Pipeline defect identification sensor, device and method

Abstract

The invention provides a pipeline defect identification sensor, device and method wherein the pipeline defect identification sensor comprises a magnet yoke, a high-frequency alternating current coil, a direct current coil and an induction coil; the magnet yoke comprises a cross beam and a side arm, and the cross beam is arranged on the side arm to form an open end; the high-frequency alternating-current coil is sleeved on a cross beam of the magnet yoke so as to apply sine alternating-current excitation and generate a detection magnetic field; the direct-current coil is sleeved on the side arm of the magnet yoke to apply direct-current excitation, so that the detection magnetic field is saturated or nearly saturated; the open end of the magnet yoke is located above the pipeline, so that the pipeline generates an eddy current field based on the saturated or near-saturated detection magnetic field; and the induction coil is arranged between the magnet yoke and the pipeline to induce an eddy current field generated by the pipeline to obtain an induction signal so as to detect pipeline defects.

Description

Technical Field

[0001] This invention belongs to the field of nondestructive testing technology, and specifically relates to a pipeline defect identification sensor, device, and method. Background Technology

[0002] Electromagnetic nondestructive testing (EDT) is a non-invasive testing method characterized by its non-contact, rapid, and accurate nature. It allows for inspection without damaging the target object and is widely used in pipeline engineering, aerospace, and power industries, providing crucial support for the safety and reliability of industrial facilities. In pipeline inspection, EDT utilizes the principle of electromagnetic field interaction to detect changes in pipe wall thickness, internal corrosion, defects, or other flaws to determine the pipe's health status and reliability.

[0003] The prior art discloses a method and apparatus for identifying internal and external wall cracks using focused magnetic flux leakage composite detection. This method is applied in the field of pipeline inspection. The apparatus includes: a magnetic focusing yoke, pole shoes or steel brushes, permanent magnets, and a yoke. The magnetic focusing yoke is positioned eccentrically and has an air gap between it and the test sample to form an end magnetic field focusing effect. The permanent magnets include two permanent magnets with opposite magnetization directions symmetrically distributed on the left and right sides, located above the pole shoes or steel brushes, for saturating the test sample. The yoke is located above the magnetic focusing yoke and the permanent magnets to form a saturation magnetization circuit. The pole shoes or steel brushes are symmetrically distributed below the two permanent magnets with opposite magnetization directions.

[0004] Existing methods are insufficient in detecting defects at different angles on the inner wall of pipes and defects at different depths on the inner and outer walls. They are also insufficient in detecting defects with small angles to magnetic field lines and are difficult to identify defect-like defects. AC electromagnetic field detection is suitable for detecting near-surface defects in ferromagnetic materials, but due to the skin effect, it is difficult to characterize the depth information of defects. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a pipeline defect identification sensor, device, and method to resolve the problems existing in the prior art.

[0006] This application discloses the following technical solution: a pipeline defect identification sensor, comprising: a magnetic yoke 1, a high-frequency AC coil 2, a DC coil 3, and an induction coil 4; the magnetic yoke 1 includes a crossbeam and a side arm, the crossbeam being disposed on the side arm to form an open end; the high-frequency AC coil 2 is sleeved on the crossbeam of the magnetic yoke 1, such that the central axis of the high-frequency AC coil 2 is aligned with the central axis of the crossbeam, to apply sinusoidal AC excitation and generate a detection magnetic field; the DC coil 3 is sleeved on the side arm of the magnetic yoke 1, such that the central axis of the DC coil 3 is aligned with the central axis of the corresponding side arm, to apply DC excitation and saturate or nearly saturate the detection magnetic field; the open end of the magnetic yoke 1 is located above the pipeline, so that the pipeline generates an eddy current field based on the saturated or nearly saturated detection magnetic field; the induction coil 4 is disposed between the magnetic yoke 1 and the pipeline to sense the eddy current field generated by the pipeline, obtain an induction signal, and detect pipeline defects.

[0007] This application also provides a pipeline defect identification device, comprising: a scanning module 5, a pipeline defect identification sensor as described in claim 1, a signal excitation module 6, and a storage module 7; the scanning module 5 is used to control the pipeline defect identification sensor to scan the pipeline; the signal excitation module 6 is connected to the high-frequency AC coil 2 to provide sinusoidal AC excitation to the high-frequency AC coil 2, and is connected to the DC coil 3 to provide DC excitation to the DC coil 3; the storage module 7 converts the induced signal into a voltage digital signal and stores it to detect pipeline defects.

[0008] Optionally, the AC excitation source 62 includes: a signal generator 621 and a power amplifier 622; the signal generator 621 is connected to the power amplifier 622 and is used to input a sinusoidal AC signal to the power amplifier; the power amplifier 622 is used to amplify the sinusoidal AC signal according to a set amplitude to generate the sinusoidal AC excitation.

[0009] Optionally, the storage module 7 includes: a signal collector 71 and an instruction unit 72; the signal collector 71 is used to perform analog-to-digital conversion processing on the sensed signal to obtain a voltage digital signal; the instruction unit 72 is connected to the collector and is used to analyze the defects of the pipe based on the voltage digital signal.

[0010] Optionally, the signal collector 71 includes: a signal conditioning module 711 and a data acquisition module 712; the signal conditioning module 711 is used to filter and amplify the induced signal to obtain a processed analog voltage signal; the data acquisition module 712 is connected to the signal conditioning module 711 and is used to perform analog-to-digital conversion processing on the processed analog voltage signal to obtain a digital voltage signal, and to store the digital voltage signal.

[0011] Optionally, the signal conditioning module 711 includes: a bandpass filter: the bandpass filter is used to filter and amplify the voltage analog signal in the induced signal.

[0012] Optionally, the bandpass filter includes: a high-pass filter, a low-pass filter, and an amplifier: the high-pass filter is used to filter low-frequency noise in the induced signal; the low-pass filter is used to filter high-frequency noise in the induced signal; and the amplifier is used to amplify the voltage analog signal in the induced signal.

[0013] Optionally, the instruction unit 72 includes: a calculator 721 and a three-axis worktable 722: the calculator 721 sends a scanning instruction to the three-axis worktable 722; the three-axis worktable 722 controls the pipeline defect identification sensor to scan the pipeline based on the scanning instruction.

[0014] Optionally, the data acquisition module 712 includes: an A / D conversion module and a data connection line; the A / D conversion module is connected to the signal conditioning module 711 and is used to perform analog-to-digital conversion on the processed analog voltage signal to obtain the digital voltage signal; one end of the data connection line is connected to the A / D conversion module and the other end is connected to the instruction unit 72 to transmit the digital voltage signal to the memory for storage.

[0015] This application also provides a pipeline defect identification method, comprising: controlling the pipeline defect identification sensor to scan the pipeline based on the scanning module 5; connecting the signal excitation module 6 to the high-frequency AC coil 2 in the pipeline defect identification sensor to provide sinusoidal AC excitation for the high-frequency AC coil 2, and connecting it to the DC coil 3 to provide DC excitation for the DC coil 3; detecting the eddy current field generated by the pipeline based on the pipeline defect identification sensor to obtain an induced signal; and converting the induced signal into a voltage digital signal based on the storage module 7 and storing it to detect pipeline defects.

[0016] This invention provides a pipeline defect identification sensor, device, and method. The pipeline defect identification sensor includes: a magnetic yoke 1, a high-frequency AC coil 2, a DC coil 3, and an induction coil 4. The magnetic yoke 1 includes a crossbeam and side arms. The crossbeam is disposed on the side arms to form an open end. The high-frequency AC coil 2 is sleeved on the crossbeam of the magnetic yoke 1, such that the central axis of the high-frequency AC coil 2 is aligned with the central axis of the crossbeam, to apply sinusoidal AC excitation and generate a detection magnetic field. The DC coil 3 is sleeved on the side arms of the magnetic yoke 1, such that the central axis of the DC coil 3 is aligned with the central axis of the corresponding side arm, to apply DC excitation and saturate or nearly saturate the detection magnetic field. The open end of the magnetic yoke 1 is located above the pipeline, so that the pipeline generates an eddy current field based on the saturated or nearly saturated detection magnetic field. The induction coil 4 is disposed between the magnetic yoke 1 and the pipeline to sense the eddy current field generated by the pipeline, obtain an induction signal, and detect pipeline defects. In this application, by combining the excitation methods of high-frequency AC coil 2 and DC coil 3, a saturated or near-saturated detection magnetic field can be generated. This strong magnetic field can more sensitively reflect changes in eddy currents in the pipeline, thereby improving the accuracy of defect detection. It can effectively identify even small or deep defects. Furthermore, the sensor applies the detection magnetic field to the pipeline through the open end of the magnetic yoke 1, without direct contact with the pipeline surface. This avoids friction and wear between the sensor and the pipeline, extending the sensor's lifespan and reducing the risk of damage to the pipeline surface. In addition, due to the use of high-frequency AC excitation, the sensor can quickly generate and detect changes in the eddy current field, thus achieving real-time detection of pipeline defects. This is particularly important for industrial applications requiring real-time monitoring. Moreover, this sensor is not only suitable for metal pipelines but can also be adapted to pipelines of different materials and sizes by adjusting the magnetic field parameters and sensor structure. Furthermore, it can detect defects on the inner and outer walls of pipelines, expanding its application range. The inductive signal obtained by the induction coil 4 can be directly used to analyze changes in eddy currents in the pipeline, thereby determining whether defects exist. This direct signal processing method simplifies the data processing flow and improves detection efficiency. Finally, since the sensor does not need to contact the pipeline during the detection process and uses the principle of electromagnetic induction, there are no safety hazards such as radiation or chemical corrosion, making it friendly to the health of operators and the environment. In summary, this invention can detect defects with small magnetic field line angles and deep defects, and identify the type of defect. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a pipeline defect identification sensor structure in this embodiment;

[0018] Figure 2 This is a schematic diagram of a pipeline defect identification device in this embodiment;

[0019] Figure 3 This is a flowchart of the data acquisition module in this embodiment;

[0020] Figure 4 This is a schematic diagram of the bandpass filter structure in this embodiment.

[0021] Figure 5 This embodiment presents a system block diagram of a pipeline defect identification method;

[0022] Figure 6 Experimental signal diagrams of defects at different angles on the inner wall in this embodiment;

[0023] Figure 7 This embodiment shows experimental signal diagrams of cracks at different depths on the inner wall.

[0024] Figure 8 This embodiment shows experimental signal diagrams of cracks at different depths on the outer wall. Detailed Implementation

[0025] Implementing any technical solution of the embodiments of this application does not necessarily require achieving all of the above advantages at the same time.

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Figure 1 This is a schematic diagram of a pipeline defect identification sensor structure in this embodiment; as shown. Figure 1The diagram illustrates a pipe defect identification sensor, comprising: a magnetic yoke 1, a high-frequency AC coil 2, a DC coil 3, and an induction coil 4. The magnetic yoke 1 includes a crossbeam and side arms, with the crossbeam positioned on the side arms to form an open end. The high-frequency AC coil 2 is sleeved on the crossbeam of the magnetic yoke 1, such that the central axis of the high-frequency AC coil 2 is aligned with the central axis of the crossbeam, to apply sinusoidal AC excitation and generate a detection magnetic field. The DC coil 3 is sleeved on the side arms of the magnetic yoke 1, such that the central axis of the DC coil 3 is aligned with the central axis of its respective side arm, to apply DC excitation, saturating or nearly saturating the detection magnetic field. The open end of the magnetic yoke 1 is located above the pipe, causing the pipe to generate an eddy current field based on the saturated or nearly saturated detection magnetic field. The induction coil 4 is positioned between the magnetic yoke 1 and the pipe to sense the eddy current field generated by the pipe, obtaining an induction signal to detect pipe defects. In this embodiment, by combining the excitation methods of high-frequency AC coil 2 and DC coil 3, a saturated or near-saturated detection magnetic field can be generated. This strong magnetic field can more sensitively reflect changes in eddy currents in the pipeline, thereby improving the accuracy of defect detection. It is particularly effective in identifying small or deep defects. Furthermore, the sensor applies the detection magnetic field to the pipeline through the open end of the magnetic yoke 1, without direct contact with the pipeline surface. This avoids friction and wear between the sensor and the pipeline, extending the sensor's lifespan and reducing the risk of damage to the pipeline surface. Additionally, due to the use of high-frequency AC excitation, the sensor can quickly generate and detect changes in the eddy current field, thus achieving real-time detection of pipeline defects. This is particularly important for industrial applications requiring real-time monitoring. Moreover, this sensor is not only suitable for metal pipelines but can also be adapted to pipelines of different materials and sizes by adjusting the magnetic field parameters and sensor structure. Furthermore, it can detect defects on the inner and outer walls of pipelines, expanding its application range. The inductive signal obtained by the induction coil 4 can be directly used to analyze changes in eddy currents in the pipeline, thereby determining whether defects exist. This direct signal processing method simplifies the data processing flow and improves detection efficiency. Finally, since the sensor does not need to contact the pipeline during the detection process and uses the principle of electromagnetic induction, there are no safety hazards such as radiation or chemical corrosion, making it friendly to the health of operators and the environment. In summary, this invention can detect defects with small magnetic field line angles and deep defects, and identify the type of defect.

[0028] Optionally, the magnetic yoke 1 is a U-shaped magnetic yoke 1. In this embodiment, the U-shaped magnetic yoke 1 helps to focus and guide the magnetic field lines to the area being detected, making the magnetic field distribution on the component under test more concentrated and uniform, thereby enhancing the magnetic field strength in the detection area and improving detection sensitivity. Furthermore, the U-shaped magnetic yoke 1 and the component under test easily form a closed magnetic circuit, which helps to ensure stable propagation of the magnetic field and stable acquisition of the detection signal.

[0029] Figure 2 This is a schematic diagram of a pipeline defect identification device in this embodiment; as shown. Figure 2 The diagram illustrates a pipeline defect identification device, comprising: a scanning module 5, a pipeline defect identification sensor, a signal excitation module 6, and a storage module 7. The scanning module 5 controls the pipeline defect identification sensor to scan the pipeline. The signal excitation module 6 is connected to the high-frequency AC coil 2 to provide sinusoidal AC excitation to the high-frequency AC coil 2, and is also connected to the DC coil 3 to provide DC excitation to the DC coil 3. The storage module 7 converts the induced signal into a voltage digital signal and stores it for detecting pipeline defects. In this embodiment, through the control of the scanning module 5, the pipeline defect identification sensor can systematically and comprehensively scan the pipeline, ensuring no blind spots, thereby greatly improving the efficiency and accuracy of defect detection. Furthermore, the signal excitation module 6 can simultaneously provide different types of excitation signals to the high-frequency AC coil 2 and the DC coil 3, enabling the device to adapt to different types and characteristics of pipeline defect detection needs, enhancing the device's versatility and flexibility. The storage module 7 not only converts the induced signal into a voltage digital signal but also has a storage function. This digital processing improves the accuracy and speed of signal processing, while facilitating subsequent data analysis and processing, providing reliable data support for later defect assessment. Furthermore, the use of sensors for scanning enables non-contact pipeline inspection. This method not only avoids pipeline damage that may result from traditional contact inspection but also allows inspection without stopping pipeline operation, significantly reducing the impact of inspection on pipeline operation. In addition, the modular design makes each part relatively independent, facilitating maintenance and upgrades. The non-contact inspection method reduces the possibility of personnel directly contacting the pipeline, lowering the risk of personal injury due to improper operation. At the same time, accurate defect detection helps to promptly identify and repair potential safety hazards, improving the overall safety of pipeline operation.

[0030] Optionally, the signal excitation module 6 includes: a DC regulated power source 61 and an AC excitation source 62; the DC regulated power source 61 is connected to the DC coil 3 to provide DC excitation to the DC coil 3, saturating or nearly saturating the detection magnetic field; the AC excitation source 62 is connected to the high-frequency AC coil 2 to provide sinusoidal AC excitation to the high-frequency AC coil 2, and the high-frequency AC coil 2 generates the detection magnetic field based on the sinusoidal AC excitation. In this embodiment, by combining the DC regulated power source 61 and the AC excitation source 62, the excitation of the DC coil 3 and the high-frequency AC coil 2 can be controlled separately, thereby achieving precise control of the detection magnetic field. This helps improve the detection accuracy and stability of the system. Moreover, the signal excitation module 6 has the characteristics of strong adjustability and a sound protection mechanism, which can adapt to different detection needs and environmental conditions, enhancing the flexibility and applicability of the system.

[0031] Optionally, the AC excitation source 62 includes: a signal generator 621 and a power amplifier 622; the signal generator 621 is connected to the power amplifier 622 and is used to input a sinusoidal AC signal to the power amplifier; the power amplifier 622 is used to amplify the sinusoidal AC signal according to a set amplitude to generate the sinusoidal AC excitation. The signal excitation module 6 uses the power amplifier 622 to amplify the sinusoidal waveform signal generated by the signal generator 621 and loads it onto both ends of the high-frequency AC coil 2 of the sensor, generating a uniform alternating electric field on the pipe surface. Simultaneously, a DC excitation signal generated by a DC regulated power supply is loaded onto both ends of the DC coil 3 of the sensor, saturating or nearly saturating the measured defect area. In this embodiment, the signal generator 621 can generate a high-precision sinusoidal AC signal, which is the basis for ensuring the accuracy of subsequent signal processing and analysis. A high-precision signal source can reduce signal distortion and noise interference, thereby improving the detection accuracy of the entire system. Furthermore, the signal generator 621 typically features multiple output waveforms and adjustable frequencies. Additionally, the gain of the power amplifier 622 can be adjusted to generate sinusoidal AC excitations of varying amplitudes, further enhancing the system's flexibility. Moreover, the power amplifier 622 amplifies the weak sinusoidal AC signal generated by the signal generator 621 according to a set amplitude, ensuring that the high-frequency AC coil 2 receives sufficient excitation current to generate a sufficiently strong detection magnetic field. This is crucial for improving the system's detection sensitivity and range.

[0032] Optionally, the storage module 7 includes: a signal collector 71 and an instruction unit 72; the signal collector 71 is used to perform analog-to-digital conversion on the induced signal to obtain a voltage digital signal; the instruction unit 72 is connected to the collector and is used to analyze the defects of the pipeline based on the voltage digital signal. In this embodiment, the signal collector 71 performs analog-to-digital conversion on the induced signal, converting the analog signal into a voltage digital signal. This process can significantly improve the accuracy and stability of the data, reduce noise and distortion that may be introduced during analog signal transmission and processing, and thus more accurately reflect the defect status of the pipeline. In addition, the instruction unit 72 is closely connected to the signal collector 71 and can receive and analyze the voltage digital signal in real time. This real-time processing capability enables the system to quickly respond to abnormal situations in the pipeline, promptly detect and locate defects, and improve the efficiency and accuracy of detection. Moreover, the instruction unit 72 is not only responsible for receiving data, but also has data analysis functions. It can intelligently analyze pipeline defects based on the voltage digital signal using preset algorithms and models.

[0033] Optionally, the command unit 72 includes: a calculator 721 and a three-axis worktable 722. The calculator 721 sends scanning commands to the three-axis worktable 722; based on the scanning commands, the three-axis worktable 722 controls the pipe defect identification sensor to scan the pipe. In this embodiment, by sending scanning commands from the calculator 721 to the three-axis worktable 722, automated control of pipe scanning is achieved. This not only reduces the burden of manual operation but also improves the accuracy and consistency of scanning, avoiding errors caused by human factors. Furthermore, the three-axis worktable 722 can precisely control the movement trajectory and speed of the pipe defect identification sensor on the pipe surface. This precise control ensures that the sensor can comprehensively and meticulously scan the pipe surface, without missing any potential defect areas. In addition, during the scanning process, the three-axis worktable 722 can also feed back the real-time data from the sensor to the calculator 721 for further processing and analysis. The calculator 721 can adjust the scanning strategy based on this data or issue timely warning signals so that operators can take timely measures. This data processing and feedback mechanism improves the system's response speed and decision-making capabilities.

[0034] Optionally, the signal collector 71 includes: a signal conditioning module 711 and a data acquisition module 712. The signal conditioning module 711 filters and amplifies the induced signal to obtain a processed analog voltage signal. The data acquisition module 712 is connected to the signal conditioning module 711 and performs analog-to-digital conversion on the processed analog voltage signal to obtain a digital voltage signal, and stores the digital voltage signal. In this embodiment, the signal conditioning module 711 filters and amplifies the induced signal, effectively removing noise and interference components from the signal while amplifying the useful signal, significantly improving the quality of the processed analog voltage signal. This helps the subsequent data acquisition module 712 to more accurately capture signal characteristics, improving the reliability and accuracy of the data. Furthermore, the design of the signal conditioning module 711 can be adjusted and optimized according to different induced signal characteristics and detection requirements. In addition, the data acquisition module 712 performs analog-to-digital conversion on the processed analog voltage signal to obtain a digital voltage signal. Because the processed signal has high quality, the error and distortion during the analog-to-digital conversion process are small, ensuring that the converted digital signal has high accuracy and stability.

[0035] Optionally, the signal conditioning module 711 includes a bandpass filter; the bandpass filter is used to filter the voltage analog signal in the induced signal. In this embodiment, the bandpass filter allows signals within a specific frequency range to pass through while suppressing noise and interference signals outside that range. In pipeline defect detection, the induced signal often contains many unnecessary noise components, which may originate from the environment, the equipment itself, or various factors during signal transmission. Through the filtering effect of the bandpass filter, these noises can be effectively removed, improving signal quality. Moreover, compared with other types of filters, the bandpass filter has a greater advantage in preserving useful signals. It can ensure that while filtering out noise, the waveform and amplitude of the useful signal are affected as little as possible, thereby maintaining the original characteristics of the signal. This is crucial for subsequent data analysis and processing, because accurate signal characteristics can more realistically reflect the pipeline defect situation. In addition, by filtering out noise and interference signals, the bandpass filter enables the detection system to capture useful signal characteristics more clearly. This helps to improve the sensitivity of the detection system, enabling the system to detect smaller defects or changes. Finally, the filtering range of the bandpass filter can be adjusted according to actual needs. By changing parameters such as the filter's cutoff frequency, it can be adapted to the signal filtering requirements of different frequency ranges. This flexibility allows the signal conditioning module 711 to be applicable to various detection scenarios and needs, improving the system's versatility and adaptability.

[0036] Figure 4 This is a schematic diagram of the bandpass filter structure in an embodiment of this application, as shown below. Figure 4As shown: Optionally, the bandpass filter includes: a high-pass filter, a low-pass filter, and an amplifier. The high-pass filter is used to filter low-frequency noise in the induced signal; the low-pass filter is used to filter high-frequency noise in the induced signal; and the amplifier is used to amplify the voltage analog signal in the induced signal. Because the voltage signal output by the induction coil 4 is extremely weak and has a low signal-to-noise ratio, making it difficult to acquire, a bandpass filter amplifier circuit composed of a low-pass filter and a high-pass filter is used to filter and amplify the defect detection voltage signal extracted from the induction coil 4, which has the same frequency as the AC excitation signal. This improves the signal-to-noise ratio, increases the identification of the defect response signal, and outputs the processing result. In this embodiment, the combined use of the high-pass filter and the low-pass filter effectively filters out low-frequency and high-frequency noise in the induced signal. This noise may originate from various factors in the environment, the equipment itself, or the signal transmission process, and it can mask or interfere with the useful defect detection signal. By filtering out this noise, the signal-to-noise ratio can be improved, making the useful defect detection signal more prominent and clear. Furthermore, the amplifier amplifies the filtered voltage analog signal, enhancing the signal strength. Because the voltage signal output by induction coil 4 is extremely weak, directly acquiring and processing this signal can be very difficult. Amplification by an amplifier makes the signal easier for the subsequent data acquisition module 712 to capture and process, improving the system's sensitivity and response speed. Furthermore, the signal after bandpass filtering and amplification has frequency characteristics consistent with the AC excitation signal, making the defect response signal more prominent and easier to identify in the frequency domain. This processing method helps reduce false alarms and missed alarms, improving the accuracy and reliability of the detection results. Finally, the entire bandpass filter amplification circuit is optimized for the signal characteristics output by induction coil 4, enabling the system to better adapt to detection scenarios with low signal-to-noise ratios and weak signals. This optimization not only improves detection efficiency but also reduces the requirements for subsequent processing circuits, helping to reduce costs and simplify the system structure.

[0037] Optionally, the high-pass filter includes: R101&C101, R102&C102, and R106&C106; R101&C101 is in series; R102&C102 is in series; R106&C106 is in series, and C101=C102=C106, R101=R102=R106=R109, the equivalent resistance of R101&C101 is R1, the equivalent resistance of R102&C102 is R2, and the equivalent resistance of R106&C106 is R6.

[0038] Optionally, the low-pass filter includes: R103 & C103, R104 & C104, and R107 & C107; R103 & C103 are in series; R104 & C104 are in series; R107 & C107 are in series, and C103 = C104 = C107, R103 = R104 = R107, the equivalent resistance of R103 & C103 is R3, the equivalent resistance of R104 & C104 is R4, and the equivalent resistance of R107 & C107 is R7. Optionally, the band-pass filter further includes: an SGM72 operational amplifier; amplification factor... VREF is the reference voltage. In AC mode: DC is blocked, and the input signal has no offset voltage Voffset. Adjusting VREF = VCC / 2 maximizes the measurement range. In DC mode: The input signal has an offset voltage Voffset, which, after amplification, results in a bias voltage Voffset*Av. Adjusting VREF = VCC / 2 - Voffset*Av maximizes the measurement range. Voffset = V+ - V-. Where V+ is the positive output terminal of the sensor, and V- is the negative output terminal. In this embodiment, the input signal passes through high-pass and low-pass filter networks to filter out unwanted low-frequency and high-frequency signals, respectively, allowing only signals within a specific frequency range to pass. The filtered signal then enters the SGM722 operational amplifier for amplification. The amplification factor is determined by the ratio of the feedback resistor to the input resistor. Reference voltage adjustment: The value of VREF is adjusted according to application requirements to set the reference voltage for the operational amplifier circuit. In AC conditions, the effect of offset voltage is eliminated by adjusting VREF to half of VCC; in DC conditions, offset voltage compensation needs to be considered. The amplified and reference voltage-adjusted signal is output from the output terminal of the operational amplifier circuit for subsequent signal processing or measurement. The use of high-precision capacitors and resistors, along with the low-noise SGM722 operational amplifier, helps improve circuit stability and reduce noise levels, thereby ensuring signal accuracy and reliability.

[0039] Optionally, the data acquisition module 712 includes: an A / D conversion module and a data connection line. The A / D conversion module is connected to the signal conditioning module 711 and is used to perform analog-to-digital conversion on the processed analog voltage signal to obtain the digital voltage signal. One end of the data connection line is connected to the A / D conversion module, and the other end is connected to the instruction setter 72 to transmit the digital voltage signal to the memory for storage. In this embodiment, the A / D conversion module is responsible for converting the processed analog voltage signal into a digital voltage signal. Since the A / D conversion module typically has high conversion accuracy and stability, it can ensure that the converted digital signal accurately reflects the characteristics of the original analog signal. This is crucial for subsequent data analysis and processing, as an accurate digital signal can provide more reliable detection results. Furthermore, the data connection line acts as a bridge between the A / D conversion module and the instruction setter 72, responsible for reliably transmitting the converted digital voltage signal to the memory for storage. Since the data connection line typically adopts a low-noise, high-interference-resistant design, it can effectively protect the signal quality during transmission and reduce signal distortion and interference. In addition, the data acquisition module 712, as part of the entire detection system, is designed with full consideration for integration and collaborative operation with other modules. The A / D conversion module is tightly connected to the signal conditioning module 711, enabling rapid conversion from analog to digital signals; the data connection line is connected to the instruction unit 72, enabling rapid transmission and storage of digital signals. This highly integrated design simplifies the system structure and improves the overall performance and reliability of the system. Finally, by converting analog signals to digital signals and transmitting them to the memory in real time, the data acquisition module 712 significantly improves detection efficiency. Digital signals are typically processed much faster than analog signals and are easier to automate and process intelligently. This helps to shorten the detection cycle and improve the real-time performance and accuracy of the detection results.

[0040] Optionally, the A / D conversion module includes: an operational amplifier, a digital-to-analog converter, a control logic unit, a successive asymptotic register, and an output port. The processed analog voltage signal is input to the operational amplifier for comparison with the analog reference signal generated by the digital-to-analog converter to obtain a comparison result, and the comparison result is input to the control logic unit. The control logic unit processes the clock signal generated by the high-low level transformation of the pulse source and the conversion control signal to obtain a processed control signal. The successive asymptotic register converts the comparison result into the digital voltage signal based on the processed control signal and stores the digital voltage signal internally. The digital-to-analog converter generates the analog reference signal based on the digital voltage signal and compares it with the processed analog voltage signal. The output port transmits the digital voltage signal to a memory for external storage via the data connection line. In this embodiment, the operational amplifier plays a crucial role in the A / D conversion process. It amplifies the weak processed analog voltage signal to enable accurate comparison with the analog reference signal generated by the digital-to-analog converter. This helps ensure that the converted digital voltage signal has high accuracy. Furthermore, the successive asymptotic register is one of the core components of the A / D conversion module. It employs a successive approximation algorithm to convert analog signals into digital signals. This conversion method gradually determines the value of each digital code by continuously approximating the true analog signal value, thus achieving high-precision conversion. Successive approximation A / D converters typically have high resolution and conversion accuracy. In addition, the digital-to-analog converter (DAC) in the A / D conversion module not only generates the analog reference signal but also participates in the conversion process, forming a closed-loop feedback system. In this system, the DAC generates an analog reference signal based on the voltage digital signal and compares it with the processed voltage analog signal. If a difference exists, the control logic unit adjusts the value of the successive asymptotic register until the comparison result meets certain accuracy requirements. This closed-loop feedback mechanism helps improve the accuracy and stability of the conversion. Finally, the control logic unit is responsible for processing the clock signal generated by the high-low level transition of the pulse source and the conversion control signal to generate the processed control signal. This flexible control logic allows the A / D conversion module to be adjusted and optimized according to different application scenarios and requirements, thereby improving the system's adaptability and flexibility.

[0041] Optionally, the data connection line transmits the voltage digital signal to the memory for external storage based on the UART serial port protocol. In this embodiment, the UART protocol only requires two data lines and a ground line to achieve bidirectional data transmission. This simple connection method reduces the complexity of hardware design and also reduces wiring costs.

[0042] Optionally, the magnetic yoke 1 is made of a high-permeability magnetic material. In this embodiment, the high-permeability magnetic material, under the action of an external magnetic field, has a much higher permeability than ordinary magnetic materials, enabling it to effectively absorb and concentrate the magnetic field and convert magnetic energy into its own energy. This characteristic allows the magnetic yoke 1 to more effectively concentrate and transmit the magnetic field, thereby improving the magnetic field efficiency of the entire system. Furthermore, due to the high permeability and low magnetic reluctance of the high-permeability magnetic material, energy loss is less during magnetic field transmission. This helps reduce the system's energy consumption and improve energy utilization efficiency.

[0043] Optionally, an air gap is formed between the open end of the magnetic yoke 1 and the pipe to ensure that the detection magnetic field satisfies the magnetic field boundary continuity condition. The magnetic permeability of the magnetic yoke 1 and the pipe is greater than that of air, and the magnetic field lines in the air gap are perpendicular to the boundaries between the air and the U-shaped magnetic yoke 1, and between the air gap and the pipe. When the air gap between the magnetic yoke 1 and the pipe is sufficiently small, the magnetic reluctance is very small. In this embodiment, when the air gap between the magnetic yoke 1 and the pipe is sufficiently small, the magnetic reluctance is significantly reduced. Since magnetic reluctance is an obstacle in the transmission of magnetic fields, reducing magnetic reluctance helps to enhance the transmission efficiency of the magnetic field, allowing more magnetic energy to be transmitted into the pipe, thereby improving the strength and effectiveness of the detection magnetic field. In addition, by satisfying the magnetic field boundary continuity condition, it can be ensured that the distribution of the magnetic field between the magnetic yoke 1, the air gap, and the pipe is more uniform and stable. This optimized magnetic field distribution helps to improve the sensitivity of the detection magnetic field, enabling even very small defects to be accurately detected. Furthermore, by designing the air gap between the magnetic yoke 1 and the pipe and satisfying the magnetic field boundary continuity condition, the size and weight of the equipment can be reduced without sacrificing the detection effect. This compact design helps save space, reduce costs, and improve the portability of the device. Finally, due to the reduced magnetoresistance and the focusing effect of the magnetic field, this design helps reduce energy loss during magnetic field transmission. This not only improves the energy efficiency ratio of the device but also reduces operating costs.

[0044] Optionally, the induction coil 4 is made of copper. The magnetic yoke 1 is positioned directly above the pipe defect and has an air gap between it and the pipe to form a defect magnetic field. The high-frequency AC coil 2 is located on the crossbeam of the magnetic yoke 1 and is uniformly wound to generate two opposite eddy current fields on the pipe surface directly below the magnetic yoke 1. The DC coil 3 is located at both ends of the sidewall of the magnetic yoke 1 and is symmetrically and uniformly wound to saturate or near-saturate the test area, increasing the background magnetic field and reducing the permeability. The induction coil 4 is located directly below the magnetic yoke 1 and is used to extract the changes in the magnetic field and eddy current fields in the specimen space caused by the presence of the defect. In this embodiment, the high-frequency AC coil 2 is uniformly wound on the crossbeam of the magnetic yoke 1, which can generate two opposite eddy current fields. These eddy current fields interact on the pipe surface, enhancing the complexity and sensitivity of the magnetic field in the defect detection area. At the same time, the DC coil 3 is symmetrically and uniformly wound at both ends of the sidewall of the magnetic yoke 1 to saturate or near-saturate the test area, increasing the background magnetic field strength and reducing the permeability, making the influence of the defect on the magnetic field and eddy current field more significant. In addition, the induction coil 4 is made of copper, which has good conductivity and thermal stability, and can accurately and quickly respond to changes in magnetic field and eddy current field. When defects exist in the pipeline, these changes will be captured by the induction coil 4 and converted into electrical signal output, providing reliable data support for subsequent defect analysis and evaluation.

[0045] Figure 5 This is a system block diagram of a pipeline defect identification method in this embodiment; as follows: Figure 4 As shown, based on a pipeline defect identification device in an embodiment of this application, this application also provides a pipeline defect identification method: The scanning module 5 controls the pipeline defect identification sensor to scan the pipeline; the signal excitation module 6 is connected to the high-frequency AC coil 2 in the pipeline defect identification sensor to provide sinusoidal AC excitation to the high-frequency AC coil 2, and is also connected to the DC coil 3 to provide DC excitation to the DC coil 3; the pipeline defect identification sensor detects and senses the eddy current field generated by the pipeline to obtain an induced signal; the storage module 7 converts the induced signal into a voltage digital signal and stores it to detect pipeline defects.

[0046] Optionally, the step of converting the induced signal into a voltage digital signal based on the storage module 7 and storing it to detect pipeline defects includes: filtering and amplifying the induced signal based on the signal conditioning module 711 to obtain a processed voltage analog signal; and performing analog-to-digital conversion on the processed voltage analog signal based on the data acquisition module 712 connected to the signal conditioning module 711 to obtain a voltage digital signal, and storing the voltage digital signal.

[0047] Optionally, the connection between the signal excitation module 6 and the high-frequency AC coil 2 to provide sinusoidal AC excitation for the high-frequency AC coil 2, and the connection between the signal excitation module 6 and the DC coil 3 to provide DC excitation for the DC coil 3, includes: connecting the signal generator 621 and the power amplifier 622 to input a sinusoidal AC signal to the power generator; and amplifying the sinusoidal AC signal according to a set amplitude using the power amplifier 622 to generate the sinusoidal AC excitation. By applying excitation to the coil, a corresponding magnetic field and eddy current field are generated in the pipe. Due to the defect, the magnetic flux in the original magnetic circuit inside the pipe is distorted, and the magnetic lines of force are deflected at both ends of the defect, bypassing the defect area and leaking above the defect to form a leakage magnetic field. Due to the presence of the defect, the conductivity in this area is discontinuous, causing the direction of the induced current to be deflected, bypassing the two ends and the bottom of the defect, and the induced current accumulates at both ends of the defect. The distortion of the magnetic field and eddy current field caused by the defect on the surface of the specimen is extracted using the induction coil 4. The signal excitation module 6 uses a power amplifier 622 to amplify the sinusoidal waveform signal generated by the signal generator 621, and applies it to both ends of the high-frequency AC coil 2 of the sensor, generating a uniform alternating electric field on the surface of the pipe. Simultaneously, a DC excitation signal generated by a DC regulated power supply is applied to both ends of the DC coil 3 of the sensor, saturating or nearly saturating the tested defect area. The signal excitation module 6 uses a power amplifier 622 to amplify the high-frequency sinusoidal waveform signal generated by the signal generator 621, and applies it to both ends of the high-frequency AC coil 2 of the sensor, generating a uniform alternating electric field on the surface of the specimen. Simultaneously, a DC excitation signal generated by a DC regulated power supply is applied to both ends of the DC coil 3 of the sensor, saturating or nearly saturating the tested pipe.

[0048] Optionally, the defect detection voltage signal output from the induction coil 4 is filtered and amplified based on the bandpass filter amplifier circuit in the signal conditioning module 711. Because the voltage signal output from the induction coil 4 is extremely weak and has a low signal-to-noise ratio, making it difficult to acquire, the signal conditioning module 711 uses a bandpass filter amplifier circuit composed of a low-pass filter and a high-pass filter to filter and amplify the defect detection voltage signal extracted from the induction coil 4 that has the same frequency as the AC excitation signal. This improves the signal-to-noise ratio, increases the recognition accuracy of the defect response signal, and outputs the processing result.

[0049] Optionally, the high-pass filter performs filtering based on the following formula:

[0050] Where f1 is the high-pass cutoff frequency; R1 is the high-pass filter resistor; and C1 is the high-pass filter capacitor.

[0051] Optionally, the low-pass filter performs filtering based on the following formula:

[0052] Where f2 is the low-pass cutoff frequency; R2 is the low-pass filter resistor; and C2 is the low-pass filter capacitor.

[0053] The induced voltage in induction coil 4 is calculated based on the following formula:

[0054]

[0055] Wherein, V is the induced voltage in the induction coil 4; N is the number of turns of the coil; Φ is the magnetic flux; B_f is the magnetic induction intensity; and S is the area through which the magnetic field lines pass.

[0056] Optionally, the step of connecting the data acquisition module 712 and the signal conditioning module 711 to perform analog-to-digital conversion on the processed analog voltage signal to obtain a digital voltage signal, and storing the digital voltage signal, includes: connecting the A / D conversion module to the signal conditioning module 711 to perform analog-to-digital conversion on the processed analog voltage signal to obtain the digital voltage signal; and connecting one end of a data connection line to the A / D conversion module and the other end to the instruction unit 72 to transmit the digital voltage signal to the memory for storage.

[0057] The analog signal output by the induction coil 4 is filtered and amplified by the signal conditioning module 711 and then input to the data acquisition module 712. The analog signal is compared with the analog reference signal by the operational amplifier and then input to the control logic unit. When the conversion control signal changes from low level to high level, the pulse source generates a clock signal. At this time, the signal is stored in the register and connected to the computer via USB cable. The digital signal data of the signal is sent to the computer via the UART serial port protocol.

[0058] Figure 6 This is an experimental signal diagram of defects at different angles on the inner wall in this embodiment; Figure 7 This is an experimental signal diagram of cracks at different depths on the inner wall in this embodiment; Figure 8 This example shows experimental signal diagrams of cracks at different depths on the outer wall in this embodiment. A 0.3mm wide inner wall angle crack was also shown. Cracks at different angles (0°, 15°, 30°, 45°, 60°, 75°, and 90°) with dimensions of 24mm × 0.3mm × 1mm (length × width × depth) were also included. The waveforms detected by the pipeline defect identification device are shown below. Figure 6 As shown: the horizontal axis represents the number of samples, and the vertical axis represents the applied voltage value. When the crack angle gradually approaches 90° from 0°, the peak values ​​of the two opposite eddy current fields detected by the pipeline defect identification device gradually approach each other.

[0059] A 0.5mm wide inner wall crack, at a 90° angle to the detection direction, with depths of 1mm, 2mm, 3mm, 4mm, 5mm, 6mm, and 7mm, and all other dimensions being 24×0.5mm (length×width), is detected using a pipeline defect identification device. The waveform is shown below. Figure 7 As shown: the horizontal axis represents the number of samples, and the vertical axis represents the applied voltage value. As the crack depth gradually increases, the peak values ​​of the two opposite eddy current fields detected by the pipeline defect identification device gradually increase.

[0060] A 0.5mm wide outer wall crack, forming a 90° angle with the detection direction, with depths of 1mm, 2mm, 3mm, 4mm, 5mm, 6mm, and 7mm, and all other dimensions being 24×0.5mm (length×width), is detected using a pipeline defect identification device. The waveform is shown below. Figure 8 As shown: the horizontal axis represents the number of samples, and the vertical axis represents the applied voltage value. As the crack depth gradually increases, the peak values ​​of the two opposite eddy current fields detected by the pipeline defect identification device gradually increase.

[0061] The present application will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. In fact, those skilled in the art will recognize that modifications and variations can be made to the present application without departing from the scope or spirit thereof. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. Therefore, it is desirable that the present application encompass such modifications and variations that fall within the scope of the appended claims and their equivalents.

[0062] In the description of this application, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," and "bottom," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and do not require that this application be constructed and operated in a specific orientation, and therefore should not be construed as limiting this application. The terms "connected," "linked," and "set up" used in this application should be interpreted broadly. For example, they can refer to a fixed connection or a detachable connection; they can refer to a direct connection or an indirect connection through intermediate components. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

Claims

1. A pipeline defect identification sensor, characterized in that, include: Magnetic yoke (1), high-frequency AC coil (2), DC coil (3) and induction coil (4); The magnetic yoke (1) includes a crossbeam and a side arm, the crossbeam being disposed on the side arm to form an open end; The high-frequency AC coil (2) is sleeved on the crossbeam of the magnetic yoke (1), so that the central axis of the high-frequency AC coil (2) is aligned with the central axis of the crossbeam, so as to apply sinusoidal AC excitation and generate a detection magnetic field; The DC coil (3) is sleeved on the side arm of the magnetic yoke (1) so that the central axis of the DC coil (3) is aligned with the central axis of the side arm to apply DC excitation and saturate or nearly saturate the detection magnetic field. The open end of the magnetic yoke (1) is located above the pipe, so that the pipe generates an eddy current field based on the saturated or near-saturated detection magnetic field; The induction coil (4) is positioned between the magnetic yoke (1) and the pipe to sense the eddy current field generated by the pipe and obtain an induction signal to detect pipe defects.

2. A pipeline defect identification device, characterized in that, include: The scanning module (5), the pipeline defect identification sensor as described in claim 1, the signal excitation module (6), and the storage module (7) are as follows: The scanning module (5) is used to control the pipeline defect identification sensor to scan the pipeline; The signal excitation module (6) is connected to the high-frequency AC coil (2) to provide sinusoidal AC excitation for the high-frequency AC coil (2), and is also connected to the DC coil (3) to provide DC excitation for the DC coil (3). The storage module (7) converts the sensing signal into a voltage digital signal and stores it to detect pipeline defects.

3. The pipeline defect identification device according to claim 2, characterized in that, The signal excitation module (6) includes: a DC regulated power source (61) and an AC excitation source (62); the DC regulated power source (61) is connected to the DC coil (3) to provide DC excitation for the DC coil (3) so that the detection magnetic field is saturated or nearly saturated; the AC excitation source (62) is connected to the high-frequency AC coil (2) to provide sinusoidal AC excitation for the high-frequency AC coil (2), and the high-frequency AC coil (2) generates a detection magnetic field based on the sinusoidal AC excitation.

4. The pipeline defect identification device according to claim 2, characterized in that, The storage module (7) includes: a signal collector (71) and an instruction unit (72); The signal collector (71) is used to perform analog-to-digital conversion on the induced signal to obtain a voltage digital signal; The instruction unit (72) is connected to the collector and is used to analyze the defects of the pipe based on the voltage digital signal.

5. A pipeline defect identification device according to claim 4, characterized in that, The signal collector (71) includes: a signal conditioning module (711) and a data acquisition module (712). The signal conditioning module (711) is used to filter and amplify the induced signal to obtain a processed voltage analog signal; The data acquisition module (712) is connected to the signal conditioning module (711) and is used to perform analog-to-digital conversion on the processed analog voltage signal to obtain a digital voltage signal, and to store the digital voltage signal.

6. A pipeline defect identification device according to claim 5, characterized in that, The signal conditioning module (711) includes: a bandpass filter: The bandpass filter is used to filter and amplify the voltage analog signal in the induced signal.

7. A pipeline defect identification device according to claim 6, characterized in that, The bandpass filter includes: a high-pass filter, a low-pass filter, and an amplifier. The high-pass filter is used to filter low-frequency noise in the sensed signal; The low-pass filter is used to filter high-frequency noise in the sensed signal; The amplifier is used to amplify the voltage analog signal in the induced signal.

8. A pipeline defect identification device according to claim 4, characterized in that, The instruction unit (72) includes: a calculator (721) and a three-axis worktable (722). The calculator (721) sends a scanning command to the three-axis worktable (722); The three-axis worktable (722) controls the pipeline defect identification sensor to scan the pipeline based on the scanning command.

9. A pipeline defect identification device according to claim 8, characterized in that, The data acquisition module (712) includes: an A / D conversion module and a data connection cable. The A / D conversion module is connected to the signal conditioning module (711) and is used to perform analog-to-digital conversion on the processed voltage analog signal to obtain the voltage digital signal; One end of the data connection line is connected to the A / D conversion module, and the other end is connected to the instruction unit (72) to transmit the voltage digital signal to the memory for storage.

10. A method for identifying pipeline defects, characterized in that, include: The scanning module (5) controls the pipeline defect identification sensor to scan the pipeline; The signal excitation module (6) is connected to the high-frequency AC coil (2) in the pipeline defect identification sensor to provide sinusoidal AC excitation to the high-frequency AC coil (2), and is connected to the DC coil (3) to provide DC excitation to the DC coil (3); Based on the detection of pipeline defect identification sensors, the eddy current field generated by the pipeline is sensed to obtain the sensing signal; The storage module (7) converts the sensing signal into a voltage digital signal and stores it to detect pipeline defects.

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