Inverse Fourier transform particle cross detection method and system of laser particle analyzer

Abstract

The invention relates to the technical field of particle size analysis, solves the technical problem of signal distortion in rodlike abrasive dust particle size monitoring in a high-intensity magnetic field environment, and particularly relates to an inverse Fourier transform particle cross detection method and system for a laser particle analyzer, and the method comprises the following steps: collecting an original scattered light intensity signal and magnetic field intensity data; calculating a magnetic field change gradient based on the magnetic field intensity data; calculating a predicted phase offset used for eliminating signal distortion caused by rotating speed abrupt change by using the magnetic field change gradient; and identifying an oscillation risk period based on the magnetic field change gradient and a preset risk determination threshold. The method breaks through the hypothesis of a traditional Mie theory on spherical particles, establishes a scattering kernel function of the rod-shaped particles based on a T matrix theory, introduces a magnetic field coupling term, and quantifies the influence of a magnetic field on particle orientation and scattering signals. The situation that single particles are misjudged as multi-size mixed particles due to scattering double-peak artifacts caused by directional arrangement of the rod-shaped particles in a high-intensity magnetic field is avoided, and the particle size inversion precision is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of particle size analysis, and in particular to a method and system for particle cross detection using an inverse Fourier transform of a laser particle size analyzer. Background Art

[0002] The inverse Fourier transform particle cross-detection method used in laser particle size analysis is a highly efficient particle size analysis technique based on light scattering theory. Its principle is as follows: after laser irradiation of the sample, a Fourier lens system maps the angular distribution of the scattered light into a spatial distribution signal. A multi-quadrant detector simultaneously collects the scattered light intensity at different spatial locations. An inverse Fourier transform is then performed on the scattered light intensity, and the particle size distribution is determined using the Mie scattering theory model. This method's core advantages lie in its rapid speed and wide dynamic range, and it has been widely used in the chemical, pharmaceutical, and other fields.

[0003] However, existing laser particle size analyzers' inverse Fourier transform particle cross-detection methods rely on a fundamental assumption: that particles are perfectly spherical. This assumption stems from the mathematical foundation of Mie theory—the analytical solution of Maxwell's equations for spherical boundaries. There is no analytical solution for the scattering behavior of non-spherical particles, requiring numerical approximations (such as the T-matrix method). However, due to the high computational complexity, these methods cannot be integrated into real-time particle size analyzers. Consequently, commercial devices forcibly map the scattering signals of non-spherical particles to equivalent spherical diameters, resulting in systematic distortion in certain scenarios.

[0004] In particular, in the case of wear particle monitoring for magnetic fluid seals, real-time monitoring of ferroferric oxide wear debris within a hydrocarbon-based carrier fluid is required to provide early warning of seal failure based on particle size growth. Wear debris is typically rod-shaped particles with an aspect ratio of 3:1-10:1 (material wear generates flaky debris, which is then stretched by the combined magnetic field orientation and the antimagnetic force of the hydrocarbon-based carrier fluid, locking the rod-shaped morphology). When the equipment generates a strong magnetic field (>0.5T), the wear debris particles are oriented along the magnetic field lines (with the long axis parallel to the magnetic field), and their scattered signal forms a bimodal angular distribution in the equatorial plane. However, the inversion algorithm forces the non-spherical signal to be fitted to a spherical model, resulting in the misinterpretation of a single wear debris particle as a mixture of particles of multiple sizes. For example, a 10μm wear debris particle is broken down into 5μm and 20μm spherical particles, causing the system's early warning to fail. In addition, in high-speed rotating equipment (such as turbines, pumps, compressors, etc.), the direction of the magnetic moment of the wear particles oscillates violently at the moment of sudden change in speed, and the scattered light intensity shows high-frequency sub-peak movement, which in turn causes high-frequency jumps in the scattered light phase offset signal, leading to the dynamic offset being misinterpreted as a bimodal distribution, causing system warning errors. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a laser particle size analyzer inverse Fourier transform particle cross detection method and system, which solves the technical problem of signal distortion in rod-shaped wear debris particle size monitoring in a strong magnetic field environment, and achieves the purpose of real-time accurate inversion and early warning of the true size of wear debris particles.

[0006] To solve the above technical problems, the present invention provides the following technical solution: a laser particle size analyzer inverse Fourier transform particle cross detection method, the method comprising the following steps: The original scattered light intensity signal and magnetic field strength data are collected, and the magnetic field gradient is calculated based on the magnetic field strength data. The magnetic field gradient is used to calculate the predicted phase offset used to eliminate signal distortion caused by sudden rotational speed changes. The oscillation risk period is identified based on the magnetic field gradient and a preset risk determination threshold. The original scattered light intensity signal in the oscillation risk period is marked as a transient signal, and the others are marked as steady-state signals. The double-peaked pseudo signal of the steady-state signal caused by the directional arrangement of the magnetic field is corrected by the morphological characteristics of the wear debris particles and the magnetic field coupling effect; the phase jump caused by mechanical interference is compensated in the transient signal by time-frequency analysis; the steady-state signal and the transient signal are weighted and fused into a composite signal; During the oscillation risk period, the magnetic field interference component is stripped from the composite signal to obtain a de-oscillation phase domain signal; time-frequency analysis is performed on the de-oscillation phase domain signal to determine the bimodal characteristic parameters, and the true scattering characteristics are calculated; the morphological characteristics of the wear debris particles are inverted based on the results of the true scattering characteristics, and the equipment wear warning is triggered based on the inversion results.

[0007] Furthermore, the method of correcting the double-peak pseudo signal of the steady-state signal caused by the directional arrangement of the magnetic field by using the morphological characteristics of the wear debris particles and the magnetic field coupling effect includes: Acquire the morphological characteristics of the wear debris particles based on the wear debris particle image, identify the main axis of the wear debris particle shape, and determine the lengths of the major axis and minor axis; Establish the scattering kernel function of non-spherical wear debris particles: ; Where, is the scattering kernel function; is the long axis of the wear debris particle; is the minor axis of the wear debris particle; is the scattering angle; is the scattering amplitude; y is the wave number of the propagating wave; is the wavelength of light; Introduce the magnetic coupling term to correct the scattering intensity: ; Where, is the modified scattering kernel function; represents the scattering kernel function calculated under the condition of no magnetic field; is the shape correction coefficient; is the Boltzmann constant; T is the absolute temperature, H is the external magnetic field; is the material parameter; Decompose the steady-state signal into morphological feature contributions and noise: ; m represents the number of categories of wear debris particles with different morphological characteristics; is the weight corresponding to the i-th category of wear particles; represents the scattering intensity of the i-th category of wear debris particles; For noise; The second-order derivative, which can reveal the concave and convex features of the steady-state signal, is calculated, and the number of extreme points of the second-order derivative is identified. If the second-order derivative has two extreme points near the equatorial plane, it indicates that the steady-state signal is a multi-particle signal. If the second-order derivative has only one extreme point near the equatorial plane, it is determined to be a single-particle signal.

[0008] Furthermore, the method of extracting the transient signal through time-frequency analysis to compensate for the phase jump caused by mechanical interference includes: The transient signal is divided into preset time windows, and the Fourier transform is performed on the signal in each time window, that is: ; Where, is the time-frequency plane; is the expression of the window function; is the frequency, is the time delay; j is the imaginary unit; Find each delay The frequency with the strongest energy is: ; Where, is the main frequency; Match the extracted main frequency with the frequency of the equipment speed change. If the two frequency changes match, extract the phase information, that is: ; Where, Indicates the phase jump caused by mechanical interference; Indicates the phase angle of the main frequency.

[0009] Furthermore, the method of stripping the magnetic field interference component from the composite signal is: ; Where, is the de-oscillation phase domain signal; is the fundamental oscillation function; The scaling factor is used to adjust the amplitude of the compensation signal. It is obtained by calibrating the historical oscillation data of the device to ensure that the subtracted interference signal is of appropriate size and that the compensation signal matches the actual interference amplitude. is the oscillation frequency modulation factor, To predict the phase offset, the calculation formula is: ; Wherein, k is the magneto-optical coupling coefficient; is the magnetic field gradient; For the time scale.

[0010] Furthermore, the method of calculating the true scattering characteristics is: The scale range of the wavelet transform is set based on the peak width W of the oscillating phase domain signal; Perform discrete wavelet transform on the oscillation phase domain signal and calculate the wavelet coefficients, namely: ; Where q is the scale; p is the translation parameter; is the wavelet coefficient; is the wavelet function; Step by step, the wavelet coefficients of each scale are checked within the scale range of the wavelet transform, and the corresponding peak clarity is calculated, that is: ; Where, is peak clarity; is the maximum value of the wavelet coefficient; is the minimum value of the wavelet coefficient; is the variance of the wavelet coefficients; The scale that maximizes the peak clarity is selected as the final scale, and the local maximum of the wavelet coefficient at this scale is calculated to determine the significant peak; that is: ; Where, is the collection of significant peaks; is the peak screening threshold; The two strongest local maxima are selected from the set of significant peaks and defined as double peaks. The signal intensities of the two peaks are compared to calculate the intensity ratio, that is: ; Where, is the intensity ratio; Indicates the position angle Signal strength at Indicates the position angle Signal strength at The double peak angular distance used to accurately identify the morphological characteristics of wear debris particles and improve the inversion accuracy is calculated by the position angles of the two peaks, namely: ; Where, is the bimodal angular distance, position angle Indicates the angular position of the first peak, position angle represents the angular position of the second peak.

[0011] Furthermore, the method of calculating the true scattering characteristics is: ; Where, is the real scattered signal intensity distribution after reconstruction; is the convolution operator; is the unit pulse function.

[0012] Furthermore, the inversion of the morphological characteristics of the wear debris particles based on the result of the true scattering characteristics includes: ; Where, Indicates the scattering angle of wear debris particles The scattering intensity at ; n is the order of the scattering mode; and is the correlation coefficient related to the major-minor axis ratio and scattering angle of wear debris particles; and is the contact function related to the cosine of the scattering angle; The reconstructed real scattering signal intensity distribution and scattering intensity are fitted with the linear least square method to invert the major axis and minor axis of the wear debris particles, namely: ; Where C is the calibrated concentration correction factor.

[0013] Furthermore, the method of triggering equipment wear warning based on the inversion result is: Calculate the equivalent volume diameter of wear debris particles: ; Where, is the equivalent volume diameter of the wear debris particles; is the long axis inversion value of the wear debris particle; is the short axis inversion value of the wear debris particle; The equivalent volume diameter of the wear debris particles is compared with the preset volume threshold. When the equivalent volume diameter exceeds the volume threshold N times in a row, an equipment wear warning is triggered.

[0014] Furthermore, the magneto-optical coupling coefficient is determined as follows: Calculate the electric field intensity when the laser beam reaches the surface of the wear debris particles, that is: ; Where, is the electric field intensity when the laser beam propagates to the surface of the wear debris particles; is the initial electric field strength; is the absorption coefficient of the hydrocarbon-based carrier liquid; z is the propagation distance; The total scattered intensity is calculated by integrating the scattered patterns, namely: ; Where, The wear particles are scattered at a specific angle Total field intensity under ; is the distribution function of wear debris particles; is the scattering pattern related to the interaction intensity between wear debris particles and the incident laser beam; The magneto-optical coupling coefficient is calculated based on the total scattering intensity and the electric field intensity, namely: ; Where, is the dielectric constant of vacuum; is the incident field intensity; is the scattered field intensity, and the calculation formula is: ; in, To monitor the volume of a container; is the volume of wear debris particles.

[0015] A laser particle size analyzer inverse Fourier transform particle cross detection system, comprising: Signal acquisition module, used to collect laser scattering signals and equipment operating parameters; Signal preprocessing module, used to classify the initial scattered light intensity distribution and eliminate environmental noise; Signal correction module, used to correct the double-peak artifact signal based on the magnetic field oriented alignment effect of rod-shaped particles; Phase compensation module, used to eliminate the phase offset of magnetic moment oscillation caused by sudden speed change; Signal reconstruction module, used to remove magnetic field artifacts and extract the true scattering characteristics of particles; The particle inversion and early warning module is used to invert the geometric size of wear debris particles and realize wear early warning.

[0016] By means of the above technical solution, the present invention provides a method and system for particle cross-detection using an inverse Fourier transform of a laser particle size analyzer, which has at least the following beneficial effects: 1. This invention breaks through the traditional Mie theory's assumption of spherical particles. It establishes a scattering kernel function for rod-shaped particles based on T-matrix theory and introduces a magnetic field coupling term to quantify the effect of the magnetic field on particle orientation and scattering signals. This solves the problem of double-peak scattering artifacts caused by the oriented arrangement of rod-shaped particles in strong magnetic fields, avoids misinterpreting single particles as mixed particles of multiple sizes, and significantly improves the accuracy of particle size inversion.

[0017] 2. This invention uses time-frequency analysis to extract the magnetic moment oscillation frequency caused by sudden speed changes, dynamically compensates for phase jumps, and fuses steady-state and transient signals to generate an interference-resistant composite signal. This eliminates high-frequency jumps in scattered signals caused by sudden speed changes, prevents the misinterpretation of dynamic phase shifts as sudden particle size changes, and improves system stability under transient conditions.

[0018] 3. The present invention combines wavelet transform and magnetic field gradient data to remove oscillation artifact signals, extract the true double peak angular distance, and reconstruct the essential scattering distribution through the unit pulse function. It accurately separates magnetic field interference and true particle signals, and inverts the long axis. and short axis The error is reduced to less than 5%, providing a reliable data basis for wear analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 Schematic diagram of the detection method in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] To make the above-mentioned objectives, features, and advantages of the present invention more clearly understood, the present invention is further described below in detail with reference to the accompanying drawings and specific embodiments. This will enable a full understanding of how this application uses technical means to solve technical problems and achieve technical effects, and to implement the invention accordingly.

[0021] This embodiment proposes a laser particle size analyzer inverse Fourier transform particle cross-detection method, which solves the problem that under a strong magnetic field, the long axis of the wear debris particles is parallel to the magnetic lines of force, and the scattered signal forms an erroneous bimodal distribution in the equatorial plane. The inversion algorithm mistakenly interprets these signals as a mixture of particles of various sizes due to the forced assumption that the particles are spherical. In addition, during high-speed operation of the equipment, the sudden change in rotation speed causes violent oscillations in the direction of the magnetic moment of the particles, resulting in high-frequency jumps in the phase of the scattered light, making the signal unstable, and thus interfering with the true measurement of the particle size. By correctly decoupling the influence of the magnetic field and the oscillating signal, the true size parameters (major axis and minor axis) of the rod-shaped particles can be accurately identified and inverted during the analysis process, greatly reducing the measurement error caused by improper model assumptions. Figure 1 As shown, the method includes the following steps: Establish a correlation between the original scattered light intensity signal and the equipment operating parameters, and filter out the effective signal range. Because in the magnetic fluid seal scenario, the sudden change in equipment speed will cause a drastic change in the magnetic field intensity, the magnetic moment of the wear particles will precess under the action of the Lorentz force, and the scattered light will produce a high-frequency phase shift; the phase shift and the real particle scattering signal are mixed in the time domain, and traditional inversion cannot be separated. By collecting the original scattered light intensity signal and magnetic field intensity data in the magnetic fluid seal wear particle monitoring scenario and aligning them according to the acquisition time, a direct mapping relationship between the magnetic field intensity change and the scattered signal is established to solve the phase shift problem caused by the sudden change in speed. Specifically: Based on the time series data of magnetic field intensity, the magnetic field gradient at each discrete time point is calculated, that is: ; Where, is the magnetic field gradient, reflecting the instantaneous rate of change of the magnetic field; For The magnetic field strength collected at every moment, that is, the magnetic field strength at the current moment; For The magnetic field strength collected at the moment is the magnetic field strength at the previous moment; is the sampling time interval; t is the time scale.

[0022] The predicted phase offset used to eliminate signal distortion caused by sudden rotational speed changes is calculated using the magnetic field gradient and material parameters, namely: ; Where, To predict the phase offset, that is, to quantify the phase offset of scattered light caused by magnetic field interference; k is the magneto-optical coupling coefficient, and its dimension is , reflects the phase shift produced by each unit magnetic field gradient under specific material susceptibility conditions, and is determined based on experimental data fitting; is a material parameter, namely the magnetic susceptibility of wear debris particles, which reflects the intensity of the magnetization response of wear debris particles under the action of the magnetic field.

[0023] At the same time, the oscillation risk period for triggering the compensation processing window is marked based on the magnetic field change gradient and the preset risk judgment threshold, that is: ; Where, It is a risk marker for the period of oscillation risk; is the risk determination threshold, which is calibrated through historical failure data.

[0024] when When , it means that the magnetic field oscillates violently and enters the transient interval, and the original scattered light intensity signal in this interval is marked as a transient signal The drastic change of magnetic field causes the magnetic moment of wear debris particles to precess and the phase of scattered light to oscillate. At the same time, wear debris particles may also be affected by other dynamic forces (such as Lorentz force) and rotate. Therefore, the transient signal is not only related to the scattering angle It is related to the transient signal and changes rapidly with time, showing a dynamic process. Therefore, the transient signal cannot be directly processed by the static inversion method. It is necessary to perform dynamic compensation to eliminate the phase distortion before inversion.

[0025] when When , it means that the magnetic field is stable and enters the steady-state interval, and the original scattered light intensity signal in this interval is marked as the steady-state signal ; Since the magnetic field is stable, the direction of the magnetic moment of the wear debris particles is stable, and the phase of the scattered light is not disturbed by the sudden change of the magnetic field; therefore, the steady-state signal is only related to the scattering angle, does not change with time, and can be expressed as a static distribution; and then the steady-state signal can be directly used in the classic static light scattering inversion algorithm (such as Mie theory inversion) to obtain the particle size distribution of the wear debris particles.

[0026] Using the known material parameters and particle shape model of wear debris particles, the double-peak false signal caused by the directional arrangement of the magnetic field is corrected. Specifically: Collect images of wear debris particles in the wear particle monitoring scene of magnetic fluid seals, obtain the morphological characteristics of the wear debris particles, identify the main axis of the wear debris particle shape, and determine the lengths of the major axis and minor axis.

[0027] Based on the T-matrix theory, the wear debris particles are regarded as rotating ellipsoids, and the relationship between the morphological characteristics of the wear debris particles and the scattering intensity is established, namely: ; Where, is the scattering kernel function, which indicates the scattering angle The morphological feature is the long axis , short axis The scattering intensity of wear debris particles; The long axis of the wear debris particle refers to the straight line with the farthest distance between the two ends of the wear debris particle, corresponding to the main extension direction of the wear debris particle. In non-spherical wear debris particles, the value of the long axis directly affects the angular distribution of scattered light; The short axis of the wear particle is perpendicular to the long axis and points to the shortest distance between the two ends in the cross section. It can provide information about the effect of the shape of the wear particle on the rheological properties. The scattering angle is the angle between the incident laser beam and the scattered light direction. This angle affects the intensity and distribution of the scattering of wear particles and is usually used to define different scattering patterns. is the scattering amplitude, which is related to the geometric shape and physical properties of the wear debris particles and represents the complex intensity of scattered light at a specific angle. Its expression is: ; in, is a complex exponential function; y is the wave number of the propagating wave, and the calculation formula is: ; in, is the wavelength of light, so the wave number determines the propagation characteristics of light waves in space.

[0028] The scattering kernel function is used to critically calculate the scattering behavior of wear particles under different conditions (including shape and magnetic field). Subsequent magnetic field coupling corrections are all based on this basic model.

[0029] The scattering kernel function in the absence of a magnetic field is modified by introducing a magnetic coupling term. If the wear debris particles have good magnetic properties, their orientation will be adjusted under the action of an external magnetic field, thereby changing their optical properties during the scattering process. That is: ; Where, is the modified scattering kernel function, which describes the scattering intensity of wear particles under the influence of the external magnetic field H. represents the scattering kernel function calculated under the condition of no magnetic field; is the magnetic field correction term, which is used to consider the influence of the external magnetic field on the scattering behavior of wear debris particles; is the shape correction coefficient, obtained through experimental calibration, and is used to adjust the degree of magnetic field influence; is the Boltzmann constant, which connects temperature and energy and is usually used in statistical physics; T is the absolute temperature in Kelvin, which characterizes the degree of thermal motion of the material.

[0030] The steady-state signal The contribution and noise of wear debris particles with different morphological characteristics to the scattered signal are decomposed to clarify the impact of each wear debris particle on the entire signal, namely: ; Where m represents the number of types of wear debris particles with different morphological characteristics involved in the calculation; is the weight corresponding to the i-th category of wear debris particles, indicating the relative density of wear debris particles with this morphological characteristic in the whole; represents the scattering intensity of the i-th category of wear debris particles; is the long axis of the wear debris particle of type i; is the minor axis of the i-th type of wear debris particles; For noise.

[0031] This decoupling process allows us to more accurately parse the contributions of wear debris particles of different time periods and morphological characteristics within the original scattered light intensity signal, thereby improving overall accuracy and reducing errors caused by signal overlap. Furthermore, separating the noise component from the total signal effectively suppresses random fluctuations caused by external interference or wear debris movement, making subsequent analysis more stable and reducing misjudgments. This provides a sound data foundation for subsequent inversion of wear debris morphological characteristics.

[0032] Calculating the second-order derivative reveals the concave and convex features (i.e., rapidly changing regions) of the steady-state signal, which exhibit significant differences between single-particle and multi-particle signals. The signal's nature is determined by identifying the number of extreme values ​​in the second-order derivative of the steady-state signal. If the second-order derivative of the steady-state signal exhibits two extreme values ​​near the equatorial plane, it indicates a multi-particle signal with two scattering peaks. If the extreme values ​​are smooth and confined to a single peak, it is considered a single-particle signal. This distinguishes single-particle signals from multi-particle signals, ensuring the accuracy and denoising capabilities of subsequent analysis.

[0033] Eliminate the phase shift and high-frequency noise caused by the magnetic moment oscillation of wear debris particles caused by sudden changes in speed to obtain the real scattered signal intensity distribution after reconstruction. The transient signal is divided into preset time windows. For example, each time window is: Perform Fourier transform on the signal in each time window to obtain its frequency domain representation, namely: ; Where, is the time-frequency plane, is the Fourier transform result of the signal, is a complex number, and describes the characteristics of the signal at a given frequency and time delay; is the expression of a window function (such as Hanning window), a function used to smooth a signal; is the frequency, is the time delay, which represents the central function of the window function; j is the imaginary unit, which is used to construct the complex space.

[0034] By analyzing the spectrum, find each delay The frequency with the strongest energy is: ; Where, is the main frequency, indicating the delay When, frequency The main frequency.

[0035] The extracted main frequency is matched with the frequency of the equipment speed change detected by the speed sensor. If the two frequency changes match, it indicates that the frequency component is caused by mechanical interference of the equipment.

[0036] Extract the phase information of the main frequency caused by the mechanical interference of the equipment, and identify the phase jump and nonlinear interference components caused by mechanical interference. ; Where, Indicates the phase jump caused by mechanical interference; Indicates the phase angle of the main frequency.

[0037] By compensating the phase jump of the transient signal, the unnecessary interference caused by mechanical oscillation can be corrected, that is: ; Where, For the compensated transient signal, the phase shift caused by mechanical interference or other factors is removed, so that the signal is closer to its true characteristics.

[0038] The steady-state signal represents the particle size distribution of the wear particles under normal operating conditions of the equipment, while the transient signal captures the transient characteristics caused by changes in rotational speed, etc. By merging the two, more comprehensive information can be obtained, reflecting the true characteristics of the wear particles under actual operating conditions. In the subsequent particle size inversion process of the wear particles, if the two types of corrected signals are not merged, each type of signal can only provide partial information. That is, the steady-state signal may not reflect instantaneous changes and unpredictable events, while the transient signal may be obscured by various noises, causing the true characteristics to be obscured. Inversion based on only a single signal may lead to deviations in the inversion results, especially when the transient signal fluctuates greatly or the signal quality is poor, the characteristics of the particles will not be accurately captured. By weighted merging the two to obtain a composite signal, the stability and reliability of the signal can be further ensured. Specifically, the compensated transient signal and steady-state signal are merged as follows: The compensated transient signal and steady-state signal are aligned according to the acquired timestamps. For signals that cannot be aligned directly, an interpolation algorithm (such as linear interpolation or spline interpolation) is used to adjust them to the same time axis so that the corresponding signal value can be obtained at each time point. The compensated transient signal and steady-state signal are weightedly fused according to the preset distribution weights, that is: ; Where, is the composite signal after fusion; and Assign weights to the presets, satisfying , calibrated based on experimental data.

[0039] During the oscillation risk period with risk markers, the false signal components caused by the magnetic field are stripped from the composite signal. This prevents the composite signal from being misjudged as a sudden change in particle size due to high-frequency peak movement caused by magnetic moment oscillation when the speed changes suddenly. That is: ; Where, The de-oscillation phase domain signal, that is, the essential scattered light intensity distribution after stripping away the transient interference of the magnetic field, is a three-dimensional tensor, a two-dimensional matrix consisting of the scattering angle and time, superimposed with the real part of the complex signal (describing the intensity distribution of the scattering of the wear debris particles, which is directly related to the particle size and shape) and the imaginary part (characterizing the phase information of the light wave with suppressed magnetically induced phase jumps); is the fundamental oscillation function, which is used to restore the time-varying periodicity of the interference signal; The scaling factor is used to adjust the amplitude of the compensation signal. It is obtained by calibrating the historical oscillation data of the device to ensure that the subtracted interference signal is of appropriate size and that the compensation signal matches the actual interference amplitude. is the oscillation frequency modulation factor, in rad / s, which determines the oscillation frequency of the compensation signal.

[0040] The peak width W of the de-oscillation phase domain signal is extracted to determine the scale range of the wavelet transform, and the scale range of the wavelet transform is set based on the peak width W, that is: ; in, is the lower limit of the scale range of wavelet transform, is the upper limit of the scale range of wavelet transform.

[0041] The de-oscillation phase domain signal is converted to the time-frequency domain using discrete wavelet transform, and the fine signal structure is obtained through the Daubechies wavelet function, namely: ; Where q is the scale, which is used to control the expansion degree of the wavelet function; p is the translation parameter, which is used to control the movement position of the wavelet function and can locate the specific time point of the signal; is the wavelet coefficient, which represents the characteristic intensity of the de-oscillation phase domain signal at a specific position under the specified scale and translation parameters. It reflects the details of the de-oscillation phase domain signal at this scale and position and is the representation of the signal in the time-frequency domain. is the wavelet function.

[0042] Step by step, the wavelet coefficients of each scale are checked within the scale range of the wavelet transform, and the corresponding peak clarity is calculated, that is: ; Where, is the peak clarity, which indicates the signal clarity index for a specific scale; is the maximum value of the wavelet coefficient under given scale and all translation parameters; is the minimum value of the wavelet coefficient under a given scale and all translation parameters; is the variance of the wavelet coefficients, which is used to quantify the distribution range of the wavelet coefficients and reflect the randomness and fluctuation degree of the signal.

[0043] The scale that maximizes the peak clarity is selected as the final scale, and the local maximum of the wavelet coefficients at this scale is calculated to determine the possible significant peaks; that is: ; Where, is a collection of significant peaks, including possible local maximum positions and their corresponding times; is the peak screening threshold. Only when the absolute value of the wavelet coefficient exceeds this threshold can the time point be considered as a potential peak, which is determined based on the experimental data fitting.

[0044] The two strongest local maxima are selected from the set of significant peaks, and the two are defined as double peaks on the equatorial plane. The position angles of the two peaks are determined. The signal intensities of the two peaks are compared to calculate the intensity ratio, which is: ; Where, is the intensity ratio; Indicates the position angle Signal strength at Indicates the position angle The signal strength at the

[0045] The double peak angular distance used to accurately identify the morphological characteristics of wear debris particles and improve the inversion accuracy is calculated by the position angles of the two peaks, namely: ; Where, The bimodal angular distance represents the angular difference between the two peaks identified in the de-oscillation phase domain signal in the equatorial plane. It is an important parameter used to evaluate the particle morphology, especially in rod-shaped particles that cause bimodal distribution. The angular position of the first peak, that is, the angle of the first local extreme point of the de-oscillation phase domain signal, usually corresponds to a smaller scattering angle, indicating the scattering characteristics of wear debris particles in a certain direction; the position angle The angular position of the second peak, that is, the angle of the second local extreme point of the de-oscillation phase domain signal, usually corresponds to a larger scattering angle. This position is generally related to the geometric shape and movement characteristics of the wear debris particles.

[0046] The double-peak angular offset used to correct the measurement error caused by the magnetic field is calculated using the magnetic field gradient, material parameters, and the ratio of the major and minor axes of the wear debris particles, namely: ; Where, is the double-peak angular offset, i.e., the angular difference caused by the influence of the magnetic field, which is used to quantify the effect of the change in wear particle shape on the de-oscillation phase domain signal; Based on the double-peak angular distance and the double-peak angular distance offset, when the magnetic field is known, the artifact offset caused by the magnetic field is subtracted from the measured double-peak angular distance to obtain the true double-peak angular distance, that is: ; Where, is the true bimodal angular distance.

[0047] The unit pulse function is multiplied with the de-oscillated phase domain signal to extract the true scattered signal intensity distribution, that is: ; Where, The reconstructed real scattered signal intensity distribution provides the real scattering characteristics of the corrected and cleaned wear debris particles, providing a reliable data basis for subsequent analysis and particle performance evaluation; is the convolution operator; is the unit pulse function, which means that at a specific scattering angle The response at the point where the value is 1 is taken, and the value at other points is taken as 0. By setting a specific scattering angle, the unit pulse function ensures that only the signal information related to the true double-peak angular distance is retained, helping to extract the true scattering signal information and effectively isolating the influence of other angles.

[0048] The scattering intensity used to invert the geometric shape and size of wear debris particles is calculated based on the improved T-matrix method of scattering theory, namely: ; Where, Indicates the scattering angle of wear debris particles The scattering intensity at depends on the geometric characteristics (major axis and minor axis) of the wear debris particles, reflecting the scattering characteristics of the wear debris particles at a specific angle, which is used for the subsequent inversion of the geometric shape and size of the particles. n is the order of the scattering pattern, which starts from 1 and increases upward to cover all possible scattering patterns, thus taking into account all complex scattering behaviors in the calculation of the scattering intensity. is the weight factor used to adjust the contribution of different scattering modes to the final scattering intensity; and It is the correlation coefficient related to the major-minor axis ratio and scattering angle of the wear debris particles, which is used to describe the scattering intensity response in different modes and is determined by fitting experimental data; and It is a contact function related to the cosine value of the scattering angle, which is usually related to the phase and scattering direction of the light wave and is determined by fitting experimental data.

[0049] The reconstructed real scattering signal intensity distribution and scattering intensity are fitted with the linear least square method to optimize the inversion of the major axis and minor axis of the wear debris particles, namely: ; Where C is the calibrated concentration correction factor; is the long axis inversion value of the wear debris particle; is the inverted value of the minor axis of the wear debris particle. By minimizing the error between the actual scattering signal and the theoretical model, the geometric characteristics of the wear debris particle, especially the specific values ​​of the major and minor axes, are accurately inverted.

[0050] Based on the inverse geometric characteristics of the wear debris particles, the equivalent volume diameter of the wear debris particles is calculated, that is: ; Where, is the equivalent volume diameter of wear debris particles, which is used to evaluate the impact of wear debris particles on the wear process.

[0051] The equivalent volume diameter of wear debris particles is compared with a preset volume threshold. When the equivalent volume diameter exceeds the threshold for N consecutive times, an equipment wear warning is triggered. This enables real-time monitoring of the wear process and provides timely feedback on equipment operating status, reducing the risk of equipment damage and ensuring safe operation.

[0052] And the long axis inversion value of the wear debris particles is obtained by inversion and short axis inversion value , which is fed back into the calculation formula of the double-peak angular distance offset to form a closed-loop correction, effectively reducing the influence of the morphological characteristic assumption error of the wear debris particles on the intensity distribution of the reconstructed real scattering signal.

[0053] It should be noted that in the scenario of wear monitoring of magnetic fluid seals, accurate calculation of the magneto-optical coupling coefficient is very important. Traditional methods rely on experimental data to determine this coefficient, but this may lead to errors and is not suitable for rapidly changing working conditions and variable material properties. Therefore, based on the combination of electromagnetic field theory and particle scattering model, the magneto-optical coupling coefficient is dynamically calculated to improve the prediction accuracy of scattered signals in the wear monitoring of magnetic fluid seals and enhance the early warning capability. Specifically: The finite element method is used to establish a coupled model of the laser field and magnetic field, and boundary conditions are set according to the geometric structure of the instrument, including the incident angle of the laser beam, the position and direction of the wear particles in the liquid, and the externally applied magnetic field. The electric field intensity when the laser beam reaches the surface of the wear particles is calculated based on the known initial electric field intensity, absorption coefficient, and propagation distance of the laser beam in the hydrocarbon-based carrier liquid, that is: ; Where, The electric field intensity when the laser beam propagates to the surface of the wear debris particles, that is, the intensity of the incident light after passing through the hydrocarbon-based carrier liquid. It is used to describe the attenuation of the laser beam when propagating in the hydrocarbon-based carrier liquid. It can help analyze the changes in electric field intensity at different depths and provide a basis for the subsequent analysis of the scattering behavior of wear debris particles. is the initial electric field intensity, that is, the electric field intensity measured at the laser source; is the absorption coefficient of the hydrocarbon-based carrier fluid; z is the propagation distance, which represents the distance the laser beam travels from the laser source to the abrasive particles.

[0054] Then, the total scattering intensity at a specific scattering angle is calculated by analyzing the particle scattering intensity and scattering pattern of wear particles with different equivalent volume diameters, which is used to provide the necessary scattering characteristic data for solving the magneto-optical coupling coefficient and improve the accuracy and reliability of wear particle monitoring of magnetic fluid seals. That is: ; Where, The wear particles are scattered at a specific angle Total field intensity under ; is the distribution function of wear debris particles, which describes the relative number of wear debris particles with different equivalent volume diameters; It is the scattering pattern related to the interaction intensity between the wear debris particles and the incident laser beam, and describes the scattering pattern at the scattering angle after the incident laser beam interacts with the wear debris particles of equivalent volume diameter.

[0055] The magneto-optical coupling coefficient is calculated based on the total scattering intensity and the electric field intensity, namely: ; Where, is the dielectric constant of vacuum; is the incident field intensity; is the scattered field intensity, and the calculation formula is: ; in, To monitor the volume of a container; is the volume of wear debris particles, and the calculation formula is: ; The magneto-optical coupling coefficient is a key parameter that describes the strength of the interaction between electromagnetic waves and magnetic particles. By accurately calculating the magneto-optical coupling coefficient, the coupling effect between the laser beam and the magnetic field can be quantified, thereby determining the response of wear particles to the laser. Furthermore, accurate magneto-optical coupling can improve the inversion of wear particle size and morphology, ensuring more realistic and reliable monitoring of wear particle characteristics under varying environmental conditions. This is crucial for improving the accuracy of wear prediction and fault warning.

[0056] This embodiment also proposes a laser particle size analyzer inverse Fourier transform particle cross detection system, including a signal acquisition module, a signal preprocessing module, a signal correction module, a phase compensation module, a signal reconstruction module and a particle inversion and early warning module.

[0057] The signal acquisition module collects laser scattering signals and equipment operating parameters, providing raw data for subsequent analysis. It emits a monochromatic laser beam to illuminate the wear particles to be measured, collects light intensity signals at different scattering angles, and outputs the raw scattered light intensity distribution. A magnetic field sensor monitors the magnetic field strength during equipment operation, correlating magnetic field changes with scattered signal distortion. A speed sensor also collects equipment speed data to identify transient interference caused by sudden speed changes.

[0058] The signal preprocessing module is used to classify the initial scattered light intensity distribution and eliminate environmental noise. By calculating the magnetic field gradient and marking the oscillation risk period, the original scattered light intensity distribution is classified into steady-state signals and transient signals.

[0059] The signal correction module corrects for double-peaked artifacts caused by magnetic field alignment effects on rod-shaped particles. Based on T-matrix theory, a scattering kernel function for non-spherical particles is established, incorporating magnetic susceptibility and magnetic field strength to calculate the corrected scattering intensity. The steady-state signal is then decomposed into morphological contributions and noise.

[0060] The phase compensation module eliminates phase shifts in magnetic moment oscillations caused by sudden speed changes. It performs a short-time Fourier transform on the transient signal to extract the dominant frequency. It then calculates and predicts the phase shift to compensate for the transient signal. The steady-state and compensated transient signals are weighted and combined to generate a composite signal.

[0061] The signal reconstruction module strips away magnetic field artifacts and extracts the true scattering characteristics of the particles. It dynamically removes oscillation interference based on the magnetic field gradient and then uses a wavelet transform to extract the equatorial doublet angular distance to distinguish single-particle and multi-particle signals. It uses a unit pulse function to extract the true scattering distribution and outputs the reconstructed true scattering signal.

[0062] The particle inversion and warning module inverts the geometric dimensions of wear debris particles to provide wear warnings. Using an improved T-matrix method, it fits the major and minor axes and calculates the equivalent volume diameter. If the equivalent volume diameter exceeds the threshold N times consecutively, a wear alarm is triggered.

[0063] Those skilled in the art will appreciate that all or part of the steps in the above-mentioned embodiment methods can be accomplished by instructing the relevant hardware through a program. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may 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.

[0064] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to in detail. For the above embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For relevant parts, please refer to the partial description of the method embodiments.

[0065] The above embodiments provide a detailed introduction to the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A laser particle size analyzer inverse Fourier transform particle cross detection method, characterized in that: The method comprises the following steps: The original scattered light intensity signal and magnetic field strength data are collected, and the magnetic field gradient is calculated based on the magnetic field strength data. The magnetic field gradient is used to calculate the predicted phase offset used to eliminate signal distortion caused by sudden rotational speed changes. The oscillation risk period is identified based on the magnetic field gradient and a preset risk determination threshold. The original scattered light intensity signal in the oscillation risk period is marked as a transient signal, and the others are marked as steady-state signals. The double-peaked pseudo signal of the steady-state signal caused by the directional arrangement of the magnetic field is corrected by the morphological characteristics of the wear debris particles and the magnetic field coupling effect; the phase jump caused by mechanical interference is compensated in the transient signal by time-frequency analysis; the steady-state signal and the transient signal are weighted and fused into a composite signal; During the oscillation risk period, the magnetic field interference component is stripped from the composite signal to obtain a de-oscillation phase domain signal; time-frequency analysis is performed on the de-oscillation phase domain signal to determine the bimodal characteristic parameters, and the true scattering characteristics are calculated; the morphological characteristics of the wear debris particles are inverted based on the results of the true scattering characteristics, and the equipment wear warning is triggered based on the inversion results.

2. The method according to claim 1, characterized in that The method of correcting the double-peak pseudo signal of the steady-state signal caused by the directional arrangement of the magnetic field by using the morphological characteristics of the wear debris particles and the magnetic field coupling effect includes: The morphological characteristics of wear debris particles are obtained based on the wear debris particle image, the main axis of the wear debris particle shape is identified, and the lengths of the major and minor axes are determined; a scattering kernel function for non-spherical wear debris particles is established, and a magnetic coupling term is introduced to correct the scattering intensity in the scattering kernel function; Decompose the steady-state signal into morphological feature contribution and noise, that is: ； Where, is a steady-state signal; m represents the number of types of wear debris particles with different morphological characteristics; is the weight corresponding to the i-th category of wear particles; represents the scattering intensity of the i-th category of wear debris particles; For noise; The second-order derivative, which can reveal the concave and convex features of the steady-state signal, is calculated, and the number of extreme points of the second-order derivative is identified. If the second-order derivative has two extreme points near the equatorial plane, it indicates that the steady-state signal is a multi-particle signal. If the second-order derivative has only one extreme point near the equatorial plane, it is determined to be a single-particle signal.

3. The method according to claim 1, characterized in that The method of extracting a transient signal through time-frequency analysis to compensate for a phase jump caused by mechanical interference includes: The transient signal is divided into preset time windows, and the Fourier transform is performed on the signal in each time window to find the transform result at each time delay. The main frequency with the strongest energy; The main frequency is matched with the frequency of the equipment speed change. If the two frequency changes match, the phase information is extracted, that is, the phase jump caused by mechanical interference.

4. The method according to claim 1, wherein The method of stripping the magnetic field interference component from the composite signal is: ； Where, is the de-oscillation phase domain signal; is a composite signal; is the fundamental oscillation function; is the scaling factor; is the oscillation frequency modulation factor; is the predicted phase offset.

5. The method according to claim 4, characterized in that The method for calculating the true scattering characteristics is: The scale range of the wavelet transform is set based on the peak width W of the oscillating phase domain signal; Perform discrete wavelet transform on the oscillating phase domain signal and calculate the wavelet coefficients; Step by step, the wavelet coefficients of each scale are checked within the scale range of the wavelet transform, and the corresponding peak clarity is calculated. The scale that maximizes the peak clarity is selected as the final scale, and the local maximum of the wavelet coefficients at this scale is calculated to determine the significant peak. The two strongest local maxima are selected from the set of significant peaks and defined as double peaks; The double peak angular distance is calculated by the position angles of the two peaks to accurately identify the morphological characteristics of wear debris particles and improve the inversion accuracy; The double-peak angular offset used to correct the measurement error caused by the magnetic field is calculated using the magnetic field gradient, material parameters, and the ratio of the major and minor axes of the wear debris particles. Based on the double-peak angular distance and the double-peak angular distance offset, when the magnetic field is known, the artifact offset caused by the magnetic field is subtracted from the measured double-peak angular distance to obtain the true double-peak angular distance; The de-oscillated phase domain signal is multiplied by a unit pulse function to extract the true scattered signal intensity distribution.

6. The method according to claim 5, characterized in that The calculation formula of the true scattered signal intensity distribution is: ； Where, is the real scattered signal intensity distribution after reconstruction; is the convolution operator; is the unit pulse function; is the true bimodal angular distance; is the scattering angle.

7. The method according to claim 6, characterized in that The inversion of the morphological characteristics of the wear debris particles based on the results of the true scattering characteristics includes: ； Where, Indicates the scattering angle of wear debris particles The scattering intensity at ; n is the order of the scattering mode; and is the correlation coefficient related to the major-minor axis ratio and scattering angle of wear debris particles; and is the contact function related to the cosine of the scattering angle; The reconstructed real scattering signal intensity distribution and scattering intensity are fitted with the linear least square method to invert the major axis and minor axis of the wear debris particles, namely: ； Where C is the calibrated concentration correction factor is the long axis inversion value of the wear debris particle; is the short axis inversion value of the wear debris particle.

8. The method according to claim 7, characterized in that The method of triggering equipment wear warning based on the inversion result is: Calculate the equivalent volume diameter of the wear debris particles and compare the equivalent volume diameter of the wear debris particles with the preset volume threshold. When the equivalent volume diameter exceeds the volume threshold for N consecutive times, the equipment wear warning is triggered.

9. The method according to claim 1, characterized in that The magneto-optical coupling coefficient is determined as follows: Calculate the electric field intensity when the laser beam reaches the surface of the wear debris particles, that is: ； Where, is the electric field intensity when the laser beam propagates to the surface of the wear debris particles; is the initial electric field strength; is the absorption coefficient of the hydrocarbon-based carrier liquid; z is the propagation distance; The total scattered intensity is calculated by integrating the scattered patterns, namely: ； Where, The wear particles are scattered at a specific angle Total field intensity under ; is the distribution function of wear debris particles; is the scattering pattern related to the interaction intensity between wear debris particles and the incident laser beam; The magneto-optical coupling coefficient is calculated based on the total scattering intensity and the electric field intensity, namely: ； Where, is the dielectric constant of vacuum; is the incident field intensity; is the scattered field intensity, and the calculation formula is: ； in, To monitor the volume of a container; is the volume of wear debris particles.

10. A system for implementing the laser particle size analyzer inverse Fourier transform particle cross detection method according to any one of claims 1 to 9, characterized in that: include: Signal acquisition module, used to collect laser scattering signals and equipment operating parameters; Signal preprocessing module, used to classify the initial scattered light intensity distribution and eliminate environmental noise; Signal correction module, used to correct the double-peak artifact signal based on the magnetic field oriented alignment effect of rod-shaped particles; Phase compensation module, used to eliminate the phase offset of magnetic moment oscillation caused by sudden speed change; Signal reconstruction module, used to remove magnetic field artifacts and extract the true scattering characteristics of particles; The particle inversion and early warning module is used to invert the geometric size of wear debris particles and realize wear early warning.

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