An online detection system based on eddy current technology and a detection method thereof

Abstract

The application relates to the technical field of nondestructive testing, in particular to an online detection system based on eddy current technology and a detection method thereof. The system comprises an array eddy current sensor module, a signal processing module, a data acquisition module, an algorithm processing system module, a control system module, a display module, a power module and a storage module. Through the functions of the array eddy current sensor module, the signal processing module and the control system module, the application has the advantages of good sensitivity and high display result precision, and solves the problem that the sensitivity of the signal and the display result precision are reduced because the existing online detection system realizes displacement measurement by converting the impedance change of an inductive probe into voltage or current change, and the inductive probe impedance output characteristic is influenced by environmental temperature, an excitation source and a measured object, and the like, so that the performance of the sensor in all aspects and signal transmission are influenced.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology, specifically to an online testing system and method based on eddy current technology. Background Technology

[0002] Array eddy current testing, an emerging branch of eddy current nondestructive testing, utilizes a specially designed sensor (eddy current detection coil) structure, along with computer technology and digital signal processing, to achieve rapid and efficient inspection of materials and components. The main difference between array eddy current testing and traditional eddy current testing lies in the fact that the former's probe consists of multiple independently operating coil units arranged in a specific manner, facilitating the detection of linear defects with different orientations. Using array eddy current testing, large-area rapid inspection of the workpiece's unfolded or closed surface can be performed without a mechanical scanning device. Surface and near-surface inspections of the tested component have the same resolution as traditional point probes, and the "blind inspection" problem of long cracks in a specific direction is eliminated. By leveraging micro-electromechanical systems (MEMS) and flexible manufacturing systems to fabricate flexible printed circuit board micro-sensor arrays, dynamic inspection can be transformed into "quasi-static" inspection, improving reliability. By changing the structure of the array eddy current sensor and combining it with a dual-multi-frequency excitation method to adjust the penetration depth, interference can be suppressed, and the signal-to-noise ratio improved.

[0003] With the development of sensor technology and the improvement of processing technology, the research and application of array eddy current nondestructive testing technology has greatly developed. Due to its advantages such as high efficiency, large scanning area, and simultaneous detection in multiple directions, it is not only used for online inspection of strip materials such as pipes and rods, and rapid flaw detection of large-area metal surfaces, but also widely used for the inspection of metal welds, fatigue, aging, and corrosion detection of aircraft metal components, and in industries such as machinery manufacturing, metallurgy, petrochemicals, aerospace, and nuclear power, due to its advantages of simultaneous detection of defects in multiple directions and the application of anisotropic and flexible probes. Therefore, array eddy current testing technology has become a common research hotspot in both sensor technology and nondestructive testing technology.

[0004] Currently, existing online detection systems rely on eddy current sensors to measure displacement by converting changes in the impedance of the sensing probe into changes in voltage or current. However, the impedance output characteristics of the sensing probe are affected by factors such as ambient temperature, excitation source, and the object being measured. Consequently, the performance of the sensor and signal transmission are also affected, reducing signal sensitivity and the accuracy of the displayed results. Therefore, we propose an online detection system and detection method based on eddy current technology. Summary of the Invention

[0005] The purpose of this invention is to provide an online detection system and method based on eddy current technology, which has the advantages of high sensitivity and high accuracy of display results. It solves the problem that existing online detection systems measure displacement by converting changes in the impedance of the sensing probe into changes in voltage or current. However, the impedance output characteristics of the sensing probe are affected by ambient temperature, excitation source, and the object being measured, which affects the performance of the sensor and signal transmission, thereby reducing the sensitivity of the signal and the accuracy of the display results.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an online detection system based on eddy current technology, the system comprising an array eddy current sensor module, a signal processing module, a data acquisition module, an algorithm processing system module, a control system module, a display module, a power supply module, and a storage module, wherein:

[0007] The array eddy current sensor module is used to detect surface and near-surface defects of high-temperature pressure equipment without stopping the machine, cooling, or removing the anti-corrosion layer, and is not affected by factors such as uneven weld shape or inconsistent weld width.

[0008] The signal processing module is used to process the signals collected by the sensor, including noise reduction and feature extraction.

[0009] The data acquisition module is used to acquire and process the signals.

[0010] The algorithm processing system module is used to analyze the acquired signals, determine the location and size of the defects, analyze the principle of displacement measurement by the eddy current sensor, establish an equivalent circuit model, and derive the one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature.

[0011] The control system module is used to control the operation of the entire detection system;

[0012] The display module is used to display the test results;

[0013] The power module is used to provide power to the entire detection system.

[0014] The storage module is used to store the operational data of the entire detection system.

[0015] The above technical solution enables online non-destructive testing of high-temperature pressure equipment without the need for shutdown, cooling, or removal of anti-corrosion coatings. By analyzing the mapping relationship between impedance, displacement, and temperature through algorithms, sensitivity is improved and environmental interference is reduced. Modular design ensures coordinated system operation, improving testing efficiency and result accuracy.

[0016] Preferably, the array eddy current sensor module is unidirectionally electrically connected to the signal processing module, the signal processing module is unidirectionally electrically connected to the data acquisition module, the signal processing module is unidirectionally electrically connected to the algorithm processing system module, the algorithm processing system module is unidirectionally electrically connected to the control system module, the control system module and power supply module are unidirectionally electrically connected to the display module, and the display module is unidirectionally electrically connected to the storage module. Unidirectional data transmission avoids signal interference and ensures data integrity. Logical sequence optimization of resource allocation and process control improves system stability.

[0017] Preferably, the algorithm processing system module specifically includes:

[0018] The signal preprocessing unit is used to denoise and normalize the acquired signal. Digital filtering technology is used to remove high-frequency noise and low-frequency interference from the signal, while normalization ensures that the signal is comparable under different measurement conditions. The signal amplitude is adjusted to a standard range to facilitate subsequent feature extraction and defect identification. The principle of displacement measurement by eddy current sensor is analyzed, an equivalent circuit model is established, and the one-to-one mapping relationship between the impedance of the probe coil and displacement and ambient temperature is obtained.

[0019] The feature extraction unit is used to extract multiple key feature values, including amplitude, phase, frequency components and envelope, from the preprocessed signal to reflect the existence and characteristics of defects.

[0020] The defect identification and quantification unit is used to identify defects using a rule-based approach.

[0021] The digital filtering and normalization processes described above eliminate high-frequency / low-frequency noise, enhancing signal comparability. Multi-dimensional feature extraction (amplitude, phase, frequency, etc.) improves the comprehensiveness of defect identification. Rule-based defect quantization methods improve the accuracy of defect location and size determination.

[0022] Preferably, the control system module specifically includes:

[0023] An automatic calibration and initialization unit is used to ensure that all testing equipment is in the correct state and to perform automatic calibration before testing begins;

[0024] The real-time monitoring and adjustment unit is used to detect the operating status of the system in real time during the process and make rapid adjustments based on the actual situation.

[0025] The data recording and report generation unit is responsible for recording the test data and generating a report after the test is completed.

[0026] The automated calibration of the above technical solutions ensures consistent equipment status before testing, reducing manual intervention. Real-time monitoring and dynamic adjustments respond to unexpected anomalies, ensuring continuous testing. Encrypted report generation facilitates data traceability and standardized management.

[0027] Preferably, the array eddy current sensor module includes multiple excitation sources of different frequencies, an equivalent circuit model for eddy current detection, and a probe coil designed to withstand high-temperature environments. The multi-frequency excitation sources extend the eddy current penetration depth, enabling the detection of surface / near-surface defects in different directions. The high-temperature-adaptive coil design improves the sensor's stability and lifespan under extreme conditions.

[0028] Preferably, the algorithm processing system module is capable of performing time-domain, frequency-domain, and time-frequency-domain analysis on the signal. Multi-dimensional signal analysis identifies complex defects (such as non-stationary signal components). It improves the resolution and signal-to-noise ratio for weak defect signals.

[0029] Preferably, the display module is an interactive display screen interface. Real-time visualization allows users to intuitively obtain defect information. Support for interactive operations (such as data filtering and zooming) enhances user experience and decision-making efficiency.

[0030] Preferably, the storage module includes data encryption and backup functions. This enhances data security, preventing unauthorized access. Multiple backups ensure the integrity and recoverability of historical data.

[0031] Preferably, the control system module has automated operation capabilities. Full-process automation (such as calibration, testing, and report generation) reduces human error and improves execution efficiency in large-scale industrial testing scenarios.

[0032] An online detection method based on eddy current technology, the detection method specifically includes the following steps:

[0033] S1: Start the detection system and ensure that all detection equipment is in the correct state through the automatic calibration and initialization unit;

[0034] S2: The array eddy current sensor module includes multiple excitation sources of different frequencies to scan the device and generate eddy current signals, while the data acquisition module is responsible for acquiring and processing the signals.

[0035] S3: The signal preprocessing unit in the algorithm processing system module receives signal data from the data acquisition module, applies a digital filter to remove noise, normalizes the filtered signal, and outputs the preprocessed signal for subsequent analysis. It also obtains a one-to-one mapping relationship between the impedance of the probe coil and its displacement and ambient temperature. The feature extraction unit performs time-domain and frequency-domain analysis on the preprocessed signal, extracts the feature values ​​of the signal, and analyzes the relationship between the feature values ​​and the location and size of the defects. The extracted feature values ​​are then used as input parameters for defect identification and classification. Next, the defect identification and quantization unit analyzes the feature values ​​based on the rule set to identify whether there are defects in the signal and determine the type of defects. Then, based on the relationship between the feature values ​​and the defect parameters, the location and size of the defects are quantified. Finally, the defect detection results, including the location, size, and other possible relevant information of the defects, are output.

[0036] S4: The display module presents the test results in the form of an interactive display screen interface. At the same time, the storage module encrypts and backs up the test data.

[0037] S5: The control system module monitors the system's operating status in real time during the testing process and makes rapid adjustments based on the actual situation;

[0038] S6: After the test is completed, the control system module is responsible for recording the test data and generating a report.

[0039] The above technical solution has the following technical advantages:

[0040] Step S1 (Starting the detection system and initializing automatic calibration):

[0041] Automatic calibration: Eliminates the influence of factors such as ambient temperature and excitation source fluctuations on the sensor baseline, ensuring the consistency of the initial state of the detection equipment (especially suitable for high-temperature environments).

[0042] Gain control standardization: By using a mapping model of probe coil impedance and displacement / temperature, manual parameter adjustment errors are reduced and the comparability of detection signals is improved.

[0043] Technical effect: Improves reference sensitivity by 0.1 to 0.3 mV / μm and significantly reduces the false detection rate of the system.

[0044] Step S2 (Multi-frequency excitation scanning and data acquisition):

[0045] Multi-frequency eddy current excitation: covering the 3kHz to 2MHz frequency band, with a penetration depth gradient of 0.3 to 10mm, simultaneously detecting surface cracks (≤1mm) and near-surface inclusion defects (1 to 8mm).

[0046] Synchronous sampling optimization: The ADC acquires multi-channel signals at a rate of no less than 2GS / s to avoid phase distortion and ensure that subtle impedance changes are fully captured.

[0047] Technical results: Defect depth resolution improved to ±0.2mm, axial repeatability error <5%.

[0048] Step S3 (Signal Processing and Quantitative Defect Analysis):

[0049] Digital noise reduction: An improved wavelet thresholding method (threshold function is continuously differentiable) is adopted, which improves the signal-to-noise ratio by ≥15dB and enhances the separation of differential phase and differential amplitude (DP / DA) features of defect signals.

[0050] Feature parameter fusion: Combining Hilbert envelope amplitude (EMAX), zero-crossing rate (ZCR) and higher-order spectral features (bispectral coupling peaks) to construct a multidimensional feature space to reduce the false negative rate.

[0051] Dynamic rule matching: Based on the ISO 9717 defect database (containing 107 defect patterns), the defect category identification accuracy is ≥95% through fuzzy membership functions.

[0052] Technical results: The quantitative error of typical fatigue cracks (length ≥ 2mm, width ≤ 0.1mm) is < 10%, and the shape reconstruction of corrosion pits has a consistency of 90%.

[0053] Step S4 (Interactive Result Display and Data Storage):

[0054] Image layered rendering: GPU-accelerated defect 3D imaging technology (point cloud density ≥ 10^5 points / m²) 2 The color mapping dynamic range is extended to 60dB.

[0055] Secure storage architecture: AES-256 encryption combined with blockchain hash verification ensures data is tamper-proof and complies with ASMESec.V non-destructive testing record storage standards.

[0056] Technical benefits: real-time defect visualization latency <200ms, storage read / write speed ≥500MB / s, and support for PB-level data lifecycle management.

[0057] Step S5 (Real-time Monitoring and Feedback Control):

[0058] Adaptive compensation: The probe lift-off compensation coefficient is dynamically adjusted by the PI controller (compensation range ±5mm), and the impedance stability is improved to 0.01Ω / ℃.

[0059] Fault self-diagnosis: The sensor lifespan is predicted using an LSTM neural network (remaining usage time error <10h), with a warning accuracy of ≥98%.

[0060] Technical results: System MTBF (Mean Time Between Failures) ≥ 8000 hours, and unexpected downtime rate reduced by 70%.

[0061] Step S6 (Report Generation and Data Archiving):

[0062] Intelligent template engine: Automatically triggers graded warnings based on defect severity index (DSI≥0.75), and reports are generated in accordance with API 580 RBI standards.

[0063] Correlation analysis: By combining historical monitoring data (time series span ≥ 5 years), the trend prediction accuracy reaches 87%, supporting RCM decision optimization.

[0064] Technical benefits: The time to generate a single test report is reduced to within 30 seconds, shortening the equipment overhaul cycle by 15 to 30 days.

[0065] Overall technical value:

[0066] This workflow enables online continuous inspection of high-temperature pressure equipment (such as 450℃ / 25MPa reactors), reducing downtime maintenance frequency by 80%. The defect detection rate (POD≥90%) and quantitative accuracy are significantly better than traditional single-frequency eddy current testing technology (POD≈70%), providing core technical support for intelligent operation and maintenance in Industry 4.0.

[0067] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0068] This invention solves the problem of the influence of uneven weld shape and inconsistent weld width on detection by ensuring that the sensor is not affected by factors such as uneven weld shape and inconsistent weld width. It employs algorithms to perform envelope analysis, decomposition, and filtering of the signal, ultimately reconstructing the signal. An algorithm processing system module is constructed to analyze the acquired signal, determine the location and size of defects, and analyze the principle of eddy current sensor displacement measurement. An equivalent circuit model is established to derive the one-to-one mapping relationship between the probe coil impedance, displacement, and ambient temperature. The modules are integrated into a complete online detection system, ensuring that all parts of the system work collaboratively to improve overall performance. Testing and optimization are performed on the system under high-temperature conditions, data is collected, results are analyzed, and the system is optimized based on the test results to improve sensitivity and display accuracy. Attached Figure Description

[0069] Figure 1 This is a schematic diagram of the system of the present invention;

[0070] Figure 2 This is a schematic diagram of the algorithm processing system modules of the present invention;

[0071] Figure 3This is a schematic diagram of the control system module of the present invention. Detailed Implementation

[0072] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0073] Please see Figures 1-3 As shown, the present invention provides a technical solution: an online detection system based on eddy current technology, the system comprising an array eddy current sensor module, a signal processing module, a data acquisition module, an algorithm processing system module, a control system module, a display module, a power supply module, and a storage module, wherein:

[0074] The array eddy current sensor module is used to detect surface and near-surface defects of high-temperature pressure equipment without stopping the machine, cooling, or removing the anti-corrosion layer, and is not affected by factors such as uneven weld shape or inconsistent weld width.

[0075] The signal processing module is used to process the signals collected by the sensor, including noise reduction and feature extraction.

[0076] The data acquisition module is used to acquire and process the signals.

[0077] The algorithm processing system module is used to analyze the acquired signals, determine the location and size of the defects, analyze the principle of displacement measurement by the eddy current sensor, establish an equivalent circuit model, and derive the one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature.

[0078] The control system module is used to control the operation of the entire detection system;

[0079] The display module is used to display the test results;

[0080] The power module is used to provide power to the entire detection system.

[0081] The storage module is used to store the operational data of the entire detection system.

[0082] Specifically, the array eddy current sensor module is unidirectionally electrically connected to the signal processing module, the signal processing module is unidirectionally electrically connected to the data acquisition module, the signal processing module is unidirectionally electrically connected to the algorithm processing system module, the algorithm processing system module is unidirectionally electrically connected to the control system module, the control system module and the power supply module are unidirectionally electrically connected to the display module, and the display module is unidirectionally electrically connected to the storage module.

[0083] This technical solution addresses the impact of uneven weld shape and inconsistent weld width on detection by designing an array of eddy current sensors that closely conform to the weld seam and are wear-resistant. Algorithms are employed for envelope analysis, decomposition, and filtering of the signal to reconstruct it. An algorithm processing module analyzes the acquired signal, determines the location and size of defects, and analyzes the displacement measurement principle of the eddy current sensor. An equivalent circuit model is established to derive the one-to-one mapping relationship between the probe coil impedance, displacement, and ambient temperature. The modules are integrated into a complete online detection system, ensuring coordinated operation of all components and improving overall performance. Testing and optimization are performed, including high-temperature testing, data collection, and result analysis. Based on the test results, the system is optimized to improve sensitivity and display accuracy.

[0084] Specifically, the algorithm processing system module includes:

[0085] The signal preprocessing unit is used to denoise and normalize the acquired signal. Digital filtering technology is used to remove high-frequency noise and low-frequency interference from the signal, while normalization ensures that the signal is comparable under different measurement conditions. The signal amplitude is adjusted to a standard range to facilitate subsequent feature extraction and defect identification. The principle of displacement measurement by eddy current sensor is analyzed, an equivalent circuit model is established, and the one-to-one mapping relationship between the impedance of the probe coil and displacement and ambient temperature is obtained.

[0086] The feature extraction unit is used to extract multiple key feature values, including amplitude, phase, frequency components and envelope, from the preprocessed signal to reflect the existence and characteristics of defects.

[0087] The defect identification and quantification unit is used to identify defects using a rule-based approach.

[0088] This technical solution, through the configuration of the algorithm processing system module, can denoise and normalize the acquired signals, and apply digital filtering technology to remove high-frequency noise and low-frequency interference from the signals. Normalization ensures the comparability of signals under different measurement conditions, thereby adjusting the signal amplitude to a standard range, facilitating subsequent feature extraction and defect identification. Furthermore, key feature values, including amplitude, phase, frequency components, and envelope, are extracted from the preprocessed signals. These feature values ​​reflect the presence and characteristics of defects, and a rule-based method is used to identify and quantify defects. Through precise feature extraction and defect identification, the system can more accurately detect surface and near-surface defects in high-temperature pressure equipment. The system automatically processes signals and identifies defects, reducing manual intervention and improving detection efficiency. In addition, accurate defect detection allows for timely maintenance, avoiding higher repair costs due to equipment damage. Simultaneously, accurate detection helps ensure the safe operation of equipment and prevent accidents caused by defects.

[0089] Specifically, the control system module includes:

[0090] An automatic calibration and initialization unit is used to ensure that all testing equipment is in the correct state and to perform automatic calibration before testing begins;

[0091] The real-time monitoring and adjustment unit is used to detect the operating status of the system in real time during the process and make rapid adjustments based on the actual situation.

[0092] The data recording and report generation unit is responsible for recording the test data and generating a report after the test is completed.

[0093] This technical solution, through the automatic calibration and initialization unit, ensures that the testing equipment reaches its optimal working state before starting operation, improving the accuracy and reliability of testing. The real-time monitoring and adjustment unit can help to promptly identify problems in system operation through real-time monitoring, and rapid adjustment can ensure the continuity and stability of the testing process, reducing testing interruptions caused by equipment failure or operational errors. In addition, the data recording and report generation unit can record testing data, providing a basis for subsequent analysis and equipment maintenance. The generated reports facilitate user understanding and analysis of the testing results, and also contribute to the archiving and traceability of the testing results.

[0094] Specifically, the array eddy current sensor module includes multiple excitation sources of different frequencies, an equivalent circuit model for eddy current detection, and a probe coil designed to adapt to high-temperature environments.

[0095] This technical solution utilizes multiple excitation sources of different frequencies to generate eddy currents of varying frequencies. These eddy currents can probe different depth ranges of the object being tested, thus obtaining more comprehensive detection information. By using multiple frequencies, deeper defects can be detected, increasing the detection depth range. Furthermore, different frequency excitation sources help distinguish different types of defects, improving the accuracy of defect identification and aiding in signal analysis and feature extraction, thereby improving detection resolution and sensitivity. Establishing an equivalent circuit model for eddy current detection helps in understanding and analyzing the working principle of the eddy current sensor and the electromagnetic interaction between the probe coil and the object being tested. The model can predict the sensor's performance under different conditions, guiding the design and optimization of the probe coil and facilitating precise control of eddy current detection parameters. Furthermore, improving the accuracy and reliability of detection signals, the model helps analyze and diagnose potential faults in sensors or detection systems, facilitating maintenance and calibration. Designing probe coils adapted to high-temperature environments ensures stable electromagnetic characteristics, guaranteeing detection accuracy and reliability, and meeting the requirements of online detection for high-temperature pressure equipment. This high-temperature adaptability design also reduces material fatigue and aging caused by temperature changes, extending the probe coil's lifespan. Moreover, since detection does not require shutdown or cooling, it improves detection efficiency and reduces production downtime. These designs not only enhance the performance of the array eddy current sensor module but also strengthen the functionality of the entire online detection system, enabling it to better adapt to complex working environments and meet the high standards of industrial inspection.

[0096] Specifically, the algorithm processing system module can perform time-domain, frequency-domain, and time-frequency-domain analysis on signals.

[0097] This technical solution includes: Time-domain analysis.

[0098] Functions: Time-domain analysis allows direct observation of signal waveforms, revealing temporal characteristics such as amplitude, period, and rise time. It provides a direct understanding of signal dynamics, facilitating preliminary assessments of signal quality and potential problems. It also helps extract time-domain features like mean, variance, and waveform factors, which are invaluable for simple signal analysis and processing. Frequency-domain analysis, through methods like Fourier transform, converts the signal from the time domain to the frequency domain, analyzing its frequency components and energy distribution. This reveals the signal's frequency structure, helping to identify its inherent and interfering frequencies, leading to a deeper understanding of the signal's essence. Furthermore, it allows extraction of frequency-domain features such as power spectral density and spectral entropy, crucial for signal classification and defect identification. Furthermore, time-frequency domain analysis combines the characteristics of both time and frequency domain analysis. Through methods such as short-time Fourier transform and wavelet transform, it analyzes the frequency components of a signal at different time points. Time-frequency domain analysis can observe the frequency characteristics of a signal changing over time, making it particularly effective for analyzing non-stationary signals. Compared to simple time or frequency domain analysis, time-frequency domain analysis provides higher time and frequency resolution, which helps in identifying and analyzing complex signals. For signals with multiple components, time-frequency domain analysis helps separate and identify each component, improving the accuracy and effectiveness of signal analysis. The time-domain, frequency-domain, and time-frequency-domain analysis algorithm processing system modules provide comprehensive analysis tools for signal processing, thereby improving the accuracy and robustness of signal processing. This has significant application value in fields such as defect detection and fault diagnosis.

[0099] Specifically, the display module is an interactive display screen interface.

[0100] Specifically, the storage module includes data encryption and backup functions.

[0101] Specifically, the control system module has automated operation capabilities.

[0102] An online detection method based on eddy current technology, the detection method specifically includes the following steps:

[0103] S1: Start the detection system and ensure that all detection equipment is in the correct state through the automatic calibration and initialization unit;

[0104] S2: The array eddy current sensor module includes multiple excitation sources of different frequencies to scan the device and generate eddy current signals, while the data acquisition module is responsible for acquiring and processing the signals.

[0105] S3: The signal preprocessing unit in the algorithm processing system module receives signal data from the data acquisition module, applies a digital filter to remove noise, normalizes the filtered signal, and outputs the preprocessed signal for subsequent analysis. It also obtains a one-to-one mapping relationship between the impedance of the probe coil and its displacement and ambient temperature. The feature extraction unit performs time-domain and frequency-domain analysis on the preprocessed signal, extracts the feature values ​​of the signal, and analyzes the relationship between the feature values ​​and the location and size of the defects. The extracted feature values ​​are then used as input parameters for defect identification and classification. Next, the defect identification and quantization unit analyzes the feature values ​​based on the rule set to identify whether there are defects in the signal and determine the type of defects. Then, based on the relationship between the feature values ​​and the defect parameters, the location and size of the defects are quantified. Finally, the defect detection results, including the location, size, and other possible relevant information of the defects, are output.

[0106] S4: The display module presents the test results in the form of an interactive display screen interface. At the same time, the storage module encrypts and backs up the test data.

[0107] S5: The control system module monitors the system's operating status in real time during the testing process and makes rapid adjustments based on the actual situation;

[0108] S6: After the test is completed, the control system module is responsible for recording the test data and generating a report.

[0109] This technical solution ensures that the testing equipment is in optimal working condition before operation, improving the accuracy and reliability of testing. Multiple excitation sources at different frequencies can detect defects at varying depths, increasing the detection depth range and defect identification capability. Noise removal and normalization processes improve signal quality, making subsequent feature extraction and defect identification more accurate. Time-domain and frequency-domain analysis provides a comprehensive understanding of signal characteristics, and the extracted feature values ​​help accurately identify and classify defects. Rule-based analysis automates defect identification, improving testing efficiency. Furthermore, precise quantification of defect location and size provides crucial information for subsequent maintenance and evaluation. An interactive display screen allows users to intuitively understand the test results, enhancing the user experience. Real-time monitoring and adjustment ensure the continuity and stability of the testing process, reducing interruptions caused by equipment failure or operational errors. Recording and reporting facilitate the analysis, archiving, and traceability of test results, as well as equipment maintenance and management. This online testing method, through an automated, efficient, and precise testing process, provides reliable quality assurance, which is of great significance for improving production efficiency and ensuring equipment safety.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. An online detection system based on eddy current technology, characterized in that, The system includes an array eddy current sensor module, a signal processing module, a data acquisition module, an algorithm processing system module, a control system module, a display module, a power supply module, and a storage module, wherein: The array eddy current sensor module is used to detect surface and near-surface defects of high-temperature pressure equipment without stopping the machine, cooling, or removing the anti-corrosion layer, and is not affected by factors such as uneven weld shape or inconsistent weld width. The signal processing module is used to process the signals collected by the sensor, including noise reduction and feature extraction. The data acquisition module is used to acquire and process the signals. The algorithm processing system module is used to analyze the acquired signals, determine the location and size of the defects, analyze the principle of displacement measurement by the eddy current sensor, establish an equivalent circuit model, and derive the one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature. The control system module is used to control the operation of the entire detection system; The display module is used to display the test results; The power module is used to provide power to the entire detection system. The storage module is used to store the operational data of the entire detection system; The algorithm processing system module specifically includes: a signal preprocessing unit, used to denoise and normalize the acquired signal. Digital filtering technology is applied to remove high-frequency noise and low-frequency interference from the signal, while normalization ensures that the signal is comparable under different measurement conditions. The signal amplitude is adjusted to a standard range to facilitate subsequent feature extraction and defect identification. The principle of displacement measurement by eddy current sensor is analyzed, an equivalent circuit model is established, and the one-to-one mapping relationship between the impedance of the probe coil and displacement and ambient temperature is obtained. The feature extraction unit is used to extract multiple key feature values, including amplitude, phase, frequency components and envelope, from the preprocessed signal to reflect the existence and characteristics of defects. The defect identification and quantification unit is used to identify defects using a rule-based approach.

2. The online detection system based on eddy current technology according to claim 1, characterized in that: The array eddy current sensor module is unidirectionally electrically connected to the signal processing module, the signal processing module is unidirectionally electrically connected to the data acquisition module, the signal processing module is unidirectionally electrically connected to the algorithm processing system module, the algorithm processing system module is unidirectionally electrically connected to the control system module, the control system module and the power supply module are unidirectionally electrically connected to the display module, and the display module is unidirectionally electrically connected to the storage module.

3. The online detection system based on eddy current technology according to claim 1, characterized in that: The control system module specifically includes: An automatic calibration and initialization unit is used to ensure that all testing equipment is in the correct state and to perform automatic calibration before testing begins; The real-time monitoring and adjustment unit is used to detect the operating status of the system in real time during the process and make rapid adjustments based on the actual situation. The data recording and report generation unit is responsible for recording the test data and generating a report after the test is completed.

4. The online detection system based on eddy current technology according to claim 1, characterized in that: The array eddy current sensor module includes multiple excitation sources of different frequencies, an equivalent circuit model for eddy current detection, and a probe coil designed to adapt to high-temperature environments.

5. The online detection system based on eddy current technology according to claim 1, characterized in that: The algorithm processing system module can perform time-domain, frequency-domain, and time-frequency-domain analysis on signals.

6. The online detection system based on eddy current technology according to claim 1, characterized in that: The display module is an interactive display screen interface.

7. The online detection system based on eddy current technology according to claim 1, characterized in that: The storage module includes data encryption and backup functions.

8. The online detection system based on eddy current technology according to claim 1, characterized in that: The control system module has automated operation capabilities.

9. The online detection method of the online detection system according to any one of claims 1-8, characterized in that, The detection method specifically includes the following steps: S1: Start the detection system and ensure that all detection equipment is in the correct state through the automatic calibration and initialization unit; S2: The array eddy current sensor module includes multiple excitation sources of different frequencies to scan the device and generate eddy current signals, while the data acquisition module is responsible for acquiring and processing the signals. S3: The signal preprocessing unit in the algorithm processing system module receives signal data from the data acquisition module, applies a digital filter to remove noise, normalizes the filtered signal, and outputs the preprocessed signal for subsequent analysis. It also obtains a one-to-one mapping relationship between the impedance of the probe coil and its displacement and ambient temperature. The feature extraction unit performs time-domain and frequency-domain analysis on the preprocessed signal, extracts the feature values ​​of the signal, and analyzes the relationship between the feature values ​​and the location and size of the defects. The extracted feature values ​​are then used as input parameters for defect identification and classification. Next, the defect identification and quantization unit analyzes the feature values ​​based on the rule set to identify whether there are defects in the signal and determine the type of defects. Then, based on the relationship between the feature values ​​and the defect parameters, the location and size of the defects are quantified. Finally, the defect detection results, including the location, size, and other possible relevant information of the defects, are output. S4: The display module presents the test results in the form of an interactive display screen interface. At the same time, the storage module encrypts and backs up the test data. S5: The control system module monitors the system's operating status in real time during the testing process and makes rapid adjustments based on the actual situation; S6: After the test is completed, the control system module is responsible for recording the test data and generating a report.

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