CN107941899B - Weak magnetic excitation steel wire rope flaw detection device and flaw detection method - Google Patents
Weak magnetic excitation steel wire rope flaw detection device and flaw detection method Download PDFInfo
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- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
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- G01N27/82—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
- G01N27/83—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws by investigating stray magnetic fields
Abstract
The invention provides a weak magnetic excitation steel wire rope flaw detection device and a flaw detection method, wherein the steel wire rope flaw detection device comprises an excitation part and a magnetic leakage signal detection part which are arranged in a split manner; the excitation part comprises two excitation units which are respectively used for being arranged at two ends of the steel wire rope to be tested; the magnetic leakage signal detection part is provided with a detection channel for the steel wire rope to be detected to pass through and move along the steel wire rope, and the detection channel is provided with a first set number of magnetic induction sensors. According to the technical scheme provided by the invention, the excitation part and the magnetic leakage signal detection part are arranged in a split manner, when the steel wire rope needs to be detected, the excitation units of the two excitation parts are respectively arranged at the two ends of the steel wire rope to be detected, the excitation units do not need to be moved, and the steel wire rope can be detected only by moving the magnetic leakage signal detection part, so that the problem that the steel wire rope flaw detection device is inconvenient to use due to high quality is solved.
Description
Technical Field
The invention belongs to the technical field of steel wire rope flaw detection, and particularly relates to a weak magnetic excitation steel wire rope flaw detection device and a flaw detection method.
Background
Industrial production, tourism, coal mining, marine and everyday hoisting and hoisting usually use steel wire ropes as traction, load-bearing and connecting parts. The steel wire rope is easy to break, loosen and wear and damage after being used under a large load for a long time, and the steel wire rope is corroded and shrunk and has reduced bearing capacity when being used under a severe environment, so that safety accidents are easy to happen, and personal safety and equipment safety are endangered. Therefore, the technology for realizing the rapid nondestructive automatic detection of the steel wire rope by monitoring the damage condition of the steel wire rope in real time and predicting the damage condition of the steel wire rope has important social and economic benefits.
At present, the technical field of steel wire rope damage detection is applied more, and the most common method is an electromagnetic detection method. Electromagnetic-based nondestructive testing of wire ropes can be roughly classified into two types from the magnetization angle, namely coil magnetization and permanent magnet excitation magnetization. The coil magnetization detection device is usually used for winding the coil into two saddle-shaped coils, and different magnetic field strengths are generated by adjusting the current in the coils. Meanwhile, the magnetic flux leakage on the surface of the steel wire rope is collected by a main flux method or a fluxgate, so that the quantitative detection of the position and the damage condition of the surface damage can be basically realized. However, the method adopts a circumferential magnetic field addition mode to acquire one-dimensional signals, so that circumferential magnetic field distribution signals are inevitably lacked, and the method has great influence on detection and identification of concentrated defects and dispersed defects.
Most of detection devices using permanent magnets as excitation sources adopt a large number of magnets to be manufactured into a saddle shape, then magnetizers are used for carrying out magnetism gathering to magnetize the steel wire rope to saturation, and when the steel wire rope is damaged, a leakage magnetic field is generated at the damaged part, as shown in fig. 1. When the test method is used for testing, the test device needs to move back and forth along the steel wire rope to be tested, but the used test device usually comprises a permanent magnet serving as an excitation source and a detection device for detecting a leakage magnetic signal, and the permanent magnet has larger mass, so that the excitation device is heavy and inconvenient to use.
Disclosure of Invention
The invention provides a weak magnetic excitation steel wire rope flaw detection device and a flaw detection method, which are used for solving the problem that the steel wire rope flaw detection device is inconvenient to use due to large mass.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
device scheme 1: a weak magnetic excitation wire rope flaw detection device comprises an excitation part and a magnetic leakage signal detection part which are arranged in a split mode;
the excitation part comprises two excitation units which are respectively used for being arranged at two ends of the steel wire rope to be tested; the magnetic leakage signal detection part is provided with a detection channel for the steel wire rope to be detected to pass through and move along the steel wire rope, and the detection channel is provided with a first set number of magnetic induction sensors.
According to the technical scheme provided by the invention, the excitation part and the magnetic leakage signal detection part are arranged in a split manner, when the steel wire rope needs to be detected, the excitation units of the two excitation parts are respectively arranged at the two ends of the steel wire rope to be detected, the excitation units do not need to be moved, and the steel wire rope can be detected only by moving the magnetic leakage signal detection part, so that the problem that the steel wire rope flaw detection device is inconvenient to use due to high quality is solved.
Device scheme 2: on the basis of the device scheme 1, the magnetic flux leakage detection device further comprises a main control module, and the main control module is connected with the output ends of the magnetic induction sensors in the magnetic flux leakage signal detection part.
The main control module is arranged, so that detected data can be processed in time, and a detection result is obtained.
Device scheme 3: on the basis of the device scheme 1 or 2, each excitation unit comprises a second set number of magnetic elements, wherein the N poles of the magnetic elements in the first magnetic unit are in the same direction or point to the same point, and the S poles of the magnetic elements in the second excitation unit are in the same direction or point to the same point.
Device scheme 4: in the device according to claim 3, the magnetic element in each of the excitation units is a permanent magnet or an excitation coil.
Device scheme 5: on the basis of the device scheme 1 or 2, a detection ring is arranged on the detection channel, and each magnetic induction sensor is arranged on the detection ring along the axial direction of the detection channel.
Device scheme 6: on the basis of the device scheme 2, the device further comprises a signal conditioning module, wherein the signal conditioning module comprises a differential signal amplifying circuit and an analog-to-digital conversion circuit, the input end of the differential signal amplifying circuit is connected with the output end of each magnetic induction sensor, and the output end of the differential signal amplifying circuit is connected with the input end of the analog-to-digital conversion circuit; the main control module is connected with the output end of the analog-to-digital conversion circuit.
Apparatus, scheme 7: on the basis of the device scheme 6, the signal conditioning module further comprises an addition baseline lifting circuit, wherein the input end of the addition baseline lifting circuit is connected with the output end of the analog-to-digital conversion circuit, and the output end of the addition baseline lifting circuit is connected with the main control module.
Device scheme 8: on the basis of the device scheme 2, the device also comprises a pulse generation module, wherein the pulse generation module comprises a photoelectric encoder and a photoelectric encoder detection circuit, and the photoelectric encoder is used for sending out a pulse signal; the input end of the photoelectric encoder detection circuit is connected with the output end of the photoelectric encoder, and the main control module is connected with the output end of the photoelectric encoder detection circuit.
Device scheme 9: on the basis of the device scheme 8, the photoelectric encoder detection circuit comprises a photoelectric coupler and a signal shaping circuit, wherein the input end of the photoelectric coupler is connected with the photoelectric encoder, and the output end of the photoelectric coupler is connected with the signal shaping circuit; the main control module is connected with the output end of the signal shaping circuit, and the shaping circuit is used for shaping the rising edge and the falling edge of the pulse signal sent by the photoelectric encoder.
The photoelectric coupler and the shaping circuit are arranged, so that the rising edge and the falling edge of the pulse can become steep, and the pulse shaping circuit has a shaping effect on the pulse signal. Thereby obtaining a pulse signal for eliminating the interference of the digital signal.
Device scheme 10: on the basis of the device scheme 2, the main control module is also connected with a display module.
Apparatus scheme 11: on the basis of the device scheme 2, the main control module comprises an ARM chip and an FPGA chip, and the ARM chip is connected with each magnetic induction sensor in the magnetic leakage signal detection part.
Apparatus scheme 12: on the basis of the device scheme 2 or 11, the main control module is also connected with a data storage module.
The method comprises the following steps: a weak magnetic excitation steel wire rope flaw detection method comprises the following steps:
(1) arranging the N pole of the magnetic element in the first excitation unit at one end of the steel wire rope to be tested, and arranging the S pole of the magnetic element in the second excitation unit at the other end of the steel wire rope to be tested;
(2) carrying out magnetic field detection on the surface of the steel wire rope to be detected by adopting a magnetic leakage signal detection part to obtain magnetic field data of the surface of the steel wire rope to be detected;
(3) performing baseline removal processing and noise reduction processing on the magnetic field data on the surface of the steel wire rope to be detected, and converting the processed data into a magnetic field gray image of the surface of the steel wire rope to be detected;
(4) performing super-resolution reconstruction on the magnetic field gray image on the surface of the steel wire rope to be detected to improve the resolution;
(5) and extracting the characteristic quantity of the magnetic field gray level image on the surface of the steel wire rope to be detected, inputting the characteristic quantity into an artificial neural network for quantitative identification, and judging whether the steel wire rope to be detected has a breakpoint.
Drawings
FIG. 1 is a schematic diagram of a wire rope damage detection in the prior art;
FIG. 2 is a schematic structural diagram of a weak magnetic excitation wire rope flaw detection device in an embodiment;
FIG. 3 is a diagram showing a distribution of magnets in an exciting unit in the embodiment;
fig. 4 is a schematic structural diagram of a leakage magnetic signal detection module in the embodiment;
FIG. 5 is a circuit diagram showing the structure of a signal conditioning section in the embodiment;
FIG. 6 is a schematic diagram of a pulse signal detection circuit according to an embodiment;
FIG. 7 is a schematic diagram of a main control module in an embodiment;
FIG. 8 is a schematic diagram of an embodiment of detection by a weak magnetic excitation wire rope flaw detector;
FIG. 9 is a flow chart of the detection of the weak magnetic excitation wire rope flaw detector in the embodiment.
Detailed Description
The invention provides a weak magnetic excitation steel wire rope flaw detection device and a flaw detection method, which are used for solving the problem that the steel wire rope flaw detection device is inconvenient to use due to large mass.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
a weak magnetic excitation wire rope flaw detection device comprises an excitation part and a magnetic leakage signal detection part which are arranged in a split mode;
the excitation part comprises two excitation units which are respectively used for being arranged at two ends of the steel wire rope to be tested; the magnetic leakage signal detection part is provided with a detection channel for the steel wire rope to be detected to pass through and move along the steel wire rope, and the detection channel is provided with a first set number of magnetic induction sensors.
The technical solution of the present invention will be further described with reference to specific embodiments.
The embodiment provides a weak magnetic excitation wire rope flaw detection device, which is used for solving the problem of inconvenient use caused by overlarge mass of the flaw detection device when the wire rope flaw is detected.
The weak magnetic excitation wire rope flaw detector provided by the present embodiment has a structural principle as shown in fig. 2, and includes a main control section 107, a leakage magnetic signal detection section 102, a signal conditioning section 103, a pulse signal generation and detection section 105, a data storage section 104, a display section 106, and an excitation section 101.
The excitation portion 101 includes two excitation units each provided with n magnetic elements, which in this embodiment are permanent magnets. The structure of each excitation unit in the first excitation unit is shown as a in fig. 3, each permanent magnet is arranged in a ring shape, and the N pole of each permanent magnet points to the center of the ring; each of the second excitation units has a configuration in which, as shown in b in fig. 3, each permanent magnet is arranged in a ring shape, and the S pole of each permanent magnet is directed to the center of the ring.
The leakage magnetic signal detection module 102 includes a detection channel 1021, and a detection ring 1022 is disposed on the detection channel, as shown in fig. 4, the detection ring 1022 includes 18 giant magnetoresistance sensors, and each giant magnetoresistance sensor is circumferentially and uniformly disposed around an axis of the detection channel 1021 at the detection ring.
The signal conditioning section 103 includes an analog-to-digital conversion circuit 201, a differential signal amplification circuit 202, and a summing baseline boost circuit 203, as shown in fig. 5. The input end of the differential signal amplifying circuit 202 is connected to the corresponding giant magnetoresistance sensor in the leakage magnetic signal detection module 102, and the output end is connected to the input end of the analog-to-digital conversion circuit 201; the output end of the analog-to-digital conversion circuit 201 is connected with the input end of the addition baseline lifting circuit 203, and the output end is connected with the main control unit 107.
The pulse signal generating and detecting part 105 includes a grating encoder and a pulse signal detecting circuit, an output end of the grating encoder is connected with an input end of the pulse signal detecting circuit, and the main control unit 107 is connected with an output end of the pulse signal detecting circuit. The pulse signal detection circuit is shown in fig. 6, and includes a photocoupler, in which the primary side of the photocoupler is connected to the input terminal of the pulse signal detection circuit, and the secondary side of the photocoupler is connected to a shaping circuit formed by an RC low-pass filter and two chips 74HC14M connected in series.
The main control unit 107 has a structure shown in fig. 7, and includes an ARM chip and an FPGA chip, which are connected to each other, wherein the ARM chip is connected to the signal conditioning part 103, the pulse signal generating and detecting part 105, and the data storage unit 104, and the FPGA chip is connected to the display module 106.
The weak magnetic excitation steel wire rope flaw detection device provided by the embodiment comprises the following steps of:
firstly, building a test environment; as shown in fig. 8, a first excitation unit and a second excitation unit of an excitation unit 101 are respectively arranged at two ends of a steel wire rope to be measured, so that one end of the steel wire rope is positioned at the center of a circle pointed by the N pole of each permanent magnet in the first excitation unit, and the other end of the steel wire rope is positioned at the center of a circle pointed by the S pole of each permanent magnet in the second excitation unit, and a weak magnetic excitation field is applied to the steel wire rope to be measured, so that the steel wire rope to be measured is magnetized under the action of the weak magnetic field; the number n of the permanent magnets in each excitation unit is determined according to the length of the steel wire rope to be tested, and the longer the steel wire rope to be tested is, the more permanent magnets are arranged in each excitation unit;
the steel wire rope to be detected passes through a detection channel 1021 of the magnetic leakage signal detection module 102, so that the giant magnetoresistance sensors in the magnetic leakage signal detection module 102 are uniformly distributed in the circumferential direction of the steel wire rope to be detected; controlling the magnetic leakage signal detection module 102 to move along the extending direction of the steel wire rope, and simultaneously rotating the photoelectric encoder to enable the photoelectric encoder to generate pulse signals with the quantity corresponding to the moving distance of the magnetic leakage signal detection module 102 along the extending direction of the steel wire rope;
the giant magnetoresistance sensors in the leakage magnetic signal detection module 102 detect the alternate gating, collect the magnetic field signal of the circumferential direction of the steel wire rope to be detected, and send the magnetic field signal to the differential signal amplifying part 202; the differential signal amplification part 202 amplifies the received magnetic field signal and then transmits the amplified magnetic field signal to the analog-to-digital conversion circuit 201; the analog-to-digital conversion circuit 201 converts the received amplified magnetic field signal into a digital signal, and sends the digital signal to the FPGA chip in the main control module 107 through the addition baseline-raising circuit, the FPGA chip processes the received digital signal, the flow of the processing method is shown in fig. 9, and the steps are as follows:
(1) performing baseline removal processing and noise reduction processing on the magnetic field signal data on the surface of the steel wire rope to be detected, and converting the processed data into a magnetic field gray image of the surface of the steel wire rope to be detected;
the method comprises the following steps of carrying out noise reduction processing on magnetic field signal data on the surface of a steel wire rope to be detected, and adopting a wavelet soft threshold denoising algorithm based on empirical mode decomposition, wherein the wavelet soft threshold denoising algorithm specifically comprises the following steps:
step 1: carrying out mirror symmetry boundary extension on the magnetic field signal data of the surface of the steel wire rope to be detected to obtain a processed signal
Initialization
Wherein c isiObtaining an inherent modal function finally by empirical mode decomposition;
step 2: using a formula
y (t) is the semaphore after adding noise, namely the function to be decomposed;
for residue rnAdding a Gaussian white noise sequence w (t);
and step 3: using a formula
Decomposing y (t) to obtain c meeting the requirement of inherent modal componentijAnd a residual amount rn：
And 4, step 4: repeating the step 2 and the step 3 for k times to obtain a component set c meeting the requirements of the inherent modal component under different white noises each timeij(i is less than or equal to n, j is less than or equal to k), and taking set average as final inherent modal component
And 5: judging whether the condition of quitting decomposition is met, if so, quitting decomposition; otherwise, decomposing each inherent modal component into 6 layers by adopting a db5 wavelet;
step 6: selecting a threshold value for each layer from the 1 st layer to the 6 th layer, and processing the high-frequency coefficient by using a soft threshold value;
and 7: a wavelet reconstruction of the signal is calculated from the low frequency coefficients of layer 6 and the modified high frequency coefficients from layer 1 to layer 6.
Normalizing the denoised magnetic field signal data on the surface of the steel wire rope to be detected to be between 0 and 255, and performing two-dimensional expansion to obtain a gray image of the surface of the steel wire rope to be detected.
And carrying out local adaptive interpolation and field interpolation on the gray level image on the surface of the steel wire rope to be detected to obtain two high-resolution gray level images after difference, carrying out two-dimensional discrete wavelet transform on the two interpolated gray level images, and carrying out two-dimensional discrete wavelet inverse transform on a high frequency part of the gray level image obtained by the local adaptive interpolation algorithm and a low frequency part of the gray level image obtained by the neighborhood interpolation algorithm to reconstruct a high-resolution gray level image.
The specific implementation steps of the local adaptive interpolation algorithm are as follows:
if the resolution of the original gray scale image is M × N and the resolution of the amplified gray scale image is 2M × 2N, the correspondence relationship is:
E(I(i,j))＝Z(2i-1,2j-1)
wherein i, j ═ 1, 2.., n;
the initial gray scale value of the interpolation point is set to-1. There are three cases of the magnified image.
For the point where I and j are odd in the amplified image, the gray value is the gray value I (I and j) of the point in the original image;
for pixel points of which i and j are even numbers in the amplified image, considering a neighborhood 2 x 2 window, and obtaining a gray value of the point according to which edge gradient the unassigned point belongs to;
for pixel points of which i is an even number and j is an odd number in the amplified image, calculating the correlation of the image in 4 directions by considering a neighborhood 3 x 2 window and interpolating in the maximum correlation direction to obtain the gray level of an interpolation point;
and for the pixel points with the odd number of i and the even number of j in the amplified image, the correlation of the image in 4 directions is calculated by considering the neighborhood 2 x 3 window, and the gray level of the interpolation point is obtained by interpolation in the maximum correlation direction.
And extracting characteristic quantities from the gray level image with the improved resolution ratio, and inputting the characteristic quantities into an artificial neural network to judge whether the steel wire rope to be detected has a breakpoint.
The feature quantities extracted from the grayscale image with the improved resolution include equivalent area, slenderness ratio, circularity and invariant moment feature quantities of seven orders of the defect, which are used as feature descriptions of the geometrical shape of the defect, and in the present embodiment, 10 defect image feature vectors are extracted from the defect grayscale image.
The artificial neural network in the embodiment adopts a three-layer BP neural network, and the three-layer BP neural network can approach any nonlinear model, so that the defects of the steel wire rope can be effectively and quantitatively identified.
When the leakage magnetic signal detection module 102 moves along the extending direction of the steel wire rope to be detected, the photoelectric encoder generates a pulse signal, the pulse signal passes through an RC low-pass filter in the pulse signal detection circuit to filter out high-frequency components in the pulse signal, and the pulse signal passes through a Schmidt gate circuit formed by two 47HC14M, so that the rising edge and the falling edge of the pulse become steep, the pulse signal is shaped, and the pulse signal with digital signal interference eliminated is obtained.
The ARM chip in the main control module 107 determines the position of the magnetic leakage signal detection module on the steel wire rope to be detected according to the received pulse signal, and determines the position of the defect on the steel wire rope to be detected according to the data detected by the magnetic leakage signal detection module 102.
The ARM chip is connected with a data storage module 104, the ARM chip stores data received from the signal conditioning module and the pulse signal detection unit into the data storage module 104, and a user can inquire the data storage module 104 in real time at an upper computer.
The display module 106 is connected to the FPGA chip, and the detection result is displayed through the display module 106 for the user to view.
In the present embodiment, the magnetic element in the excitation portion 101 is a permanent magnet; as other embodiments, an electromagnetic coil may be employed.
In another embodiment, the N poles of the magnets in the first excitation unit may be oriented in the same direction, and the S poles of the magnets in the second excitation unit may be oriented in the same direction.
As another embodiment, if only the steel wire rope is detected whether the defect exists and the defect is not required to be located, the pulse generation module may not be provided.
As another embodiment, the main control module 107 may be provided with only one ARM chip or FPGA chip.
Claims (10)
1. A weak magnetic excitation wire rope flaw detection device is characterized by comprising an excitation part and a magnetic leakage signal detection part which are arranged in a split mode;
the excitation part comprises two excitation units which are respectively used for being arranged at two ends of the steel wire rope to be tested; the magnetic leakage signal detection part is provided with a detection channel for the steel wire rope to be detected to pass through and move along the steel wire rope, and the detection channel is provided with a first set number of magnetic induction sensors;
each excitation unit comprises a second set number of magnetic elements, the magnetic elements are permanent magnets, each permanent magnet in the first magnetic unit is arranged in a ring shape, the N pole of each permanent magnet points to the center of the ring shape, each permanent magnet in the second excitation unit is arranged in a ring shape, and the S pole of each permanent magnet points to the center of the ring shape;
the number of the magnetic elements in each excitation unit is determined according to the length of the steel wire rope to be tested, and the longer the steel wire rope to be tested is, the more the magnetic elements are arranged in each excitation unit;
still include main control module, main control module connects each magnetic induction sensor's in the magnetic leakage signal detection part output, main control module is used for carrying out following processing:
1) the method comprises the following steps of performing noise reduction processing on magnetic field signal data on the surface of a steel wire rope to be detected by adopting a wavelet soft threshold denoising algorithm based on empirical mode decomposition, and specifically comprises the following steps:
step 1: carrying out mirror symmetry boundary extension on the magnetic field signal data of the surface of the steel wire rope to be detected to obtain the processed magnetic field signal data
Step 2: using a formula
And
decomposing y (t) to obtain c meeting the requirement of inherent modal componentijAnd a residual amount rn(ii) a y (t) is the semaphore after adding noise, namely the function to be decomposed; for residual rnAdding a Gaussian white noise sequence w (t);
and step 3: repeating the step 2 k times to obtain a component set c meeting the requirements of the inherent modal component under different white noises each timeijI is less than or equal to n, j is less than or equal to k, and the average value of the component set is taken as the final inherent modal component
And 4, step 4: judging whether the condition of quitting decomposition is met, if so, quitting decomposition; otherwise, decomposing each inherent modal component into 6 layers by adopting a db5 wavelet;
and 5: selecting a threshold value for each layer from the 1 st layer to the 6 th layer, and processing the high-frequency coefficient by using a soft threshold value;
step 6: calculating wavelet reconstruction of the signal according to the low-frequency coefficient of the 6 th layer and the modified high-frequency coefficient from the 1 st layer to the 6 th layer;
2) normalizing the denoised magnetic field signal data on the surface of the steel wire rope to be detected to be between 0 and 255, and performing two-dimensional expansion to obtain a gray image of the surface of the steel wire rope to be detected;
3) carrying out local adaptive interpolation and field interpolation on the gray level image on the surface of the steel wire rope to be detected to obtain two high-resolution gray level images after difference, carrying out two-dimensional discrete wavelet transform on the two interpolated gray level images, carrying out two-dimensional discrete wavelet inverse transform on a high frequency part of the gray level image obtained by the local adaptive interpolation algorithm and a low frequency part of the gray level image obtained by the neighborhood interpolation algorithm, and reconstructing a high-resolution gray level image;
4) and extracting characteristic quantity from the gray level image with the improved resolution ratio, and inputting the characteristic quantity into an artificial neural network to judge whether the steel wire rope to be detected has a breakpoint.
2. The weakly-magnetically-excited steel wire rope flaw detector according to claim 1, wherein a detection ring is provided on the detection channel, and each magnetic induction sensor is provided on the detection ring along the circumferential direction of the axis of the detection channel.
3. The weak magnetic excitation wire rope flaw detection device according to claim 1, further comprising a signal conditioning module, wherein the signal conditioning module comprises a differential signal amplifying circuit and an analog-to-digital conversion circuit, an input end of the differential signal amplifying circuit is connected with an output end of each magnetic induction sensor, and an output end of the differential signal amplifying circuit is connected with an input end of the analog-to-digital conversion circuit; the main control module is connected with the output end of the analog-to-digital conversion circuit.
4. The weakly-magnetically-excited steel wire rope flaw detection device according to claim 3, wherein the signal conditioning module further comprises an addition baseline boost circuit, an input end of the addition baseline boost circuit is connected with an output end of the analog-to-digital conversion circuit, and an output end of the addition baseline boost circuit is connected with the main control module.
5. The weak magnetic excitation steel wire rope flaw detection device according to claim 1, further comprising a pulse generation module, wherein the pulse generation module comprises a photoelectric encoder and a photoelectric encoder detection circuit, and the photoelectric encoder is used for sending out a pulse signal; the input end of the photoelectric encoder detection circuit is connected with the output end of the photoelectric encoder, and the main control module is connected with the output end of the photoelectric encoder detection circuit.
6. The weak magnetic excitation wire rope flaw detection device according to claim 5, wherein the photoelectric encoder detection circuit comprises a photoelectric coupler and a signal shaping circuit, the input end of the photoelectric coupler is connected with the photoelectric encoder, and the output end of the photoelectric coupler is connected with the signal shaping circuit; the main control module is connected with the output end of the signal shaping circuit, and the shaping circuit is used for shaping the rising edge and the falling edge of the pulse signal sent by the photoelectric encoder.
7. The weak magnetic excitation steel wire rope flaw detection device according to claim 1, wherein a display module is further connected to the main control module.
8. The weak-magnetic-excitation steel wire rope flaw detection device according to claim 1, wherein the main control module comprises an ARM chip and an FPGA chip, and the ARM chip is connected with each magnetic induction sensor in the leakage magnetic signal detection part.
9. The weak magnetic excitation steel wire rope flaw detection device according to claim 8, wherein the main control module is further connected with a data storage module.
10. A weak magnetic excitation steel wire rope flaw detection method is characterized by comprising the following steps:
(1) arranging the N pole of the magnetic element in the first excitation unit at one end of the steel wire rope to be tested, and arranging the S pole of the magnetic element in the second excitation unit at the other end of the steel wire rope to be tested; the magnetic elements are permanent magnets, wherein each permanent magnet in the first magnetic unit is arranged in a ring shape, and the N pole of each permanent magnet points to the center of the ring; each permanent magnet in the second excitation unit is arranged in a ring shape, and the S pole of each permanent magnet points to the center of the ring;
(2) carrying out magnetic field detection on the surface of the steel wire rope to be detected by adopting a magnetic leakage signal detection part to obtain magnetic field data of the surface of the steel wire rope to be detected;
(3) performing baseline removal processing and noise reduction processing on the magnetic field data of the surface of the steel wire rope to be detected, performing noise reduction processing on the magnetic field signal data of the surface of the steel wire rope to be detected by adopting a wavelet soft threshold denoising algorithm based on empirical mode decomposition, normalizing the denoised magnetic field signal data of the surface of the steel wire rope to be detected to be between 0 and 255, and performing two-dimensional expansion to obtain a gray image of the surface of the steel wire rope to be detected; the noise reduction treatment comprises the following specific steps:
step 1: carrying out mirror symmetry boundary extension on the magnetic field signal data of the surface of the steel wire rope to be detected to obtain the processed magnetic field signal data
Step 2: using a formula
And
decomposing y (t) to obtain c meeting the requirement of inherent modal componentijAnd a residual amount rn(ii) a y (t) is the semaphore after adding noise, namely the function to be decomposed; for residual rnAdding a Gaussian white noise sequence w (t);
and step 3: repeating the step 2 k times to obtain a component set c meeting the requirements of the inherent modal component under different white noises each timeijI is less than or equal to n, j is less than or equal to k, and the average value of the component set is taken as the final inherent modal component
And 4, step 4: judging whether the condition of quitting decomposition is met, if so, quitting decomposition; otherwise, decomposing each inherent modal component into 6 layers by adopting a db5 wavelet;
and 5: selecting a threshold value for each layer from the 1 st layer to the 6 th layer, and processing the high-frequency coefficient by using a soft threshold value;
step 6: calculating wavelet reconstruction of the signal according to the low-frequency coefficient of the 6 th layer and the modified high-frequency coefficient from the 1 st layer to the 6 th layer;
(4) carrying out local adaptive interpolation and field interpolation on the gray level image on the surface of the steel wire rope to be detected to obtain two high-resolution gray level images after difference, carrying out two-dimensional discrete wavelet transform on the two interpolated gray level images, carrying out two-dimensional discrete wavelet inverse transform on a high frequency part of the gray level image obtained by the local adaptive interpolation algorithm and a low frequency part of the gray level image obtained by the neighborhood interpolation algorithm, and reconstructing a high-resolution gray level image;
(5) and extracting characteristic quantity from the gray level image with the improved resolution ratio, inputting the characteristic quantity into an artificial neural network for quantitative identification, and judging whether the steel wire rope to be detected has a breakpoint.
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| JP7109247B2 (en) * | 2018-05-02 | 2022-07-29 | 三菱電機株式会社 | WIRE ROPE INSPECTION DEVICE AND METHOD |
| CN208833707U (en) * | 2018-09-20 | 2019-05-07 | 江苏多维科技有限公司 | A kind of non-destructive testing device detecting damage of steel cable |
| CN109164165B (en) * | 2018-10-09 | 2022-10-11 | 河南科技大学 | Image fusion-based steel wire rope nondestructive testing method and device |
| CN109682824B (en) * | 2018-12-28 | 2021-09-24 | 河南科技大学 | Image fusion-based steel wire rope nondestructive testing method and device |
| CN112326780B (en) * | 2020-03-06 | 2024-02-09 | 中设（深圳）设备检验检测技术有限公司 | Wire rope on-line magnetic leakage nondestructive detection device for mine hoisting |
| CN113884563B (en) * | 2021-08-12 | 2023-10-24 | 洛阳百克特科技发展股份有限公司 | Device and method for detecting magnetic leakage of saturated excitation steel wire rope |
| CN113724249B (en) * | 2021-09-18 | 2023-06-16 | 西南交通大学 | Method and system for outputting weld defect eddy current flaw detection data |
| CN114166861A (en) * | 2021-12-15 | 2022-03-11 | 中煤科工集团上海有限公司 | Online nondestructive flaw detection device and method for surface of steel wire rope |
| CN114235825B (en) * | 2022-02-24 | 2022-05-17 | 武汉祥文钢材制品有限公司 | Steel wire rope quality detection method based on computer vision |
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