Nondestructive testing and noise filtering method, system and equipment and storage medium

Abstract

The invention discloses a nondestructive testing and noise filtering method, system and device and a storage device. The nondestructive testing and noise filtering method comprises the steps that first detection data obtained when a diamond NV color center is subjected to magnetic flux leakage detection are collected; wherein the first detection data at least comprises feedback fluorescence and a scanning position corresponding to the feedback fluorescence; converting the feedback fluorescence into a fluorescence electric signal, and performing noise reduction processing on the fluorescence electric signal by using a first adaptive denoising algorithm; and calculating and analyzing the signal after noise reduction processing to obtain magnetic field information. According to the method, the leakage magnetic field of the ferromagnetic material defect is detected through the high-sensitivity NV color center magnetic sensor, and the self-developed adaptive wavelet threshold denoising method is combined, so that the environmental noise is effectively inhibited, and the weak magnetic field signal is accurately extracted; a quantum precision measurement platform is built based on the NV color center magnetic sensor, and detection of extremely tiny cracks can be achieved; the microwave frequency is supported to dynamically adjust the sensitivity so as to adapt to different detection requirements, and the detection precision and adaptability in a complex industrial environment are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of non-destructive testing and precision measurement, and particularly to a non-destructive testing and noise filtering method, system, device and storage medium. Background Art

[0002] With the continuous improvement of the precision and safety requirements of industrial equipment, the importance of non-destructive testing technology in the fields of material defect identification, structural health monitoring, etc. has become increasingly prominent. Although traditional non-destructive testing methods such as ultrasonic testing and X-ray testing are widely used, they still have problems such as insufficient sensitivity or limited applicability in some special scenarios. In recent years, the quantum magnetic sensing technology based on diamond nitrogen-vacancy (NV) centers has provided a new solution for high-precision non-destructive testing due to its high sensitivity, high spatial resolution and room-temperature working characteristics.

[0003] The diamond NV center is a solid-state spin system with optical readability, and its ground state energy level is extremely sensitive to external magnetic fields. Through laser excitation and microwave regulation, nano-scale magnetic field measurement can be realized, which is especially suitable for the detection of micro-cracks on the surface of ferromagnetic materials. However, in the actual detection process, the NV center sensor is easily affected by environmental noise, resulting in a decrease in the signal-to-noise ratio, and further affecting the accuracy of defect identification. Therefore, how to effectively filter out noise and retain useful signals has become one of the key problems in improving the detection performance of NV centers.

[0004] Traditional wavelet threshold denoising methods (such as hard threshold and soft threshold) have obvious limitations in noise processing. The hard threshold method directly removes noise by retaining wavelet coefficients greater than the threshold. Although it can avoid signal amplitude deviation, it is discontinuous at the threshold point and is prone to Gibbs oscillations; the soft threshold method shrinks all coefficients greater than the threshold. Although it can ensure continuity, it will introduce amplitude attenuation, resulting in over-smoothing of the signal. Both of these methods are difficult to achieve an ideal balance between noise suppression and signal fidelity.

[0005] In view of the above problems, there is an urgent need for an adaptive wavelet denoising algorithm that can dynamically adjust the threshold function according to the noise intensity. Developing a non-destructive testing system that combines the high-sensitivity magnetic sensing of diamond NV centers with an adaptive wavelet denoising algorithm is of great significance for promoting the application of quantum sensing technology in the field of industrial testing. Summary of the Invention

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the problem solved by the non-destructive testing and noise filtering method, system, device and storage medium provided by the present invention is that when extracting weak magnetic field signals in non-destructive testing based on diamond NV centers, it is difficult for traditional wavelet threshold denoising methods (hard threshold and soft threshold) to balance noise suppression and signal fidelity, resulting in limited crack detection accuracy.

[0008] To solve the above technical problems, the present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides a non-destructive testing and noise filtering method, including:

[0010] Collecting first detection data obtained during magnetic flux leakage detection using diamond NV centers; the first detection data includes at least the feedback fluorescence and its corresponding scanning position;

[0011] Converting the feedback fluorescence into a fluorescence electrical signal, and performing noise reduction processing on the fluorescence electrical signal using a first adaptive denoising algorithm;

[0012] Performing calculation and analysis on the signal after the noise reduction processing to obtain magnetic field information.

[0013] As a preferred solution of the non-destructive testing and noise filtering method of the present invention, wherein: the magnetic flux leakage detection includes:

[0014] Scanning a magnetized workpiece using diamond NV centers;

[0015] Irradiating the diamond NV centers with excitation laser and radiating microwaves to detect the first detection data generated by the diamond NV centers under the action of the microwave field and the excitation laser.

[0016] As a preferred solution of the non-destructive testing and noise filtering method of the present invention, wherein: the performing noise reduction processing on the fluorescence electrical signal using the first adaptive denoising algorithm includes:

[0017] Comparing the absolute value of the fluorescence electrical signal with a preset first threshold;

[0018] When the absolute value of the fluorescence electrical signal is greater than or equal to the first threshold, the calculation of the signal after noise reduction is: the fluorescence electrical signal minus the result of the first calculation adjustment based on the absolute value of the difference between the fluorescence electrical signal and the first threshold;

[0019] When the absolute value of the fluorescence electrical signal is less than the first threshold, the signal after noise reduction is determined by an exponential function depending on the absolute value of the difference between the fluorescence electrical signal and the first threshold.

[0020] The beneficial effects of this preferred technical solution are as follows: By using a continuously differentiable threshold function between the soft and hard thresholds, significant signals are retained in the strong noise region, and features are finely extracted in the weak noise region, avoiding the Gibbs oscillation or signal over-smoothing problems of traditional methods, and improving the signal-to-noise ratio and defect recognition accuracy.

[0021] As a preferred solution of the non-destructive testing and noise filtering method described in the present invention, wherein: the magnetized workpiece to be tested includes:

[0022] The ferromagnetic material to be tested is magnetized by a magnetizer to generate a leakage magnetic field on its surface defects;

[0023] The position of the magnetizer corresponds to the color center probe of the diamond NV color center, so that the color center probe can sense the defect leakage magnetic field formed by the magnetizer.

[0024] As a preferred solution of the non-destructive testing and noise filtering method described in the present invention, wherein: in the magnetic flux leakage detection, a laser with a wavelength of 532 nm is used as the excitation laser for irradiating the diamond NV color center.

[0025] In a second aspect, the present invention provides a non-destructive testing and noise filtering system, including a detection module, a signal acquisition and processing module, a laser module, and a microwave module;

[0026] The detection module includes an NV color center probe and a magnetizer;

[0027] The NV color center probe includes a diamond NV color center, a microwave antenna, and an optical fiber. When the NV color center probe works, the excitation laser is transmitted through the optical fiber and irradiates the diamond NV color center. The microwave antenna receives the microwave signal and radiates a microwave field to the above-mentioned diamond NV color center. The diamond NV color center senses the nearby magnetic field and generates feedback fluorescence under the action of the microwave field and the excitation laser;

[0028] The magnetizer is used to magnetize the ferromagnetic material to be tested to generate a leakage magnetic field on its surface defects;

[0029] The signal acquisition and processing module is used to collect the feedback fluorescence, perform noise reduction processing on the signal converted from the feedback fluorescence, and perform calculation and analysis on the processed signal to obtain magnetic field information;

[0030] The laser module is used to provide the excitation laser;

[0031] The microwave module is used to provide the microwave signal.

[0032] As a preferred solution of the non-destructive testing and noise filtering system described in the present invention, wherein: the signal acquisition and processing module further includes a microwave regulation module;

[0033] The microwave regulation module is used to automatically change the frequency of the microwave signal according to the detection sensitivity requirements of different scenarios, so as to match the current working environment.

[0034] The beneficial effects of this preferred technical solution are as follows: By automatically adjusting the microwave frequency to match different detection requirements, there is no need to replace the sensing chip, significantly improving the detection flexibility and efficiency.

[0035] As a preferred solution of a non-destructive testing and noise filtering system according to the present invention, wherein: the detection module further includes a probe cover made of pure iron. Due to the high magnetic permeability of pure iron, all the magnetic field lines in the magnetic field are attracted into the probe cover made of pure iron to shield the influence of the surrounding magnetic field.

[0036] The beneficial effects of this preferred technical solution are as follows: The pure iron probe cover uses the high magnetic permeability characteristic to shield the environmental magnetic field interference, ensuring the purity of the detection signal and enhancing the stability of the system in a complex industrial environment.

[0037] In a third aspect, the present invention provides a computer device, including a memory and a processor; the memory is used to store computer-executable instructions, and when the processor executes the computer-executable instructions, the steps of a non-destructive testing and noise filtering method are implemented.

[0038] In a fourth aspect, the present invention provides a computer-readable storage medium, which stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of a non-destructive testing and noise filtering method are implemented.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides a non-destructive testing and noise filtering method, system, device and storage medium. By using a high-sensitivity NV color center magnetic sensor to detect the leakage magnetic field of ferromagnetic material defects, combined with a self-developed adaptive wavelet threshold denoising method, that is, the threshold function is between the soft threshold and the hard threshold. At the place where the noise signal is large, retain the larger wavelet coefficients to filter out the noise. At the place where the noise is small, retain the smaller threshold to remove the noise and effectively extract the signal itself, which can effectively suppress the environmental noise and accurately extract the weak magnetic field signal. Moreover, at present, due to the low sensitivity of traditional detection methods, it is difficult to detect some micro-cracks. Especially when the crack depth is extremely small, the magnetic field leaked after magnetization excitation of the crack is at the uT level. And the present invention is based on the NV color center magnetic sensor, builds a quantum precision measurement platform, and the sensitivity can reach The spatial resolution can reach 200um, and it can detect extremely small cracks. In addition, the system shields the interference magnetic field through a pure iron probe cover and supports dynamic adjustment of the microwave frequency to adjust the sensitivity to adapt to different detection requirements, significantly improving the detection accuracy and adaptability in a complex industrial environment. Description of the Drawings

[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0041] Figure 1 It is a schematic diagram of the overall process logic of a non-destructive testing and noise filtering method according to an embodiment of the present invention.

[0042] Figure 2 It is a noise reduction effect diagram of the adaptive filtering algorithm of a non-destructive testing and noise filtering method according to an embodiment of the present invention.

[0043] Figure 3 It is a schematic diagram of the component modules of a non-destructive testing and noise filtering system according to an embodiment of the present invention.

[0044] Figure 4 It is an example structure diagram of the detection module of a non-destructive testing and noise filtering system according to an embodiment of the present invention.

[0045] Figure 5 It is an example structure diagram of the NV color center probe of a non-destructive testing and noise filtering system according to an embodiment of the present invention. Specific Embodiments

[0046] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific embodiments of the present invention in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0047] Example 1, referring to Figure 1 This is an embodiment of the present invention, providing a non-destructive testing and noise filtering method, as Figure 1 shown, specifically including the following steps:

[0048] S100: Collect the first detection data obtained during the magnetic flux leakage detection of diamond NV color centers; wherein, the first detection data at least includes the feedback fluorescence and its corresponding scanning position;

[0049] S200: Convert the feedback fluorescence into a fluorescence electrical signal, and perform noise reduction processing on the fluorescence electrical signal using the first adaptive denoising algorithm;

[0050] S300: Perform calculation and analysis on the signal after noise reduction processing to obtain magnetic field information.

[0051] It should be noted that traditional wavelet threshold denoising methods (such as hard threshold and soft threshold) have obvious limitations in noise processing. The basic idea of ​​hard threshold and soft threshold denoising methods is to remove relatively small wavelet coefficients as much as possible, and directly retain or reduce relatively large wavelet coefficients. The estimation of wavelet coefficients by hard threshold filtering is unbiased, but it is easy to produce large oscillations (Gibbs phenomenon) at the sudden change of the filtered signal; the estimation of wavelet coefficients in soft threshold filtering is biased (wavelet coefficients with amplitudes greater than the threshold are partially subtracted, so the mathematical expectation of the estimate is not equal to the mathematical expectation of the observed value), and the filtered signal is too smooth. Both of these existing methods are difficult to achieve an ideal balance between noise suppression and signal fidelity.

[0052] Therefore, in order to solve the problem that the above-mentioned prior art is difficult to balance noise suppression and signal fidelity, resulting in limited crack detection accuracy, through steps S100 to S300, the leakage magnetic field of ferromagnetic material defects is detected by a high-sensitivity NV color center magnetic sensor, combined with a self-developed adaptive wavelet threshold denoising method, that is, the threshold function is between the soft threshold and the hard threshold. In places where the noise signal is large, a larger wavelet coefficient is retained to filter out the noise. In places where the noise is small, a smaller threshold is retained to remove the noise and effectively extract the signal itself. It can effectively suppress environmental noise and accurately extract weak magnetic field signals. Moreover, the current traditional detection methods are difficult to detect some tiny cracks due to their low sensitivity, especially when the crack depth is very small. At this time, the magnetic field leaked by the crack after magnetization excitation is at the uT level. The present invention is based on NV color center magnetic sensors to build a quantum precision measurement platform with a sensitivity of up to The spatial resolution can reach 200um, which can detect extremely small cracks. In addition, the system shields the interfering magnetic field through a pure iron probe cover and supports dynamic adjustment of microwave frequency sensitivity to meet different detection requirements, significantly improving the detection accuracy and adaptability in complex industrial environments.

[0053] Example 2, reference Figures 1 to 2 As an embodiment of the present invention, based on the above embodiment, a nondestructive testing and noise filtering method is provided to illustrate the technical solution of the present invention.

[0054] S100: collecting first detection data obtained when performing magnetic flux leakage detection on diamond NV color centers;

[0055] In the embodiment of the present application, the steps of magnetic flux leakage detection include:

[0056] Use diamond NV color centers to scan the magnetized test piece;

[0057] Irradiate the diamond NV color center with an excitation laser and radiate microwaves to detect the first detection data generated by the diamond NV color center under the action of a microwave field and an excitation laser.

[0058] In an alternative embodiment, magnetic flux leakage detection can adopt a multi-frequency microwave modulation scheme, that is:

[0059] Use a pulsed magnetizer to generate a periodic magnetization field to enhance the transient characteristics of the magnetic flux leakage field at the defect;

[0060] Synchronously modulate the microwave frequency during the NV color center scanning process, and extract the fluorescence responses at different frequencies through lock-in amplification technology;

[0061] Combine the xyz three-dimensional displacement stage to achieve high-precision spatial positioning and establish a three-dimensional distribution model of the defect magnetic field;

[0062] Use the multi-frequency signal correlation to suppress electromagnetic interference in a specific frequency band.

[0063] In another alternative embodiment, magnetic flux leakage detection can also adopt an array detection scheme, that is:

[0064] Integrate multiple diamond NV color centers to form a 1×4 linear array probe and set the spacing between each color center;

[0065] Collect data in parallel through the array probe, and adopt differential processing of adjacent probe signals to suppress environmental common-mode noise;

[0066] According to the feedback of the array probe, adjust the current intensity of the magnetizer in real time to optimize the signal-to-noise ratio of the magnetic field at the defect.

[0067] In the embodiments of the present application, the steps of obtaining the magnetized workpiece to be measured include:

[0068] Magnetize the ferromagnetic material to be measured through a magnetizer to generate a magnetic flux leakage field on its surface defects;

[0069] The position of the magnetizer corresponds to the color center probe of the diamond NV color center, so that the color center probe can sense the magnetic flux leakage field of the defect formed through the magnetizer.

[0070] Preferably, for the diamond NV color center, a 532 nm laser is used as the excitation laser for irradiating the diamond NV color center in magnetic flux leakage detection.

[0071] In an alternative embodiment, the obtained first detection data may include fluorescence intensity data, microwave response characteristics, spatial position information, environmental parameters, auxiliary diagnosis data, etc.;

[0072] In the embodiments of the present application, the first detection data at least includes the feedback fluorescence generated by the diamond NV color center under the synergistic action of the laser and the microwave and its corresponding scanning position;

[0073] Specifically, the feedback fluorescence includes parameters such as intensity, spectral characteristics, and time-domain response. Meanwhile, the scanning position coordinates are recorded to form a spatial magnetic field distribution map. These data also include auxiliary parameters such as ambient temperature and electromagnetic noise background, as well as system operating parameters such as laser power, microwave frequency, and the operating state of the magnetizer. Through multi-dimensional data fusion, the leakage magnetic field characteristics generated by surface defects of the component under test can be accurately characterized, providing a comprehensive and accurate raw data basis for subsequent signal processing and defect identification.

[0074] It should be noted that the above step S100 provides a raw signal basis for subsequent high-precision magnetic field analysis by collecting magnetic flux leakage detection data based on diamond NV centers. This step utilizes the high-sensitivity response of NV centers to weak magnetic fields (such as magnetic flux leakage at the μT level), combined with spatial position information, to accurately locate tiny cracks on the surface of ferromagnetic materials, overcoming the problem of missed detection caused by insufficient sensitivity in traditional detection methods, and providing initial data support with high signal-to-noise ratio for subsequent adaptive denoising and magnetic field calculation.

[0075] S200: Convert the feedback fluorescence into a fluorescence electrical signal, and use the first adaptive denoising algorithm to perform noise reduction processing on the fluorescence electrical signal;

[0076] It should be noted that the feedback fluorescence is collected and converted into an electrical signal by a photodetector. The magnitude of this electrical signal is related to the magnitude of the external magnetic field, so the magnetic field can be measured. However, the electrical signal collected and converted will have noise, and the noise will affect the accuracy of magnetic field measurement. Therefore, before performing magnetic field calculation, it is necessary to use the first adaptive denoising algorithm to perform noise reduction processing on the electrical signal.

[0077] In an alternative embodiment, the first adaptive denoising algorithm can be an improved adaptive wavelet threshold denoising algorithm, which uses a non-linear threshold function with continuous first-order derivatives to achieve a smooth transition between hard threshold and soft threshold, suppressing pseudo-oscillations while retaining the signal mutation characteristics; the first adaptive denoising algorithm can also be an adaptive denoising algorithm based on variational mode decomposition. The signal is decomposed into K intrinsic mode functions through non-recursive mode decomposition, an optimization problem is constructed, and the effective IMF components are automatically selected and reconstructed using the correlation coefficient criterion. The advantage of this algorithm is that it can effectively separate the frequency bands of noise and useful signals, and is particularly suitable for the ODMR signal processing of NV centers;

[0078] In another alternative embodiment, the first adaptive denoising algorithm can also be a quantum state estimation filtering algorithm, that is, a stochastic master equation of the spin state of the NV center is established, the Kalman filtering framework is used to estimate the real magnetic field signal in real time, and an adaptive observation matrix is introduced to directly suppress noise at the quantum measurement level and maintain the quantum characteristics of the nanoscale magnetic field signal.

[0079] In the embodiments of the present application, the signal noise reduction process uses an adaptive threshold wavelet denoising algorithm. The specific steps include:

[0080] Compare the absolute value of the fluorescence electrical signal with a preset first threshold;

[0081] When the absolute value of the fluorescence electrical signal is greater than or equal to the first threshold, the calculation of the denoised signal is: the fluorescence electrical signal minus the result adjusted by the first calculation based on the absolute value of the difference between the fluorescence electrical signal and the first threshold;

[0082] When the absolute value of the fluorescence electrical signal is less than the first threshold, the denoised signal is determined by an exponential function that depends on the absolute value of the difference between the fluorescence electrical signal and the first threshold;

[0083] The formula representation of the algorithm is:

[0084]

[0085] where w is the fluorescence electrical signal, λ is the preset first threshold, and w 阈 is the effective signal after the noise reduction process.

[0086] It should be noted that in the prior art, the hard threshold method is to compare the absolute value of the signal with the threshold, set the points less than the threshold to zero, and keep the others unchanged; the soft threshold method is to compare the absolute value of the signal with the threshold, set the points less than the threshold to zero, and the points greater than or equal to the threshold are shrunk towards zero and become the difference between the point value and the threshold. After such operations, the absolute value of the wavelet coefficient of the soft threshold method function is always less than the actual value, which will cause errors in signal reconstruction; the wavelet coefficients estimated at the threshold points of the hard threshold method are discontinuous, and in the signal reconstruction process, oscillations and ringing phenomena will occur at the threshold points. The traditional hard and soft threshold methods will cause over-denoising. System signals are always accompanied by noise, and most of the noise is irregular. During non-destructive testing, there are not only electronic noises but also vibration noises and magnetic field noises. When using traditional threshold denoising for these noises, some types of noises are often overly weakened, while other types of noises are not processed. The noise decreases as the wavelet decomposition scale in wavelet denoising increases, and using a fixed threshold may over-suppress.

[0087] It should be noted that the advantage of the adaptive threshold wavelet denoising algorithm in the present application is that it is continuous at the threshold, does not produce oscillations and ringing phenomena at the threshold points, and the threshold is variable, which can filter out more types of noises; when the normal signal is 50mv, when the noise is small (noises within ±5mv are considered small noises), a smaller threshold is used to retain the useful signal while denoising, and when the noise is large (noises exceeding 5mv are considered large noises), a larger threshold is used to enhance the denoising ability and effectively remove the noise. As Figure 2 is the comparison chart before and after using the denoising algorithm. From Figure 2It can be seen that there are many stray jumps in the sampling point-detection signal curve before noise reduction, and the curve is smooth after noise reduction, so that it is clear which parts are defective.

[0088] Exemplarily, the preset first threshold should be able to effectively remove noise and retain useful signals. The ideal threshold should be outside the normal signal fluctuation range but close to this range, so as to minimize the impact on useful signals while maximizing the noise reduction effect. When the normal signal is 50mv, the first threshold can be initially set to the upper limit of the normal signal amplitude fluctuation plus the maximum amplitude of small noise, that is, considered to be set at about ±55mv.

[0089] In the embodiments of the present application, abnormal signals are removed before noise reduction processing of the electrical signal. The specific steps include:

[0090] For all fluorescence electrical signals, calculate their root mean square value RMS;

[0091] Judge whether each fluorescence electrical signal is lower than its root mean square value RMS, and whether the absolute value of the difference between the two exceeds a preset threshold;

[0092] If the current fluorescence electrical signal is lower than its root mean square value RMS, and the absolute value of the difference between the two exceeds the preset threshold, then determine that the signal is an abnormal signal, and set all signals lower than RMS to RMS.

[0093] It should be noted that abnormal signals are removed before noise reduction processing of the electrical signal. This step is used to identify abnormal signals, remove abnormal signals, and replace them with RMS. This is because there will be abnormal signals in the detection. For example, when the test piece is a ferromagnetic plate, the magnetic leakage signals generated by the splicing gaps of the plates, the introduction of other noises in the environment, etc. will also cause abnormal signals. For crack signals, the signals are higher than RMS. The preset threshold in this embodiment is 500mv, which is an empirical value and can be determined according to the detected abnormal signals. There may be differences for different detection devices, and for the same detection device, its value is unified. If there are no abnormal signals, then perform filtering and noise reduction processing.

[0094] It should be noted that the above step S200 effectively overcomes the limitations of traditional hard threshold and soft threshold denoising. While retaining the effective magnetic field signal, the adaptive algorithm can dynamically adjust the threshold strategy according to the noise intensity: maintaining signal integrity in strong noise regions and finely extracting weak features in weak noise regions. This processing method not only avoids the Gibbs oscillation phenomenon but also prevents signal over-smoothing, significantly improving the signal-to-noise ratio and providing high-quality preprocessed signals for the accurate calculation of subsequent magnetic field information.

[0095] S300: Calculate and analyze the signal after noise reduction processing to obtain magnetic field information;

[0096] Specifically, perform optically detected magnetic resonance spectroscopy on the noise-reduced fluorescence electrical signal. By fitting the fluorescence intensity depression curve obtained from the microwave frequency scan, accurately determine the resonance frequency offset corresponding to the NV color center energy level splitting. According to the linear dependence of the NV color center spin energy level on the external magnetic field, convert the frequency offset into the corresponding magnetic field strength value. At the same time, combined with the scanning position coordinate information, construct a two-dimensional / three-dimensional leakage magnetic field distribution map of the surface of the sample to be measured. Finally, by setting an appropriate magnetic field strength threshold, automatically identify and mark the possible defect areas, and output a quantitative detection report including the crack position, size, and abnormal magnetic field strength.

[0097] It should be noted that the above step S300 realizes the quantitative characterization of the leakage magnetic field of ferromagnetic material defects. Based on the high-quality signals obtained in the previous steps, it can accurately extract the nanoscale magnetic field characteristic information. Combining with a spatial resolution of 200 μm, it can clearly identify the micron-scale crack characteristics that are difficult to detect by traditional methods. At the same time, this analysis process supports intelligent matching with the scanning position information, provides a reliable magnetic field data basis for defect location and morphology reconstruction, and significantly improves the accuracy and reliability of non-destructive testing.

[0098] Example 3, refer to Figures 3 to 5 This is an embodiment of the present invention. In this embodiment, a non-destructive testing and noise filtering system is provided, such as Figure 3 The system shown includes a detection module, a signal acquisition and processing module, a laser module, and a microwave module;

[0099] In the embodiment of the present application, the detection module includes an NV color center probe and a magnetizer, where:

[0100] As Figure 5 shown, the NV color center probe includes a diamond NV color center, a microwave antenna, and an optical fiber. When the NV color center probe works, the excitation laser is transmitted through the optical fiber and irradiates the diamond NV color center. The microwave antenna receives the microwave signal and radiates a microwave field to the above-mentioned diamond NV color center. The diamond NV color center senses the nearby magnetic field and generates feedback fluorescence under the action of the microwave field and the excitation laser (which contains the information of the magnetic field to be measured, and the magnetic field size can be deduced through analysis and calculation);

[0101] The magnetizer is used to magnetize the ferromagnetic material to be measured so that leakage magnetic fields are generated on the surface defects. The position of the magnetizer corresponds to the color center probe of the diamond NV color center, so that the color center probe can sense the leakage magnetic field of the defect formed by the magnetizer.

[0102] Specifically, the diamond NV color center is bonded to the middle of the end face of the optical fiber (i.e., the core area). The microwave antenna can be a spiral copper wire or a microstrip antenna, and the microwave antenna is arranged on the periphery of the diamond NV color center.

[0103] In a preferred embodiment, Figure 4 The detection module shown also includes a pure iron probe cover. When the surrounding magnetic field contacts the pure iron structural parts, due to the high magnetic permeability of pure iron, all the magnetic lines of force in the magnetic field are attracted to the pure iron probe cover and will not dissipate in the air, so as to shield the influence of the surrounding magnetic field.

[0104] It should be noted that the pure iron probe cover should be isolated from the magnetizer when in use.

[0105] In the embodiment of the present application, the laser module is used to provide excitation laser;

[0106] In a preferred embodiment, a 532 nm laser is used as an excitation laser for irradiating the diamond NV color center during magnetic flux leakage detection.

[0107] In the embodiment of the present application, the microwave module is used to provide a microwave signal.

[0108] In the embodiment of the present application, the signal acquisition and processing module is used to collect feedback fluorescence, perform noise reduction processing on the signal converted from the feedback fluorescence, and perform calculation and analysis on the processed signal to obtain magnetic field information;

[0109] In a preferred embodiment, the signal acquisition and processing module further includes a microwave control module for automatically changing the frequency of the microwave signal to match the current working environment according to the detection sensitivity requirements of different scenarios;

[0110] Specifically, the principle of the microwave control module is: when the NV color center magnetic sensor is working, it needs to irradiate the NV color center in the diamond with microwaves. Different microwave powers and frequencies correspond to different sensitivities of the NV color center magnetic sensor. The experiment shows that when the microwave power is between 10dbm-16dbm and the microwave frequency is 2.875GHz, the sensitivity of the NV color center magnetic sensor in detecting the magnetic field can reach the Pitt level. At this time, if the microwave power is reduced and the microwave frequency is changed, the detection sensitivity of the NV color center magnetic sensor will decrease. In actual work, the equipped intelligent detection algorithm detects the changes in the magnetic field output value during the working time period to change the microwave frequency and power, and then changes the sensitivity of the NV color center magnetic sensor to match the current working environment.

[0111] For example, for an object to be tested, a low-sensitivity measurement method can be used for initial measurement. After quickly finding an area with many defects (the system can make a judgment based on the number of defect alarms in a short period of time), the microwave frequency is automatically switched to a high-precision slow scan mode to obtain the specific defect conditions of the area.

[0112] It should be noted that this is only an automatic switching instruction. The automatic switching instruction can be set according to different detection requirements. The core still lies in the design of switchable sensitivity.

[0113] It should be noted that the technical solution of the non-destructive testing and noise filtering system belongs to the same concept as the technical solution of the above non-destructive testing and noise filtering method. For the details not described in detail in the technical solution of the non-destructive testing and noise filtering system in this embodiment, reference can be made to the description of the technical solution of the non-destructive testing and noise filtering method above.

[0114] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each module above.

[0115] Embodiment 4 provides an electronic device in this embodiment. The electronic device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it realizes a non-destructive testing and noise filtering method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad set on the shell of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0116] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by the processor, it realizes the method proposed in the above embodiment.

[0117] The storage medium proposed in this embodiment and the method proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0118] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

[0119] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages.

[0120] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a means for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0121] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction means that implements the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0122] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0123] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0124] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application is also intended to include these changes and modifications.

Claims

1. A non-destructive testing and noise filtering method, characterized in that, Including: The first detection data obtained when collecting diamond NV color centers for magnetic flux leakage detection; The first detection data at least includes the feedback fluorescence and its corresponding scanning position; Converting the feedback fluorescence into a fluorescence electrical signal, and using a first adaptive denoising algorithm to perform noise reduction processing on the fluorescence electrical signal; Performing calculation and analysis on the signal after the noise reduction processing to obtain magnetic field information.

2. The non-destructive testing and noise filtering method according to claim 1, characterized in that, The magnetic flux leakage detection includes: Scanning the magnetized workpiece using diamond NV color centers; Irradiating the diamond NV color centers with excitation laser and radiating microwaves to detect the first detection data generated by the diamond NV color centers under the action of the microwave field and the excitation laser.

3. The non-destructive testing and noise filtering method according to claim 2, characterized in that, The using the first adaptive denoising algorithm to perform noise reduction processing on the fluorescence electrical signal includes: Comparing the absolute value of the fluorescence electrical signal with a preset first threshold; When the absolute value of the fluorescence electrical signal is greater than or equal to the first threshold, the calculation of the signal after noise reduction is: the fluorescence electrical signal minus the result adjusted by the first calculation based on the absolute value of the difference between the fluorescence electrical signal and the first threshold; When the absolute value of the fluorescence electrical signal is less than the first threshold, the signal after noise reduction is determined by an exponential function depending on the absolute value of the difference between the fluorescence electrical signal and the first threshold.

4. A non-destructive testing and noise filtering method according to claim 2, characterized in that, The magnetized workpiece includes: Magnetizing the ferromagnetic material to be measured through a magnetizer to generate a magnetic flux leakage field on its surface defects; The position of the magnetizer corresponds to the color center probe of the diamond NV color center, so that the color center probe can sense the defect magnetic flux leakage field formed by the magnetizer.

5. The non-destructive testing and noise filtering method according to claim 2, characterized in that In the magnetic flux leakage detection, a laser with a wavelength of 532 nm is used as the excitation laser irradiated to the diamond NV color centers.

6. A non-destructive testing and noise filtering system that applies a non-destructive testing and noise filtering method according to any one of claims 1 to 5, characterized in that, The system includes a detection module, a signal acquisition and processing module, a laser module, and a microwave module; The detection module includes an NV color center probe and a magnetizer; The NV color center probe includes a diamond NV color center, a microwave antenna, and an optical fiber. When the NV color center probe works, the excitation laser is transmitted through the optical fiber and irradiates the diamond NV color center, the microwave antenna receives the microwave signal and radiates a microwave field to the above-mentioned diamond NV color center, and the diamond NV color center senses the nearby magnetic field and generates feedback fluorescence under the action of the microwave field and the excitation laser; The magnetizer is used to magnetize the ferromagnetic material to be measured to generate a magnetic flux leakage field on its surface defects; The signal acquisition and processing module is used to collect the feedback fluorescence, perform noise reduction processing on the signal converted from the feedback fluorescence, and perform calculation and analysis on the processed signal to obtain magnetic field information; The laser module is used to provide the excitation laser; The microwave module is used to provide the microwave signal.

7. The non-destructive testing and noise filtering system according to claim 6, characterized in that, The signal acquisition and processing module further includes a microwave regulation module; The microwave regulation module is used to automatically change the frequency of the microwave signal according to the detection sensitivity requirements in different scenarios to match the current working environment.

8. The non-destructive testing and noise filtering system according to claim 6, characterized in that, The detection module further includes a probe housing made of pure iron. Due to the high magnetic permeability characteristics of pure iron, all the magnetic field lines in the magnetic field are attracted into the probe housing made of pure iron to shield the influence of the surrounding magnetic field.

9. A computer device, comprising a memory and a processor, characterized in that: The memory is used for storing computer-executable instructions, and when the processor executes the computer-executable instructions, the steps of a non-destructive testing and noise filtering method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer-executable instructions are executed by the processor, the steps of a non-destructive testing and noise filtering method according to any one of claims 1 to 5 are implemented.

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