient method to be right every way magnetic leakage signal of being surveyed wire rope carries out the spike noise filtering, wherein, adopt the gradient method right every way magnetic leakage signal of being surveyed wire rope carries out the step that the spike noise filtering includes:

using gradient method to realize first order differentiation of image, for image X₁(x, y) whose gradient at coordinate (x, y) is a two-dimensional column vector representation:

the modulus of this vector is:

and summing the multipath magnetic leakage signals to obtain a magnetic leakage sum signal X2.

5. The method according to claim 4, wherein in step S20, the leakage magnetic characteristic values of the steel wire rope to be tested at least include peak-to-peak values, widths, average values, areas and mean square deviations of each defect waveform of the steel wire rope to be tested, and the step of obtaining the leakage magnetic characteristic values of the defects of the steel wire rope to be tested according to the preprocessed leakage magnetic signals includes:

the method comprises the steps of positioning defects by adopting a local maximum value method, and setting a preset threshold value to judge whether the defect is detected, wherein the preset threshold value is obtained through testing of the minimum defect of the actual steel wire rope;

taking the found defect position as a central point, intercepting L points on the left and right sides of the axial direction of the waveform to obtain each defect waveform, wherein L is obtained through the test of the maximum defect of the actual steel wire rope;

and extracting the peak value, the width, the average value, the area and the mean square error of each defect waveform of the detected steel wire rope.

6. The steel wire rope nondestructive testing method according to claim 1, wherein in step S30, the step of obtaining the defect width of the steel wire rope to be tested from the magnetic flux characteristic value and the magnetic leakage characteristic value includes:

and inputting the waveform width and the waveform area in the magnetic flux characteristic value and the waveform width and the waveform area of the magnetic flux leakage characteristic value into a defect width calculation equation or a neural network to obtain the defect width of the detected steel wire rope.

7. The method according to claim 1, wherein in step S40, if the defect width of the steel wire rope to be tested is greater than or equal to the preset width threshold, the step of obtaining the cross-sectional loss amount of the steel wire rope to be tested according to the magnetic flux characteristic value of the steel wire rope to be tested comprises:

and if the defect width of the detected steel wire rope is larger than or equal to the preset width threshold, inputting a waveform peak value, a waveform area, a waveform average value and a waveform mean square error in the magnetic flux characteristic value into a defect section loss quantity magnetic flux calculation equation or a neural network to obtain the section loss quantity of the detected steel wire rope defect.

8. The method according to claim 1, wherein in step S40, if the defect width of the steel wire rope to be tested is smaller than the preset width threshold, the step of obtaining the cross-section loss amount of the steel wire rope to be tested according to the magnetic flux characteristic value and the magnetic leakage characteristic value of the steel wire rope to be tested comprises:

and if the defect width of the steel wire rope to be detected is smaller than the preset width threshold, inputting a waveform peak value, a waveform area, a waveform average value, a waveform mean square error and a waveform peak value, a waveform area, a waveform average value and a waveform mean square error in the magnetic flux characteristic value into a defect section loss quantity calculation equation or a neural network to obtain the section loss quantity of the steel wire rope to be detected.

9. A steel wire rope nondestructive testing device is characterized by comprising a magnetic flux detection sensor, a magnetic field intensity detection sensor and a signal acquisition and processing system, wherein,

the magnetic flux detection sensor is used for acquiring a magnetic flux signal of the steel wire rope to be detected, and the magnetic field intensity detection sensor is used for acquiring a magnetic leakage signal of the steel wire rope to be detected;

the signal acquisition and processing system comprises a signal acquisition unit, a signal preprocessing unit, a characteristic value calculating unit and a defect section loss quantitative analysis unit, wherein,

the signal preprocessing unit is used for preprocessing the magnetic flux signal and the magnetic leakage signal of the steel wire rope to be detected;

the characteristic value calculating unit is used for obtaining a magnetic flux characteristic value of the detected steel wire rope defect according to the preprocessed magnetic flux signal and obtaining a magnetic leakage characteristic value of the detected steel wire rope defect according to the preprocessed magnetic leakage signal;

the defect section loss quantitative analysis unit is used for obtaining the defect width of the steel wire rope to be detected according to the magnetic flux characteristic value and the magnetic leakage characteristic value;

the defect section loss quantitative analysis unit is also used for comparing the defect width of the detected steel wire rope with a preset width threshold value;

if the defect width of the steel wire rope to be detected is larger than or equal to the preset width threshold value, obtaining the section loss of the steel wire rope to be detected according to the magnetic flux characteristic value of the defect of the steel wire rope to be detected;

and if the defect width of the detected steel wire rope is smaller than the preset width threshold, obtaining the section loss of the detected steel wire rope according to the magnetic flux characteristic value and the magnetic leakage characteristic value of the detected steel wire rope defect.

10. The nondestructive testing device for steel wire rope according to claim 9, further comprising an excitation structure for exciting the steel wire rope to be tested to saturation or near saturation.

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