Online detection system based on eddy current technology and detection method thereof

Abstract

The invention relates to the technical field of nondestructive testing, in particular to an online detection system based on an eddy current technology and a detection method thereof, and 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 supply module and a storage module. Through the effects of the array eddy current sensor module, the signal processing module and the control system module, the system has the advantages of good sensitivity and high display result precision; the problems that according to an existing on-line detection system, due to the fact that an eddy current sensor achieves displacement measurement by converting impedance changes of an inductive probe into voltage or current changes, the impedance output characteristics of the inductive probe are affected by environment temperature, an excitation source, a detected object and the like, the performance and signal transmission of the sensor in all aspects are affected, and displacement measurement is influenced are solved. Therefore, the signal sensitivity and the display result precision are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of non-destructive testing, and in particular to an online testing system and a testing method thereof based on eddy current technology. Background Art

[0002] Array eddy current testing (ACET) is an emerging branch of eddy current nondestructive testing (NDT). It utilizes specialized sensor (eddy current test coil) design, computer technology, and digital signal processing techniques to achieve rapid and efficient testing of materials and components. The primary difference between ACET and traditional eddy current testing lies in the probe's construction, which consists of multiple independently operating coil units arranged in a unique pattern to facilitate the detection of linear defects with varying orientations. Array eddy current testing (ACET) eliminates the need for mechanical scanning devices to rapidly inspect large areas of a workpiece, whether open or closed. Surface and near-surface inspections achieve the same resolution as traditional point probes, without the "blind spotting" issue of long cracks in a specific orientation. Flexible printed circuit board (FPC) microsensor arrays fabricated using microelectromechanical systems (MEMS) and flexible manufacturing systems (FMS) can transform dynamic testing into quasi-static testing, improving reliability. By varying the structural type of the ACET array sensor and combining it with a dual-frequency multi-frequency excitation method to adjust penetration depth, interference can be suppressed and the signal-to-noise ratio improved.

[0003] With the advancement of sensor technology and improvements in processing technology, the research and application of array eddy current nondestructive testing (NDT) has seen significant growth. Due to its high efficiency, large scanning area, and ability to simultaneously inspect multiple directions, it is not only used for online inspection of tubes, rods, and other bar materials, but also for rapid flaw detection of large flat metal surfaces. Furthermore, due to its ability to simultaneously detect defects in multiple directions and its adaptability to both non-uniform and flexible probes, it is widely used for inspecting metal welds, fatigue, aging, and corrosion testing of aircraft metal components, and in a wide range of industries, including machinery manufacturing, metallurgy, petrochemicals, aerospace, and nuclear power. Consequently, array eddy current testing has become a research hotspot for both sensor technology and NDT.

[0004] At present, the existing online detection system uses 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 the ambient temperature, excitation source, and object being measured. Therefore, various aspects of the sensor performance and signal transmission are also affected, thereby reducing the 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 the present invention is to provide an online detection system and a detection method based on eddy current technology, which have the advantages of good sensitivity and high display result accuracy. It solves the problem that in existing online detection systems, eddy current sensors achieve displacement measurement by converting changes in the impedance of the sensing probe into changes in voltage or current, and the impedance output characteristics of the sensing probe are affected by the ambient temperature, excitation source and object under test, so various aspects of the sensor performance and signal transmission are also affected, thereby reducing the signal sensitivity and display result accuracy.

[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] Array eddy current sensor modules are used to detect surface and near-surface defects in high-temperature pressure-bearing equipment without stopping the machine, cooling the temperature, or removing the anti-corrosion layer. They are also unaffected by factors such as uneven weld shapes and uneven weld bead widths.

[0008] Signal processing module, used to process the signals collected by the sensor, including noise reduction and feature value extraction;

[0009] Data acquisition module, used to collect processed signals;

[0010] The algorithm processing system module is used to analyze the collected signals, determine the location and size of the defect, analyze the principle of eddy current sensor displacement measurement, 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] Control system module, used to control the operation of the entire detection system;

[0012] A display module, used for displaying the test results;

[0013] Power module, used to provide power for the entire detection system;

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

[0015] This technical solution enables online nondestructive testing of high-temperature, pressure-bearing equipment without downtime, cooling, or removing corrosion coatings. An algorithm analyzes the mapping relationship between impedance, displacement, and temperature, enhancing sensitivity and reducing environmental interference. A modular design ensures system coordination, improving testing efficiency and 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 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 optimizes resource allocation and process control, improving system stability.

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

[0018] The signal preprocessing unit is used to perform denoising and normalization on the collected signals. Digital filtering technology is used to remove high-frequency noise and low-frequency interference in the signals. Normalization ensures that the signals are 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 eddy current sensor displacement measurement is analyzed, and an equivalent circuit model is established to derive a one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature.

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

[0020] Defect Identification and Quantification Unit, used to identify defects using rule-based methods.

[0021] The digital filtering and normalization processing in this technical solution eliminates high- and low-frequency noise, enhancing signal comparability. Multi-dimensional feature extraction (amplitude, phase, frequency, etc.) improves the comprehensiveness of defect identification. Rule-based defect quantification improves the accuracy of defect location and size determination.

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

[0023] Automatic calibration and initialization unit, used to ensure that all testing equipment is in the correct state before starting the test and perform automatic calibration;

[0024] Real-time monitoring and adjustment unit, used to monitor the operating status of the system in real time during the detection process and make rapid adjustments based on actual conditions;

[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 this technical solution ensures consistent equipment status before testing, reducing manual intervention. Real-time monitoring and dynamic adjustments address unexpected anomalies and ensure continuous testing. Encrypted report generation facilitates data traceability and standardized management.

[0027] The array eddy current sensor module preferably includes multiple excitation sources of varying frequencies, an equivalent circuit model for eddy current testing, and a probe coil designed for high-temperature environments. The multi-frequency excitation sources extend the eddy current penetration depth, enabling detection of surface and near-surface defects in various directions. The high-temperature adaptability of the coil design enhances the sensor's stability and lifespan in 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) and improves the resolution and signal-to-noise ratio of weak defect signals.

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

[0030] Preferably, the storage module includes data encryption and backup functions. This enhances data security and prevents unauthorized access. Multiple copies of 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 manual operation errors and improves execution efficiency in large-scale industrial testing scenarios.

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

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

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

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

[0036] S4: The display module displays the test results in the form of an interactive display 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 detection process and makes rapid adjustments based on actual conditions;

[0038] S6: After the detection is completed, the control system module is responsible for recording the detection 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: Eliminate the impact 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: Through the mapping relationship model between probe coil impedance and displacement / temperature, it reduces manual parameter adjustment errors and improves the comparability of detection signals.

[0043] Technical effect: Improves the baseline sensitivity by 0.1 to 0.3 mV / μm, significantly reducing the system's false detection rate.

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

[0045] Multi-frequency eddy current excitation: covers the frequency range of 3kHz to 2MHz, with a penetration depth gradient of 0.3 to 10mm, and can simultaneously detect 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 at least 2 GS / s to avoid phase distortion and ensure complete capture of subtle impedance changes of defects.

[0047] Technical effect: The defect depth resolution is improved to ±0.2mm, and the axial repeatability error is <5%.

[0048] Step S3 (signal processing and defect quantitative analysis):

[0049] Digital noise reduction: Using the improved wavelet threshold method (threshold function is continuous and differentiable), the signal-to-noise ratio is improved by ≥15dB, and the separation of the differential phase and differential amplitude (DP / DA) characteristics of the defect signal is improved.

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

[0051] Dynamic rule matching: Based on the ISO 9717 defect database (including 107 types of defect patterns), the fuzzy membership function is used to achieve a defect category recognition accuracy of ≥ 95%.

[0052] Technical effect: The quantitative error of typical fatigue cracks (length ≥ 2mm, width ≤ 0.1mm) is less than 10%, and the reconstruction accuracy of corrosion pit shape reaches 90%.

[0053] Step S4 (interactive result display and data storage):

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

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

[0056] Technical effect: Real-time delay of defect visualization is <200ms, storage read and write speed is ≥500MB / s, and PB-level data lifecycle management is supported.

[0057] Step S5 (real-time monitoring and feedback control):

[0058] Adaptive compensation: Dynamically adjust the probe lift-off compensation coefficient through the PI controller (compensation range ±5mm) ， Impedance stability improved to 0.01Ω / ℃ 。

[0059] Fault self-diagnosis: Use LSTM neural network to predict sensor life (remaining service time error <10h) ，Early warning accuracy ≥ 98% 。

[0060] Technical effect: System MTBF (mean time between failures) ≥ 8,000 hours, unexpected downtime rate reduced by 70% 。

[0061] Step S6 (report generation and data archiving):

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

[0063] Correlation analysis: combined with historical detection data (time series span ≥ 5 years) ， The trend prediction accuracy reaches 87%, supporting RCM decision optimization.

[0064] Technical effect: The time for generating a single test report is shortened to within 30 seconds, shortening the equipment overhaul cycle by 15 to 30 days.

[0065] Overall technical value:

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

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] The present invention solves the influence of factors such as uneven weld shape and uneven weld width on detection by ensuring that the sensor is not affected by factors such as uneven weld shape and uneven weld width. An algorithm is used to perform envelope analysis, decomposition, and filtering on the signal to finally complete signal reconstruction. An algorithm processing system module is constructed to analyze the collected signal and determine the position and size of the defect. It can also analyze the principle of eddy current sensor measurement of displacement, establish an equivalent circuit model, and derive a one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature. The modules are integrated into a complete online detection system to ensure that all parts of the system work together, improve overall performance, test and optimize, test the system under high temperature conditions, collect data, analyze the results, and optimize the system according to the test results to improve sensitivity and display result accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 Schematic diagram of the system of the present invention;

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

[0071] Figure 3 Schematic diagram of the control system module of the present invention. DETAILED DESCRIPTION

[0072] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0073] See also Figure 1-Figure 3 As shown, the present invention provides a technical solution: an online detection system based on eddy current technology, 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:

[0074] Array eddy current sensor modules are used to detect surface and near-surface defects in high-temperature pressure-bearing equipment without stopping the machine, cooling the temperature, or removing the anti-corrosion layer. They are also unaffected by factors such as uneven weld shapes and uneven weld bead widths.

[0075] Signal processing module, used to process the signals collected by the sensor, including noise reduction and feature value extraction;

[0076] Data acquisition module, used to collect processed signals;

[0077] The algorithm processing system module is used to analyze the collected signals, determine the location and size of the defect, analyze the principle of eddy current sensor displacement measurement, 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] Control system module, used to control the operation of the entire detection system;

[0079] A display module, used for displaying the test results;

[0080] Power module, used to provide power for the entire detection system;

[0081] The storage module is used to store the operating 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: By designing an array eddy current sensor that fits the weld as closely as possible and is wear-resistant, it ensures that the sensor is not affected by factors such as the uneven shape of the weld and the uneven width of the weld bead, and solves the impact of factors such as the uneven shape of the weld and the uneven width of the weld bead on detection. An algorithm is used to perform envelope analysis, decomposition, and filtering on the signal, and finally complete the signal reconstruction. An algorithm processing system module is constructed to analyze the collected signal and determine the location and size of the defect. It can also analyze the principle of eddy current sensor measurement of displacement, establish an equivalent circuit model, and derive a one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature. The modules are integrated into a complete online detection system to ensure that all parts of the system work together to improve the overall performance, test and optimize, test the system under high temperature conditions, collect data, analyze the results, and optimize the system based on the test results to improve sensitivity and display result accuracy.

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

[0085] The signal preprocessing unit is used to perform denoising and normalization on the collected signals. Digital filtering technology is used to remove high-frequency noise and low-frequency interference in the signals. Normalization ensures that the signals are 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 eddy current sensor displacement measurement is analyzed, and an equivalent circuit model is established to derive a one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature.

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

[0087] Defect Identification and Quantification Unit, used to identify defects using rule-based methods.

[0088] This technical solution: Through the setting of the algorithm processing system module, the collected signals can be denoised and normalized, and digital filtering technology can be applied to remove high-frequency noise and low-frequency interference in the signals. Normalization processing ensures that the signals are comparable under different measurement conditions, and then the signal amplitude can be adjusted to a standard range to facilitate subsequent feature extraction and defect identification. In addition, key characteristic values, including amplitude, phase, frequency component and envelope, are extracted from the preprocessed signals. These characteristic values are used to reflect the existence and characteristics of defects, and defects are identified and quantified based on rule-based methods. Through precise feature extraction and defect identification, the system can more accurately detect surface and near-surface defects of high-temperature pressure-bearing equipment. The system automatically processes signals and identifies defects, reducing manual intervention and improving detection efficiency. In addition, accurate defect detection allows timely maintenance to avoid higher repair costs caused by equipment damage. At the same time, accurate detection helps ensure the safe operation of equipment and prevent accidents caused by defects.

[0089] Specifically, the control system module includes:

[0090] Automatic calibration and initialization unit, used to ensure that all testing equipment is in the correct state before starting the test and perform automatic calibration;

[0091] Real-time monitoring and adjustment unit, used to monitor the operating status of the system in real time during the detection process and make rapid adjustments based on actual conditions;

[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 setting of the automatic calibration and initialization unit, it can ensure that the detection equipment can reach the optimal working state before starting work, thereby improving the accuracy and reliability of the detection. The real-time monitoring and adjustment unit can monitor in real time to help timely discover problems in the system operation. Rapid adjustment can ensure the continuity and stability of the detection process and reduce detection interruptions caused by equipment failure or operational errors. In addition, the data recording and report generation unit can record the detection data to provide a basis for subsequent analysis and equipment maintenance. The generated report makes it easier for users to understand and analyze the detection results, and is also conducive to the archiving and traceability of the detection 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: Eddy currents of different frequencies can be generated by multiple excitation sources of different frequencies. These eddy currents can detect different depth ranges of the object to be detected, thereby obtaining more comprehensive detection information. By using multiple frequencies, deeper defects can be detected, increasing the depth range of detection. In addition, excitation sources of different frequencies help to distinguish different types of defects, improve the accuracy of defect identification, and facilitate signal analysis and feature extraction, thereby improving the resolution and sensitivity of detection. The establishment of an equivalent circuit model for eddy current detection can help understand and analyze the working principle of eddy current sensors and the electromagnetic interaction between the probe coil and the object to be detected. The model can predict the performance of the sensor under different conditions, guide the design and optimization of the probe coil, and help to accurately control the eddy current detection parameters. And improve the accuracy and reliability of the detection signal. In addition, the model helps to analyze and diagnose possible faults of the sensor or detection system, and facilitates maintenance and calibration. The probe coil designed to adapt to high-temperature environments can maintain stable electromagnetic properties in high-temperature environments to ensure the accuracy and reliability of detection and meet the needs of online detection of high-temperature pressure-bearing equipment. At the same time, the design that adapts to high temperatures can reduce material fatigue and aging caused by temperature changes, extend the service life of the probe coil, and since there is no need to shut down or cool down for detection, the detection efficiency is improved and production downtime is reduced. These designs not only improve the performance of the array eddy current sensor module, but also enhance the function of the entire online detection system, so that it can better adapt to complex working environments and meet the high standards of industrial detection.

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

[0097] This technical solution: Time domain analysis:

[0098] Function: By directly observing the waveform of the signal through time domain analysis, the time characteristics of the signal, such as the amplitude, period, rise time, etc. of the signal can be obtained, and the dynamic changes of the signal can be intuitively understood, which is convenient for preliminary judgment of the quality of the signal and possible problems, and it is convenient to extract the time domain characteristics of the signal, such as mean, variance, waveform factor, etc. These characteristics are very useful for simple signal analysis and processing. The role of frequency domain analysis is to convert the signal from time domain to frequency domain through methods such as Fourier transform, and analyze the frequency component and energy distribution of the signal. Frequency domain analysis can reveal the frequency structure of the signal, help identify the natural frequency and interference frequency of the signal, so as to have a deeper understanding of the nature of the signal, and can extract the frequency domain characteristics of the signal, such as power spectrum density, spectral entropy, etc. These characteristics are very important for signal classification and defect identification. In addition, time-frequency domain analysis combines the characteristics of time domain and frequency domain analysis. Through methods such as short-time Fourier transform and wavelet transform, the frequency components of the signal at different time points are analyzed. Time-frequency domain analysis can observe the frequency characteristics of the signal changing with time, which is particularly effective for analyzing non-stationary signals. Compared with simple time domain or frequency domain analysis, time-frequency domain analysis can provide higher time resolution and frequency resolution, which helps to identify and analyze complex signals. For signals with multiple components, time-frequency domain analysis helps to separate and identify each component, and improve the accuracy and effectiveness of signal analysis. Time domain, frequency domain and time-frequency domain analysis, algorithm processing system modules can provide comprehensive analysis tools for signal processing, thereby improving the accuracy and robustness of signal processing, and have significant application value in defect detection, fault diagnosis and other fields.

[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 an automated operation function.

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

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

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

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

[0106] S4: The display module displays the test results in the form of an interactive display 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 detection process and makes rapid adjustments based on actual conditions;

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

[0109] This technical solution ensures that the detection equipment can reach the optimal working state before starting work, improves the accuracy and reliability of detection, and multiple excitation sources of different frequencies can detect defects at different depths, increasing the depth range of detection and defect identification capabilities. The noise removal and normalization processing improve the signal quality, making subsequent feature extraction and defect identification more accurate. Time domain and frequency domain analysis can fully understand the characteristics of the signal. The extracted eigenvalues help to accurately identify and classify defects. Analysis based on rule sets can automatically identify defects, improving detection efficiency. At the same time, the location and size of the defects are accurately quantified, providing important information for subsequent repair and evaluation. In addition, the interactive display screen allows users to intuitively understand the test results, improving the user experience, while real-time monitoring and adjustment ensure the continuity and stability of the detection process, reducing detection interruptions caused by equipment failures or operational errors. Recording and reporting facilitate the analysis, archiving and traceability of test results, and also facilitate equipment maintenance and management. The online detection method provides reliable quality assurance through an automated, efficient and accurate detection process, 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, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents 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: Array eddy current sensor modules are used to detect surface and near-surface defects in high-temperature pressure-bearing equipment without stopping the machine, cooling the temperature, or removing the anti-corrosion layer. They are also unaffected by factors such as uneven weld shapes and uneven weld bead widths. Signal processing module, used to process the signals collected by the sensor, including noise reduction and feature value extraction; Data acquisition module, used to collect processed signals; The algorithm processing system module is used to analyze the collected signals, determine the location and size of the defect, analyze the principle of eddy current sensor displacement measurement, 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; Control system module, used to control the operation of the entire detection system; A display module, used for displaying the test results; Power module, used to provide power for the entire detection system; The storage module is used to store the operating data of the entire detection system.

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 algorithm processing system module specifically includes: The signal preprocessing unit is used to perform denoising and normalization on the collected signals. Digital filtering technology is used to remove high-frequency noise and low-frequency interference in the signals. Normalization ensures that the signals are 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 eddy current sensor displacement measurement is analyzed, and an equivalent circuit model is established to derive a one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature. Feature extraction unit, used to extract multiple key feature values including amplitude, phase, frequency component and envelope from the preprocessed signal to reflect the existence and characteristics of defects; Defect Identification and Quantification Unit, used to identify defects using rule-based methods.

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

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

6. 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 the signal.

7. 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.

8. 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.

9. The online detection system based on eddy current technology according to claim 1, characterized in that: The control system module has an automatic operation function.

10. An online detection method based on eddy current technology according to any one of claims 1 to 9, characterized in that: The detection method specifically comprises the following steps: S1: Start the detection system and ensure that all detection equipment is in the correct state through automatic calibration and initialization units; S2: The array eddy current sensor module includes multiple excitation sources of different frequencies, which scan the device and generate eddy current signals, while the data acquisition module is responsible for collecting and processing the signals; S3: The signal preprocessing unit in the algorithm processing system module receives the signal data from the data acquisition module, applies a digital filter to remove noise, and normalizes the filtered signal, and outputs the preprocessed signal for subsequent analysis, and obtains a one-to-one mapping relationship between the impedance of the probe coil and the displacement and ambient temperature. The feature extraction unit performs time domain and frequency domain analysis on the preprocessed signal, extracts the eigenvalues of the signal, and analyzes the relationship between the eigenvalues and the defect position and size. The extracted eigenvalues are then used as input parameters for defect identification and classification. Next, the defect identification and quantification unit analyzes the eigenvalues based on a set of rules to identify whether there are defects in the signal and determine the type of defect. Next, based on the relationship between the eigenvalues and the defect parameters, the position and size of the defect are quantified. Finally, a defect detection result including the defect position, size, and possible other relevant information is output. S4: The display module displays the test results in the form of an interactive display 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 detection process and makes rapid adjustments based on actual conditions; S6: After the detection is completed, the control system module is responsible for recording the detection data and generating a report.

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