Transmission tower body angle steel corrosion defect detection method

Abstract

The invention discloses a transmission tower body angle steel corrosion defect detection method, which comprises the following steps: designing an excitation device, and carrying out saturation magnetization on transmission tower body angle steel; arranging a Hall sensor, and collecting a magnetic flux leakage signal; carrying out filtering processing and feature extraction on the magnetic flux leakage signal acquired by the Hall sensor; establishing a fitting relationship between the defect parameters and the magnetic flux leakage characteristic quantity; and quantitatively detecting the size of the angle steel corrosion defect of the to-be-detected transmission tower body. Whether the transmission tower has a defect or not is judged and the size of the defect is quantitatively judged by detecting the magnetic flux leakage signal on the surface of the transmission tower angle steel, so that the corrosion defect size of the transmission tower body angle steel is accurately and quickly diagnosed, the reliability is good, the detection efficiency is high, the operation is simple and convenient, and the magnetic flux leakage detection device is simple and portable in structure, low in cost and easy to popularize. A theoretical basis is provided for avoiding electric power accidents caused by tower corrosion defects, and the method has important engineering significance.

Description

Technical Field

[0001] The invention relates to the technical field of magnetic flux leakage nondestructive detection, and in particular to a magnetic flux leakage detection method for reflecting the size of corrosion defects of angle steel of a transmission tower body through magnetic flux leakage signals. Background Art

[0002] Transmission lines are an important part of the power system and the main artery of modern energy. Transmission towers play an important role in supporting transmission conductors and overhead ground wires in transmission lines. Affected by environmental factors, transmission lines will inevitably corrode. The environment can be classified into rural environment, marine environment, industrial pollution environment, urban environment, etc. Among them, the corrosion rate of industrial pollution environment and marine environment is the highest. In addition to corrosion factors, human factors, bird pecking and lightning strikes may cause structural defects in transmission lines. Transmission towers are composed of angle steels. Once the structure of the transmission tower body angle steel is damaged, a large stress concentration will be generated at the damaged part of the structure. In addition, the transmission tower is under a large load. Coupled with additional loads such as wind blowing and ice covering, the probability of the transmission tower becoming unstable and collapsing is extremely high. Once the transmission tower collapses, the entire line will be shut down, which will have a serious adverse impact on social production and life, and the recovery time is long, resulting in a large amount of economic losses. Therefore, in order to avoid greater accidents caused by defects in the transmission tower body angle steel, it is very important to detect corrosion defects in the transmission tower body angle steel. When defects are detected, quantitative judgment of the defects will help to formulate subsequent maintenance and reinforcement work plans.

[0003] Nondestructive testing technology has gradually developed from qualitative early warning research to determine the existence of defects in the early stage to quantitative research for defect location and size evaluation. When there are defects in the material, there are signal differences in the response of the material or structure to the effects of sound, heat, light, magnetism, etc. People can judge whether there are defects in the material or structure and the location and size of the defects through signal differences. The transmission tower is a spatial truss structure composed of angle steels of various specifications. At present, the nondestructive testing methods suitable for the angle steels of the transmission tower include ultrasonic testing, X-ray testing, eddy current testing, infrared thermal imaging testing, microwave testing and magnetic flux leakage testing. Ultrasonic testing requires good acoustic coupling, has requirements for the smoothness of the casting surface, has a low signal-to-noise ratio, is difficult to detect small cracks, and has high requirements for the testing personnel; X-ray testing has high requirements for the testing environment, slow speed, high cost, radiation hazards, and high requirements for the quality of the testing personnel; Eddy current testing can only detect surface and near-surface defects of conductive materials, and it is difficult to qualitatively and quantitatively evaluate defects; infrared thermal imaging has low image contrast, high cost, and expensive price; microwave testing is not suitable for detecting defects less than 1mm, and has low spatial resolution.

[0004] The above existing non-destructive testing technologies all have different disadvantages. Therefore, it is urgent to propose a method for detecting corrosion defects of angle steel of transmission tower body with good reliability and high detection efficiency. For defect detection of ferromagnetic materials, the magnetic flux leakage detection method has the advantages of high measurement accuracy, simple operation and low cost. Summary of the invention

[0005] In view of the obvious deficiencies of the above-mentioned non-destructive testing methods and the good applicability of the leakage magnetic detection method, the present invention provides a method for detecting corrosion defects of the angle steel of the transmission tower body. By detecting the leakage magnetic signal on the surface of the transmission tower angle steel, it is determined whether the transmission tower has defects and quantitatively determines the size of the defects, thereby achieving accurate and rapid diagnosis of the corrosion defect size of the transmission tower body angle steel. The operation is simple, the leakage magnetic detection device has a simple and portable structure, and the cost is low. It provides a theoretical basis for avoiding power accidents caused by corrosion defects of the tower, and has important engineering significance.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions.

[0007] A method for detecting corrosion defects of angle steel of a transmission tower body, comprising the following steps: Step S1: design an excitation device to saturate magnetize the angle steel of the transmission tower body; Step S2: Arrange Hall sensors to collect leakage magnetic signals; Step S3: Filter and extract features of the magnetic flux leakage signal collected by the Hall sensor. The magnetic flux leakage feature quantity includes the magnetic flux leakage signal B x The peak value and leakage magnetic signal of component B y The peak-to-valley spacing of the components; Step S4: Establish the fitting relationship between defect parameters and magnetic flux leakage characteristics, including defect depth-B x Peak Fitting Relationship and Defect Width-B y Peak-to-valley spacing fitting relationship; Step S5: quantitatively detect the size of the corrosion defects of the angle steel of the transmission tower body to be tested, and obtain defect parameter information.

[0008] The present invention provides a method for detecting corrosion defects of angle steels of transmission tower bodies. By detecting the magnetic leakage signal on the surface of the angle steels of the transmission tower bodies, it is determined whether the transmission tower has defects and the size of the defects is quantitatively determined, thereby achieving accurate and rapid diagnosis of the size of the corrosion defects of the angle steels of the transmission tower bodies. The method has good reliability, high detection efficiency, and simple operation. The magnetic leakage detection device has a simple and portable structure and low cost. The method provides a theoretical basis for avoiding power accidents caused by corrosion defects of the tower bodies and has important engineering significance.

[0009] Preferably, in step S1, for different types of transmission tower angle steel components, the finite element calculation method is used to determine the magnetic pole spacing L and the air gap δ; the first armature and the second armature are placed according to the magnetic pole spacing L, the permanent magnet N pole is placed on the first armature, and the permanent magnet S pole is placed on the second armature; the third armature is placed on the permanent magnet.

[0010] In order to ensure that the leakage magnetic signal at the defect is strong and stable enough during the detection of the tower, it is necessary to design the excitation device reasonably to ensure that the tower angle steel is magnetized to saturation or near saturation. The design of the excitation device mainly includes the determination of the magnetic field excitation source, the magnetic pole spacing L, and the air gap δ between the magnet and the tower surface.

[0011] There are two excitation methods currently available: electromagnetic and permanent magnet. The electromagnetic excitation method is to energize a coil with a magnetic core, so that the coil generates a magnetic field, the magnetic core is magnetized, and then the electrified magnetic core moves on the surface of the pole tower angle steel to generate excitation. The biggest advantage of the electromagnetic solution is that the excitation of the magnet is controllable, but since the coil will dissipate heat, the excitation current generated by the coil itself also needs to be considered. The permanent magnet excitation method is to directly excite the pole tower with a permanent magnet, and the material and size of the permanent magnet directly affect the excitation effect. The advantage of the permanent magnet solution is that the structure is simple and no excitation current is generated. Comparing the electromagnetic and permanent magnet excitation methods, when magnetizing the pole tower angle steel of the same size and the same material, the magnetic induction intensity of the pole tower angle steel is detected. Only when the excitation voltage is too high and the number of coil turns is too large, can the magnetic induction intensity of the electromagnetic solution and the permanent magnet solution be equal, but the use of multiple coils will make the structure of the leakage magnetic detection device more bulky. Therefore, the complexity of the excitation device structure and the excitation efficiency are considered in the design of the present invention, and the permanent magnet method is finally selected to magnetize the pole tower angle steel.

[0012] The magnetic pole spacing L and the air gap δ are important structural parameters of the excitation device (excitation circuit) in magnetic flux leakage detection. An increase in the magnetic pole spacing L will lead to a decrease in the degree of magnetization and the intensity of the magnetic flux leakage signal at the defect, but an appropriate increase in L will not significantly reduce the magnetization intensity and the magnetic flux leakage signal at the defect. On the contrary, increasing L can reduce the degree of magnetic field-air coupling (the magnetic field overflowing from the air gap), reduce the background magnetic field intensity, and improve the signal-to-noise ratio. However, if L is too large, the magnetic flux leakage detection device will be larger and heavier, which is not conducive to portable design. For the selection of the air gap δ, considering the uneven surface of the angle steel of the pole tower to be tested, δ should be made as small as possible. Therefore, the present invention uses a finite element calculation method to determine the appropriate magnetic pole spacing L and air gap δ for pole tower angle steel components of different models.

[0013] Preferably, in step S2, the Hall sensor is arranged in the middle of the two magnetic poles of the permanent magnet, and a shielding box made of ferromagnetic material is provided outside the Hall sensor; and the distance Δf between the Hall sensor and the surface of the angle steel of the transmission tower is determined by a finite element calculation method.

[0014] A magnetic sensor is a device that converts magnetic signals into electrical signals. There are many types of magnetic sensors, including induction coils, Hall elements, fluxgates, magnetic diodes and transistors, magnetoresistors, etc. Different magnetic sensors have different measurement ranges. The magnetic field measurement range of Hall elements is 10 -5 ~10T, which meets the measurement requirements of the present invention, and has the advantages of small size, light weight, long life, low power consumption, good performance, etc. Therefore, the present invention selects the Hall element as the magnetic field sensor, and its working principle is: when the direction of current movement is perpendicular to the direction of magnetic induction intensity, Hall electromotive force is generated on both sides of the Hall element, which can be expressed by the following formula: V H =K H ×I×B×cosα Among them, V H is the Hall electromotive force; K H is the Hall coefficient; I is the current; B is the magnetic induction intensity; cosα is the normal angle between the magnetic induction intensity and the Hall component.

[0015] The Hall sensor is arranged in the middle of the two poles of the permanent magnet, and then the distance Δf between the Hall sensor and the surface of the angle steel of the tower is determined, that is, the lift-off value. In actual detection, it is very likely that Δf will change due to slight vibrations. When Δf is small, the measurement sensitivity is high, but the magnetic field measurement value will change greatly with the fluctuation of Δf; when Δf is large, the stability is good, but the magnetic field measurement value is close to the background magnetic field, the sensitivity becomes low, and the signal-to-noise ratio decreases. Therefore, in order to ensure the stability and reliability of the measurement signal, it is necessary to select a suitable lift-off value Δf. The present invention uses a finite element calculation method to determine the appropriate Δf.

[0016] Preferably, in step S2, the excitation device and the Hall sensor with the shielding box are placed in a four-wheeled trolley to form a magnetic flux leakage detection device for detecting magnetic flux leakage signals on the surface of the angle steel of the transmission tower. The magnetic flux leakage detection device is placed on the surface of the tower and moves along the measurement track to scan and detect magnetic flux leakage signals on the surface of the angle steel of the tower. The magnetic flux leakage detection device designed by the present invention has a simple structure and is portable.

[0017] Preferably, in step S3, a sliding average method is used to filter the magnetic flux leakage signal. By setting a fixed sliding window length, the average value is calculated, and the sliding is performed in sequence, and the output values ​​form a new sequence. The raw data collected by the Hall sensor may contain noise due to environmental factors and other factors, and needs to be filtered. The filtered data retains the original characteristics of the signal, and then the signal characteristics are extracted through the time domain waveform.

[0018] The sliding average method is used for filtering. This method is to set a fixed window, calculate the average value, slide in order, and the output value forms a new sequence. The detection data x(t) includes the effective signal f(t) and the error e(t). After discrete sampling, the dynamic detection data is shown as follows: x(n)=f(n)+e(n)(n=1,2,3,...) In order to make the measurement result more accurate, the error e(n) can be suppressed. By calculating the local average value in a small interval of x(n), the smoothed measurement result f(n) can be obtained, and the high-frequency random error can be filtered out.

[0019] Preferably, in step S3, the leakage magnetic signal feature is extracted by using the time domain waveform, and the leakage magnetic signal B is selected. x The peak value of the component is used as the characteristic quantity for judging the defect depth, and the leakage magnetic signal B is selected y The peak-to-valley distance of the component is used as the characteristic quantity to judge the defect width.

[0020] For the quantitative judgment of defects, the focus is on the time domain characteristics of the leakage magnetic signal. The waveform of the tower defect leakage magnetic detection signal has obvious peak and valley characteristics. From the perspective of time domain characteristics, the peak value, peak-valley distance and area under the waveform can be used as important characteristic quantities for the presence of defects and quantitative judgment of defects. x The peak value of B is mainly related to the depth of the defect. y The peak-to-valley spacing of is mainly affected by the defect width. Therefore, the present invention selects B x The peak value is used as the characteristic quantity for judging the defect depth, and B is selected y The peak-to-valley distance is used as the characteristic quantity for judging the defect width.

[0021] Preferably, in step S4, in order to accurately invert the defect parameters using the leakage magnetic detection signal, a finite element simulation model of the transmission tower angle steel is established using Comsol, and the leakage magnetic distribution under different defect widths and different defect depths is calculated using the finite element method, and then a fitting relationship between the defect parameters and the leakage magnetic characteristic quantity is established. The fitting relationship is represented by a fitting function, including the defect depth-B x Component peak fitting function and defect width - B y Component peak-to-valley spacing fitting function.

[0022] As a preferred embodiment, in step S4, the defect width range is divided to establish the defect depth and leakage magnetic signal B under different defect width ranges. x The peak value of the component.

[0023] Since the defect width affects B x The peak value of B yThe component peak-to-valley spacing is mainly related to the defect width and is less affected by other factors. Therefore, the defect width range is divided to establish the defect depth and B under different defect width ranges. x The peak fitting relationship.

[0024] Preferably, the specific process of step S5 includes the following steps: Step S51: The magnetic flux leakage detection device moves and scans the surface of the transmission tower angle steel to obtain the magnetic flux leakage signal on the surface of the transmission tower angle steel; Step S52: Extract the magnetic flux leakage signal B x The peak value and leakage magnetic signal of component B y The peak-to-valley spacing of the components; Step S53: Transform the magnetic flux leakage signal B y Substitute the peak-to-valley spacing of the component into the defect width - B y The component peak-to-valley spacing fitting function is used to obtain the defect width information; Step S54: Based on the defect width information, the leakage magnetic signal B x Substitute the peak value of the component into the corresponding defect depth -B x Component peak fitting function is used to obtain defect depth information.

[0025] Preferably, in step S5, for a signal x(n) containing N sampled data, the interval of each m adjacent data is close to being stable, and its mean is close to a constant, so the average value of the m adjacent data is taken as the value of the m data, and it is considered that random errors are suppressed or noise signals are eliminated. For a signal x(n) containing N sampled data, its sliding mean sequence is as follows: Where k is the sliding window length.

[0026] By processing data by the sliding average method, the influence of the noise signal e(n) on the measured data can be reduced. The length of the sliding window will affect the filtering effect. If the length is too small, the filtering effect will be poor. If the length is too large, some important information in the signal will be filtered together. Therefore, when the present invention actually processes data, it selects a suitable sliding window length according to the actual filtering effect to ensure the filtering effect and retain the curve characteristics of the signal.

[0027] Therefore, the advantages of the present invention are: by detecting the leakage magnetic signal on the surface of the transmission tower angle steel, it is determined whether the transmission tower has defects and quantitatively determines the size of the defects, thereby achieving accurate and rapid diagnosis of the corrosion defect size of the transmission tower body angle steel, good reliability, high detection efficiency, and simple operation. The leakage magnetic detection device has a simple and portable structure and low cost, which provides a theoretical basis for avoiding power accidents caused by tower corrosion defects and has important engineering significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 The present invention is a flowchart of a method for detecting corrosion defects of angle steel of a transmission tower body according to an embodiment of the present invention.

[0029] Figure 2 It is a schematic diagram of magnetic flux leakage detection of the angle steel of the transmission tower body in an embodiment of the present invention.

[0030] Figure 3 is the defect leakage magnetic characteristic signal B in the embodiment of the present invention x , B y Schematic diagram.

[0031] Figure 4 Schematic diagram of the structure of the magnetic flux leakage detection device in an embodiment of the present invention.

[0032] Figure 5 It is a schematic diagram of the structure of the excitation device in an embodiment of the present invention.

[0033] Figure 6 It is the BH curve in the embodiment of the present invention.

[0034] Figure 7 It is a cloud diagram of magnetic field distribution in an embodiment of the present invention.

[0035] Figure 8 Schematic diagram of the angle steel defects of the transmission tower body in the embodiment of the present invention.

[0036] Fig. 9 is the magnetic flux leakage signal B in the embodiment of the present invention y Schematic diagram of the relationship with defect width a.

[0037] Fig.10 is the magnetic flux leakage signal B in the embodiment of the present invention x-max Schematic diagram of the relationship with defect width a.

[0038] Fig.11 is the magnetic flux leakage signal B in the embodiment of the present invention x Schematic diagram of the relationship with defect depth b.

[0039] 1. Angle steel 2. First armature 3. Second armature 4. Permanent magnet N pole 5. Permanent magnet S pole 6. Third armature 7. Hall sensor 8. Shielding box 9. Four-wheeled trolley 10. Transmission tower. DETAILED DESCRIPTION

[0040] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0041] Embodiment 1.

[0042] A method for detecting corrosion defects of angle steel of transmission tower body, such as Figure 1 and Figure 2 As shown, the following steps are included: Step S1: design an excitation device to saturate magnetize the angle steel of the transmission tower body; Step S2: Arrange Hall sensors to collect leakage magnetic signals; Step S3: Filter and extract features of the magnetic flux leakage signal collected by the Hall sensor. The magnetic flux leakage feature quantity includes the magnetic flux leakage signal B x The peak value and leakage magnetic signal of component B y The peak-to-valley spacing of the components; Step S4: Establish the fitting relationship between defect parameters and magnetic flux leakage characteristics, including defect depth-B x Peak Fitting Relationship and Defect Width-B y Peak-to-valley spacing fitting relationship; Step S5: quantitatively detect the size of the corrosion defects of the angle steel of the transmission tower body to be tested, and obtain defect parameter information.

[0043] This embodiment provides a method for detecting corrosion defects of the angle steel of the transmission tower body. By detecting the leakage magnetic signal on the surface of the angle steel of the transmission tower, it is determined whether the transmission tower has defects and quantitatively determines the size of the defects, thereby achieving accurate and rapid diagnosis of the corrosion defect size of the angle steel of the transmission tower body. The method has good reliability, high detection efficiency, and simple operation. The leakage magnetic detection device has a simple and portable structure and low cost. It provides a theoretical basis for avoiding power accidents caused by corrosion defects of the tower and has important engineering significance.

[0044] In step S1, for different types of transmission tower angle steel components, the finite element calculation method is used to determine the magnetic pole spacing L and the air gap δ; Figure 5 As shown, the first armature 2 and the second armature 3 are placed according to the magnetic pole distance L, the permanent magnet N pole 4 is placed on the first armature 2, and the permanent magnet S pole 5 is placed on the second armature 3; the third armature 6 is placed on the permanent magnet.

[0045] In order to ensure that the leakage magnetic signal at the defect is strong and stable enough during the detection of the tower, it is necessary to design the excitation device reasonably to ensure that the tower angle steel is magnetized to saturation or near saturation state. Figure 5 As shown, the design of the excitation device mainly includes the determination of the magnetic field excitation source, the magnetic pole spacing L, and the air gap δ between the magnet and the tower surface.

[0046] There are two excitation methods currently available: electromagnetic and permanent magnet. The electromagnetic excitation method is to energize a coil with a magnetic core, so that the coil generates a magnetic field, the magnetic core is magnetized, and then the electrified magnetic core moves on the surface of the pole tower angle steel to generate excitation. The biggest advantage of the electromagnetic solution is that the excitation of the magnet is controllable, but since the coil will dissipate heat, the excitation current generated by the coil itself also needs to be considered. The permanent magnet excitation method is to directly excite the pole tower with a permanent magnet, and the material and size of the permanent magnet directly affect the excitation effect. The advantage of the permanent magnet solution is that the structure is simple and no excitation current is generated. Comparing the electromagnetic and permanent magnet excitation methods, when magnetizing the pole tower angle steel of the same size and the same material, the magnetic induction intensity of the pole tower angle steel is detected. Only when the excitation voltage is too high and the number of coil turns is too large, can the magnetic induction intensity of the electromagnetic solution and the permanent magnet solution be equal, but the use of multiple coils will make the structure of the leakage magnetic detection device more bulky. Therefore, this embodiment considers the complexity of the excitation device structure and the excitation efficiency when designing, and finally chooses the permanent magnet method to magnetize the pole tower angle steel.

[0047] The magnetic pole spacing L and the air gap δ are important structural parameters of the excitation device (excitation circuit) in magnetic flux leakage detection. An increase in the magnetic pole spacing L will lead to a decrease in the degree of magnetization and the intensity of the magnetic flux leakage signal at the defect, but an appropriate increase in L will not significantly reduce the magnetization intensity and the magnetic flux leakage signal at the defect. On the contrary, increasing L can reduce the degree of magnetic field-air coupling (the magnetic field overflowing from the air gap), reduce the background magnetic field intensity, and improve the signal-to-noise ratio. However, if L is too large, the magnetic flux leakage detection device will be larger and heavier, which is not conducive to portable design. For the selection of the air gap δ, considering the uneven surface of the angle steel of the pole tower to be tested, δ should be made as small as possible. Therefore, in this embodiment, the finite element calculation method is used to determine the appropriate magnetic pole spacing L and air gap δ for different types of pole tower angle steel components.

[0048] In step S2, Figure 5 As shown, the Hall sensor 7 is arranged in the middle of the two magnetic poles of the permanent magnet, and a shielding box 8 made of ferromagnetic material is provided outside the Hall sensor 7; the distance Δf between the Hall sensor 7 and the surface of the angle steel 1 of the transmission tower 10 is determined by the finite element calculation method.

[0049] A magnetic sensor is a device that converts magnetic signals into electrical signals. There are many types of magnetic sensors, including induction coils, Hall elements, fluxgates, magnetic diodes and transistors, magnetoresistors, etc. Different magnetic sensors have different measurement ranges. The magnetic field measurement range of Hall elements is 10 -5 ~10T, which meets the measurement requirements of this embodiment, and has the advantages of small size, light weight, long life, low power consumption, good performance, etc. Therefore, this embodiment uses the Hall element as the magnetic field sensor, and its working principle is: when the direction of current movement is perpendicular to the direction of magnetic induction intensity, the Hall electromotive force is generated on both sides of the Hall element, which can be expressed by the following formula: VH =K H ×I×B×cosα Among them, V H is the Hall electromotive force; K H is the Hall coefficient; I is the current; B is the magnetic induction intensity; cosα is the normal angle between the magnetic induction intensity and the Hall component.

[0050] The Hall sensor is arranged in the middle of the two poles of the permanent magnet, and then the distance Δf between the Hall sensor and the surface of the tower angle steel is determined, that is, the lift-off value. In actual detection, it is very likely that Δf will change due to slight vibrations. When Δf is small, the measurement sensitivity is high, but the magnetic field measurement value will change greatly with the fluctuation of Δf; when Δf is large, the stability is good, but the magnetic field measurement value is close to the background magnetic field, the sensitivity becomes low, and the signal-to-noise ratio decreases. Therefore, in order to ensure the stability and reliability of the measurement signal, it is necessary to select a suitable lift-off value Δf. This embodiment uses the finite element calculation method to determine the appropriate Δf.

[0051] In step S2, Figure 4 As shown, the excitation device and the Hall sensor 7 with the shielding box 8 are placed in the four-wheeled trolley 9 to form a magnetic flux leakage detection device for detecting magnetic flux leakage signals on the surface of the angle steel 1 of the transmission tower 10. In this embodiment, the magnetic flux leakage detection device is placed on the surface of the tower and moves along the measurement track to scan and detect the magnetic flux leakage signals on the surface of the angle steel of the tower. The magnetic flux leakage detection device designed in this embodiment is simple in structure and portable.

[0052] In step S3, the sliding average method is used to filter the magnetic flux leakage signal. By setting a fixed sliding window length, the average value is calculated, and the sliding is performed in sequence to form a new sequence of output values. The raw data collected by the Hall sensor will contain noise due to environmental factors and other factors, and needs to be filtered. The filtered data retains the original characteristics of the signal, and then the signal characteristics are extracted through the time domain waveform.

[0053] The sliding average method is used for filtering. This method is to set a fixed window, calculate the average value, slide in order, and the output value forms a new sequence. The detection data x(t) includes the effective signal f(t) and the error e(t). After discrete sampling, the dynamic detection data is shown as follows: x(n)=f(n)+e(n)(n=1,2,3,...) In order to make the measurement result more accurate, the error e(n) can be suppressed. By calculating the local average value in a small interval of x(n), the smoothed measurement result f(n) can be obtained, and the high-frequency random error can be filtered out.

[0054] In step S3, the leakage magnetic signal feature is extracted through the time domain waveform, such as Figure 3As shown, select the leakage magnetic signal B x The peak value of the component is used as the characteristic quantity for judging the defect depth, and the leakage magnetic signal B is selected y The peak-to-valley distance of the component is used as the characteristic quantity to judge the defect width.

[0055] For the quantitative judgment of defects, the focus is on the time domain characteristics of the leakage magnetic signal. The waveform of the tower defect leakage magnetic detection signal has obvious peak and valley characteristics. From the perspective of time domain characteristics, the peak value, peak-valley distance and area under the waveform can be used as important characteristic quantities for the presence of defects and quantitative judgment of defects. x The peak value of B is mainly related to the depth of the defect. y The peak-to-valley spacing is mainly affected by the defect width. Therefore, in this embodiment, B is selected. x The peak value is used as the characteristic quantity for judging the defect depth, and B is selected y The peak-to-valley distance is used as the characteristic quantity for judging the defect width.

[0056] In step S4, in order to accurately invert the defect parameters using the leakage magnetic detection signal, a finite element simulation model of the transmission tower angle steel is established using Comsol, and the leakage magnetic distribution under different defect widths and different defect depths is calculated using the finite element method. Then, a fitting relationship between the defect parameters and the leakage magnetic characteristic quantity is established. The fitting relationship is represented by a fitting function, including the defect depth-B x Component peak fitting function and defect width - B y Component peak-to-valley spacing fitting function.

[0057] In step S4, the defect width range is divided to establish the defect depth and leakage magnetic signal B under different defect width ranges. x The peak value of the component.

[0058] Since the defect width affects B x The peak value of B y The component peak-to-valley spacing is mainly related to the defect width and is less affected by other factors. Therefore, the defect width range is divided to establish the defect depth and B under different defect width ranges. x The peak fitting relationship.

[0059] The specific process of step S5 includes the following steps: Step S51: The magnetic flux leakage detection device moves and scans the surface of the transmission tower angle steel to obtain the magnetic flux leakage signal on the surface of the transmission tower angle steel; Step S52: Extract the magnetic flux leakage signal B x The peak value and leakage magnetic signal of component B y The peak-to-valley spacing of the components; Step S53: Transform the magnetic flux leakage signal B y Substitute the peak-to-valley spacing of the component into the defect width - By The component peak-to-valley spacing fitting function is used to obtain the defect width information; Step S54: Based on the defect width information, the leakage magnetic signal B x Substitute the peak value of the component into the corresponding defect depth -B x Component peak fitting function is used to obtain defect depth information.

[0060] In step S5, for a signal x(n) containing N sampled data, the small interval of each m adjacent data is close to stable, and its mean is close to a constant, so the average value of the m adjacent data is taken as the value of the m data, and it is considered that random errors are suppressed or noise signals are eliminated. For a signal x(n) containing N sampled data, its sliding average sequence is as follows: Where k is the sliding window length.

[0061] By processing data by the sliding average method, the influence of the noise signal e(n) on the measured data can be reduced. The sliding window length will affect the filtering effect. If the length is too small, the filtering effect will be poor. If the length is too large, some important information in the signal will be filtered together. Therefore, when processing data in practice, this embodiment selects a suitable sliding window length according to the actual filtering effect to ensure the filtering effect and retain the curve characteristics of the signal.

[0062] Embodiment 2.

[0063] In order to clearly illustrate the technical solution of the present invention, a specific simulation is performed below using the finite element simulation software Comsol to elaborate on the present invention in detail and verify the feasibility of the technical solution.

[0064] The present invention provides a method for quantitatively detecting defects in angle steel of a transmission tower body, comprising the following steps: 1) Design the excitation circuit and saturate the angle steel of the transmission tower body Using the electromagnetic field analysis module in Comsol, a finite element simulation model is constructed for calculation and analysis. Because the transmission tower is composed of angle steel, according to the design drawings of the transmission tower of the State Grid transmission line, the important load-bearing parts are selected, and the angle steel of model L160×14mm is modeled. The angle steel model with a length of 1m, a limb width of 160mm, and a thickness of 14mm is established; then the excitation circuit is constructed, and the length, width, and height of the permanent magnet are 100mm, 50mm, and 40mm respectively. The schematic diagram of the leakage magnetic detection device and the schematic diagram of the excitation circuit (excitation device) are shown in the figure. Figure 4 , 5 As shown; According to the magnetization characteristics of the material, the appropriate constitutive relationship is selected for different materials. The constitutive relationship of the air domain and the armature is the relative magnetic permeability, whose values ​​are 1 and 4000 respectively; the magnetic properties of the permanent magnet are expressed by the residual magnetic flux density, whose value is 1.5T; the constitutive relationship of the angle steel adopts the BH curve, such as Figure 6 As shown; the magnetic pole spacing L is set to 100mm, the air gap δ is 1mm, and the magnetic field distribution cloud diagram is as follows Figure 7 As shown, at this time, the internal magnetization degree of the angle steel reaches 1.78T, which meets the requirements of saturation magnetization; 2) Sensor layout The Hall element is selected as the magnetic field sensor. The sensor is placed in the middle of the excitation device. The sensor is covered by a shielding box made of ferromagnetic material to shield the interference magnetic field signal and enhance the signal quality. The simulation analysis found that the distance Δf between the sensor and the surface of the tower angle steel is in the range of 3 to 5mm, and the leakage magnetic signal is stable and obvious, so the value of Δf is determined to be 3mm; 3) Fitting Defect diagram see Figure 8 , preset defect features at x=500mm in the middle of the angle steel to be tested, the width of the defect is a, and the depth is b. When the defect width is 5mm, 10mm, 15mm, 20mm, 25mm, 30mm, 35mm, 40mm, 45mm, 50mm, the magnetic flux leakage detection device scans along the axial direction of the angle steel, and the magnetic flux leakage signal B measured by the sensor y like Fig. 9 As shown; Extracting magnetic flux leakage signal B y The peak-to-valley spacing, fitting peak-to-valley spacing B y-fg Relationship with defect width a, peak-to-valley spacing B y-fg It has a good linear relationship with the defect width a. The linear fitting method is adopted, and the fitting function is as follows: a=1.0512B y-fg -3.7066 When the defect depth is fixed at 5 mm, the leakage magnetic characteristic signal B corresponding to different defect widths x Peak B x-max The relationship with defect width is as follows Fig.10 As shown, it can be found from the figure that B x-max As the defect width a increases, B decreases. When the defect width increases from 5 mm to 30 mm, x-max In order to avoid the influence of defect width on defect depth inversion, a fitting function is set for every 5mm defect width to fit the defect depth b and B x-max relationship; When the defect depth is 2mm, 4mm, 6mm, 8mm, 10mm, and 12mm, the magnetic flux leakage detection device scans along the axial direction of the angle steel, and the sensor measures the signal B x like Fig.11 As shown; Extracting magnetic flux leakage signal B x The peak value of the fitting peak B x-max Relationship with defect depth b, B x-max It has a good linear relationship with the defect depth b. Using the linear fitting method, the fitting results in different ranges are as follows: Defect width a is in the range of 0 to 5 mm: b=0.004B y-fg +1.6592 Defect width a is in the range of 5 to 10 mm: b=0.0041B y-fg +1.7139 Defect width a is in the range of 10 to 15 mm: b=0.0048B y-fg +1.6751 Defect width a is in the range of 15 to 20 mm: b=0.0055B y-fg +1.5742 Defect width a is in the range of 20 to 25 mm: b=0.0061B y-fg +1.4756 Defect width a is in the range of 25 to 30 mm: b=0.0066B y-fg +1.4037 4) Measurement The actual transmission tower angle steel is tested, the magnetic field signal is scanned along the measurement trajectory, the magnetic field characteristic quantity is extracted, and the defect parameter information is obtained according to the fitting function. Six defects of different sizes are preset, and the comparison results of the actual defect size and the measured defect size are shown in Table 1 below. From the comparison between the measured data and the real data, it can be seen that the recognition error of the surface defect size of the transmission tower angle steel of the present invention is less than 1mm, and it has a good detection effect; Table 1 Comparison between true value and measured value

[0065] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for detecting corrosion defects of angle steel of a transmission tower body, characterized in that: The following steps are involved: Step S1: design an excitation device to saturate magnetize the angle steel of the transmission tower body; Step S2: Arrange Hall sensors to collect leakage magnetic signals; Step S3: filtering and extracting features of the magnetic flux leakage signal collected by the Hall sensor; Step S4: establishing a fitting relationship between defect parameters and magnetic flux leakage characteristic quantities; Step S5: quantitatively detect the size of the corrosion defects of the angle steel of the transmission tower body to be tested.

2. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 1, characterized in that: In step S1, for different types of transmission tower angle steel components, the finite element calculation method is used to determine the magnetic pole spacing L and the air gap δ; the first armature and the second armature are placed according to the magnetic pole spacing L, the permanent magnet N pole is placed on the first armature, and the permanent magnet S pole is placed on the second armature; the third armature is placed on the permanent magnet.

3. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 2, characterized in that: In step S2, the Hall sensor is arranged in the middle of the two magnetic poles of the permanent magnet, and a shielding box made of ferromagnetic material is provided outside the Hall sensor; the distance Δf between the Hall sensor and the surface of the angle steel of the transmission tower is determined by using a finite element calculation method.

4. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 3, characterized in that: In step S2, the excitation device and the Hall sensor with the shielding box are placed in a four-wheeled trolley to form a magnetic flux leakage detection device for detecting magnetic flux leakage signals on the surface of the angle steel of the transmission tower.

5. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 1, 2, 3 or 4, characterized in that: In step S3, the sliding average method is used to perform magnetic flux leakage signal filtering processing. By setting a fixed sliding window length, after the average value is calculated, it slides in sequence, and the output values ​​form a new sequence.

6. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 4, characterized in that: In step S3, the leakage magnetic signal feature is extracted through the time domain waveform, and the leakage magnetic signal B is selected. x The peak value of the component is used as the characteristic quantity for judging the defect depth, and the leakage magnetic signal B is selected y The peak-to-valley distance of the component is used as the characteristic quantity to judge the defect width.

7. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 6, characterized in that: In step S4, COMSO is used to establish a finite element simulation model of the transmission tower angle steel, and the finite element method is used to calculate the magnetic flux leakage distribution under different defect widths and different defect depths, and then a fitting relationship between the defect parameters and the magnetic flux leakage characteristic quantity is established. The fitting relationship is represented by a fitting function, including the defect depth-B x Component peak fitting function and defect width - B y Component peak-to-valley spacing fitting function.

8. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 7, characterized in that: In step S4, the defect width range is divided to establish the defect depth and leakage magnetic signal B under different defect width ranges. x The peak value of the component.

9. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 8, characterized in that: The specific process of step S5 includes the following steps: Step S51: the magnetic flux leakage detection device moves and scans on the surface of the angle steel of the transmission tower to obtain the magnetic flux leakage signal on the surface of the angle steel of the transmission tower; Step S52: Extracting the magnetic flux leakage signal B x The peak value and leakage magnetic signal of the component B y The peak-to-valley spacing of the components; Step S53: Transform the magnetic flux leakage signal B y Substitute the peak-to-valley spacing of the component into the defect width - B y The component peak-to-valley spacing fitting function is used to obtain the defect width information; Step S54: Based on the defect width information, the leakage magnetic signal B x Substitute the peak value of the component into the corresponding defect depth -B x Component peak fitting function is used to obtain defect depth information.

10. A method for detecting corrosion defects of angle steel of a transmission tower body according to claim 5, characterized in that: In step S5, for a signal x(n) containing N sampled data, its sliding average sequence is as follows: Where k is the sliding window length.

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