Quantitative x-ray scattering intensity anisotropy evaluation system based on free electron laser

Abstract

The application relates to the technical field of intelligent diagnosis, and discloses a quantitative X-ray scattering intensity anisotropy evaluation system based on a free electron laser, which comprises a signal excitation and collection end, a dynamic quantitative analysis end and a power station evaluation adaptation end; the free electron laser light source is adopted, X-rays generated by the free electron laser light source have intrinsic high-flux and ultrashort pulse characteristics, and the X-rays lay a foundation for obtaining high-contrast scattering signals inside materials. The system further introduces background noise filtering and data layering technology, pre-processes and hierarchically separates the collected scattering signals, thereby supporting early discrimination and evaluation of the equipment state; through signal synchronization and time sequence construction, the external field loading can be corresponded to the scattering response of the material, the dynamic tracking of the anisotropy evolution process of the material under the action of the external field is realized, and dynamic data support is provided for predicting the equipment life and formulating a maintenance strategy.

Description

Technical Field

[0001] This invention relates to the field of intelligent diagnostic technology, specifically to a quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers. Background Technology

[0002] X-ray scattering is a physical process in which the direction or energy of X-rays changes when they interact with matter. Its mechanisms include key phenomena in astronomical scenarios such as inverse Compton scattering and Mie scattering. In astronomy, inverse Compton scattering can explain the X-ray radiation produced by the collision of high-energy electrons and low-energy photons. This process is widely present in the inner region of black hole accretion disks and in the interaction between cosmic ray electrons and microwave background photons.

[0003] Currently, in the field of microstructural health status assessment of insulation materials for power equipment in power distribution stations, traditional X-ray scattering technology relies on conventional X-ray sources, which have limited brightness and pulse time resolution. When conducting early aging and defect detection of materials, it is impossible to distinguish between weak anisotropic changes and background noise in the scattered signal in real time. When early stress concentration occurs inside the material and the micro-defect evolution signal is submerged by noise, it will cause missed and false alarms in the condition assessment, and the earlyness and accuracy of the assessment cannot be guaranteed.

[0004] Therefore, a quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers is proposed to solve the above problems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a quantitative X-ray scattering intensity anisotropy evaluation system based on free-electron lasers, which solves the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a quantitative X-ray scattering intensity anisotropy assessment system based on free electron laser, the system comprising a signal excitation and acquisition end, a dynamic quantitative analysis end, and a power distribution station assessment and adaptation end; The signal excitation and acquisition end is used to generate X-rays through a free electron laser source, to control and excite the X-ray scattering signal from the power equipment sample under test in the substation in real time, and to perform high-speed acquisition and preprocessing of the scattering pattern. The power equipment sample under test includes key insulating material components in the substation equipment that bear mechanical and electrical stress. The dynamic quantization analysis terminal is used to receive and process the scattering pattern, distinguish scattering signals of different intensities through background noise filtering and data layering technology, and use quantization algorithms to calculate the anisotropy parameters of scattering intensity in real time, and synchronously and dynamically track the evolution process of material microstructure anisotropy. The substation assessment adapter is used to evaluate and classify the mechanical stress distribution, insulation aging degree, and potential defects of the power equipment sample under test in real time based on the quantified anisotropic parameters and in combination with the pre-set substation equipment material standard database and aging failure model.

[0007] Preferably, the signal excitation and acquisition end includes a free electron laser control module, a sample environment interaction module, and a scattering signal acquisition module; The free-electron laser control module includes a laser parameter preset unit, an optical path control unit, and a light source status monitoring unit; The laser parameter preset unit is used to set free electron laser excitation parameters that match the material types of different power distribution station equipment. The excitation parameters include X-ray photon energy, pulse width, repetition frequency, and beam size. The optical path control unit is used to acquire the shape and position information of the power equipment sample under test, and adjust the beam direction, focus point and incident angle based on the information. The light source status monitoring unit is used to monitor the brightness stability, beam center position, and pulse time jitter of the free electron laser light source in real time, and sends a primary warning signal to the dynamic quantization analysis terminal when the parameters deviate from the preset range.

[0008] Preferably, the sample environment interaction module includes a sample stage control unit, an in-situ external field loading unit, and an environment simulation unit; The sample stage control unit is used to carry and fix the power equipment sample to be tested from the power distribution station, and can drive the sample to perform three-dimensional translation, rotation and tilting movements according to preset programs and instructions. The in-situ external field loading unit is used to apply an in-situ external field simulating actual operating conditions to the sample during the detection process. The in-situ external field includes a temperature field, a mechanical stress field, and an electric field. The environmental simulation unit is used to simulate a real environment in the sample chamber that is consistent with the actual operating conditions of the power distribution station equipment. The environment includes specific temperature, humidity and insulating gas atmosphere.

[0009] Preferably, the scattering signal acquisition module includes a high-speed area array detector unit, a raw data processing unit, and a signal synchronization unit; The high-speed array detector unit is used to capture two-dimensional scattering patterns generated after X-rays interact with the sample according to a preset time sequence. The scattering patterns include Debye-Scheller rings and diffuse scattering signals. The raw data processing unit is used to perform preliminary preprocessing on the acquired two-dimensional scattering patterns, including background subtraction, geometric correction, and polarization factor correction, to obtain clean scattering data that can be used for intensity analysis. The signal synchronization unit is used to receive the external field change signal applied by the in-situ external field loading unit, and synchronize it with each frame of scattering pattern collected by the high-speed array detector unit by time stamping, so as to establish the correspondence between the external field structure evolution.

[0010] Preferably, the dynamic quantization analysis terminal includes a data filtering and layering module, an anisotropic quantization module, and a dynamic evolution tracking module; The data filtering and layering module includes a noise analysis unit and an intensity layering unit; The noise analysis unit is used to analyze the degree of interference of experimental technical noise, background scattering noise and system electronic noise on the fluctuation of sample scattering intensity, and to establish a dynamic noise background model. The intensity layering unit is used to classify the preprocessed two-dimensional scattering pattern into high-intensity scattering signal regions and medium-intensity scattering signal regions based on the absolute median difference filtering algorithm, and to separate and label the signals at different intensity levels, outputting the labeled two-dimensional scattering intensity data.

[0011] Preferably, the anisotropy quantization module includes a vectorization analysis unit and a parameter calculation unit; The vectorization analysis unit is used to perform full vectorization analysis on the layered two-dimensional scattering intensity data, integrate the scattering pattern along different azimuth angles, and obtain the distribution function of scattering intensity with azimuth angle, i.e., a one-dimensional anisotropy curve. The parameter calculation unit is used to calculate parameters that quantify the degree of anisotropy based on the one-dimensional anisotropy curve. The parameters include the anisotropy intensity ratio, orientation order parameter, and Hermanns orientation factor, which convert the degree of anisotropy of the material structure into a comparable numerical index.

[0012] Preferably, the dynamic evolution tracking module includes a time series construction unit and an evolution pattern recognition unit; The time series construction unit is used to arrange the anisotropic parameters that are collected and quantized in time order using the time markers provided by the signal synchronization unit, so as to form a time evolution sequence corresponding to the collection time order. The evolution pattern recognition unit is used to analyze the time evolution sequence, identify the dynamic patterns of anisotropic state changes of materials under the action of external fields, and compare them with theoretical models of the evolution of material microstructure.

[0013] Preferably, the substation assessment adapter includes an equipment and material database module, a condition assessment model module, and a risk assessment and reporting module; The equipment material database module includes a standard parameter storage unit and an aging spectrum unit; The standard parameter storage unit is used to establish and store the standard X-ray scattering anisotropy parameter benchmarks of power equipment materials for substations of different models, batches and health conditions under a defect-free state, forming a standard parameter range. The aging spectrum unit is used to store characteristic spectra and correlation models of the evolution of anisotropy parameters of typical insulating materials under combined thermal, electrical, and mechanical stress aging with aging time and aging degree.

[0014] Preferably, the state assessment model module includes a real-time comparison unit and a defect location unit; The real-time comparison unit is used to compare the anisotropic parameters calculated in real time by the anisotropic quantification module with the standard range in the standard parameter storage unit in real time to determine whether the current sample state deviates from the health benchmark. The defect localization unit is used to spatially locate micro-defects, stress concentration areas, and aging initiation points inside the material when an abnormal anisotropic signal is detected, by combining the azimuth distribution characteristics of the scattered signal and the scanning position information of the sample stage.

[0015] Preferably, the risk assessment and reporting module includes a failure probability prediction unit and an assessment report generation unit; The failure probability prediction unit is used to predict the probability of the power equipment sample under test experiencing operational failure in the future operating cycle based on the results of real-time comparison and defect location, and to classify it into safety, caution, warning and high-risk levels. The assessment report generation unit is used to automatically generate a structured assessment report containing anisotropic parameter evolution curves, defect location images, risk levels, and maintenance recommendations, and outputs it to the substation equipment management system through a data interface. At the same time, when the risk level reaches the warning level, an escalation alarm is executed.

[0016] Compared with the prior art, the present invention provides a quantitative X-ray scattering intensity anisotropy evaluation system based on free-electron lasers, which has the following beneficial effects: 1. In this invention, a free-electron laser source is employed, which generates X-rays with intrinsic high throughput and ultrashort pulse characteristics, laying the foundation for obtaining high-contrast scattering signals from within materials. The system further incorporates background noise filtering and data layering techniques to preprocess and hierarchically separate the acquired scattering signals, enabling the extraction of weak anisotropic scattering information originating from early material damage, thereby supporting early identification and assessment of equipment status.

[0017] 2. In this invention, during material performance evolution analysis, signal synchronization and time series construction enable the mapping between external field loading and material scattering response, achieving dynamic tracking of the anisotropic evolution process of materials under external field action. This allows the system to capture and identify the dynamic patterns of material microstructure changes under external stress, thereby establishing the correlation between microstructure state changes and macroscopic performance evolution, and identifying aging and failure modes, providing dynamic data support for predicting equipment lifespan and developing maintenance strategies.

[0018] 3. In this invention, when assessing the actual condition of substation equipment, the system integrates sample environment interaction with the substation assessment adapter. This allows the system to simulate the actual operating conditions of the equipment and, based on quantitative analysis, compare the results with a standard database and aging failure models in real time for risk assessment. This ensures that the assessment conclusions align with the on-site operation and maintenance needs of the substation. It not only enables defect location and classification but also automatically generates structured reports containing maintenance recommendations. This achieves a seamless transition from laboratory measurements to intelligent on-site diagnosis, improving the practicality of condition assessment and decision-making efficiency. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the architecture of the quantitative X-ray scattering intensity anisotropy evaluation system based on free-electron laser of the present invention. Figure 2 This is a functional module structure diagram of the quantitative X-ray scattering intensity anisotropy evaluation system based on free-electron laser of the present invention. Figure 3 This is a flowchart illustrating the operational steps of the quantitative X-ray scattering intensity anisotropy evaluation system based on free-electron lasers according to the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] For specific implementation examples, please refer to: Figure 1-3 A quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers, comprising a signal excitation and acquisition end, a dynamic quantitative analysis end, and a power distribution station assessment adaptation end; The signal excitation and acquisition end is used to generate X-rays through a free electron laser source, to control and excite the X-ray scattering signal from the power equipment sample under test in the substation in real time, and to perform high-speed acquisition and preprocessing of the scattering pattern. The power equipment sample under test includes key insulating material components in the substation equipment that bear mechanical and electrical stress. The dynamic quantization analysis terminal is used to receive and process scattering patterns. It distinguishes scattering signals of different intensities through background noise filtering and data layering technology, and uses quantization algorithms to calculate the anisotropy parameters of scattering intensity in real time, synchronously and dynamically tracking the evolution of the anisotropy of the material's microstructure. The substation assessment adapter is used to perform real-time assessment and grade determination of the mechanical stress distribution, insulation aging degree and potential defects of the power equipment sample under test based on the quantified anisotropic parameters, combined with the pre-set substation equipment material standard database and aging failure model.

[0022] The signal excitation and acquisition end includes a free electron laser control module, a sample environment interaction module, and a scattering signal acquisition module; The free-electron laser control module includes a laser parameter preset unit, an optical path control unit, and a light source status monitoring unit; The laser parameter preset unit is used to set free electron laser excitation parameters that match the material types of different power distribution station equipment. The excitation parameters include X-ray photon energy, pulse width, repetition frequency, and beam size. The optical path control unit is used to acquire the shape and position information of the power equipment sample under test, and adjust the beam direction, focus point and incident angle based on the information; The light source status monitoring unit is used to monitor the brightness stability, beam center position and pulse time jitter of the free electron laser source in real time, and send a primary warning signal to the dynamic quantization analysis terminal when the parameters deviate from the preset range.

[0023] The sample environment interaction module includes a sample stage control unit, an in-situ external field loading unit, and an environmental simulation unit; The sample stage control unit is used to carry and fix the power equipment sample from the substation, and can drive the sample to perform three-dimensional translation, rotation and tilting movements according to preset programs and instructions. The in-situ external field loading unit is used to apply an in-situ external field to the sample during the detection process to simulate the actual operating conditions. The in-situ external field includes temperature field, mechanical stress field and electric field. The environmental simulation unit is used to simulate a real environment in the sample chamber that is consistent with the actual operating conditions of the power distribution station equipment. The environment includes specific temperature, humidity and insulating gas atmosphere.

[0024] The scattering signal acquisition module includes a high-speed area array detector unit, a raw data processing unit, and a signal synchronization unit; The high-speed array detector unit is used to capture two-dimensional scattering patterns generated after X-rays interact with the sample in a preset time sequence. The scattering patterns include Debye-Scherer rings and diffuse scattering signals. The raw data processing unit performs preliminary preprocessing on the acquired two-dimensional scattering patterns, including background subtraction, geometric correction, and polarization factor correction, to obtain clean scattering data suitable for intensity analysis. This includes the following steps: Acquire the system background pattern intensity I under the same optical path and detection conditions, without a sample placed. bg (x,y); From the intensity I of the acquired original two-dimensional scattering pattern raw Subtracting the system background pixel by pixel in (x,y) yields the intensity I of the background-subtracted scattering pattern. sub (x,y), its calculation formula is: I sub (x,y)=I raw (x,y)-I bg (x,y); Among them, I bg (x,y) represents the intensity of the system background map acquired without a sample, I raw (x,y) represents the intensity of the original two-dimensional scattering pattern acquired, I sub (x,y) represents the intensity of the scattering pattern after background subtraction, where x,y are the pixel coordinates of the detector; Using diffraction patterns generated from standard calibration samples with known spacing, a mapping relationship between detector pixel coordinates (x, y) and scattering vector q space is established. Based on this mapping relationship, the intensity I of the scattering pattern after background subtraction is calculated. sub The coordinates (x, y) are transformed and interpolated to correct the scattering intensity data I, which is uniformly distributed in the q-space. geo (q); Based on the polarization state of the X-ray incident beam, the scattering geometry, and the direction of the scattering vector q, the polarization attenuation factor P(q) corresponding to each data point is calculated, and the geometrically corrected scattering intensity data I is then processed. geo (q) Divide by the corresponding polarization attenuation factor to obtain the final pure scattering data I after polarization factor correction. corr (q), its calculation formula is: ; Among them, I corr (q) represents the final purified scattering data after polarization factor correction, I geo (q) represents the scattering intensity data after geometric correction, and P(q) is the polarization attenuation factor. The signal synchronization unit is used to receive the external field change signal applied by the in-situ external field loading unit and synchronize it with each frame of scattering pattern acquired by the high-speed array detector unit by time stamping, so as to establish the correspondence between the external field structure evolution.

[0025] The dynamic quantitative analysis module includes a data filtering and layering module, an anisotropic quantization module, and a dynamic evolution tracking module. The data filtering and stratification module includes a noise analysis unit and an intensity stratification unit; The noise analysis unit is used to analyze the interference of experimental technical noise, background scattering noise, and system electronic noise on the fluctuations of sample scattering intensity, and to establish a dynamic noise background model, including the following steps: Experimental technical noise analysis: Under fixed detection conditions, repeated scattering measurements were performed on a standard uniform sample to obtain a series of scattering patterns; the standard deviation of the intensity value of each pixel was calculated. This quantifies the experimental technical noise level caused by light source brightness fluctuations and beam position drift. The calculation formula is as follows: ; in, I represents the standard deviation of experimental technique noise caused by light source jitter and beam drift at pixel (x,y). i (x,y) represents the intensity value measured at pixel (x,y) for the i-th time. Let N be the average intensity value at pixel (x,y), where N is the total number of repeated scattering measurements performed on the standard uniform sample; Background scattering noise analysis: Under the same detection and environmental conditions, the sample to be tested is removed, and background scattering patterns generated by air in the optical path, the sample stage, and the chamber window are collected. bkg (x,y) is used as the static spatial distribution model of background scattering noise. System electronic noise analysis: Dark field pattern I acquired by a high-speed area array detector unit under the condition of X-ray source shutdown. dark (x,y), calculate the average value μ of the dark field pattern. dark With standard deviation σ dark This characterizes the basis and fluctuations of electronic noise in the detector readout circuit. Dynamic noise background model synthesis: The noise components obtained from the above analysis are synthesized to establish a dynamic noise background model N. model (x,y), this model characterizes the original measurement signal I in any single measurement, excluding the sample signal. raw The total expected noise contribution of (x,y) is expressed as follows: ; Where, N model (x,y) represents the dynamic noise background model, I bkg (x,y) represents the background scattering pattern generated by the air in the optical path, the sample stage, and the cavity window.dark (x, y) is a dark-field pattern collected by the detector when the light source is turned off, and F is a noise coverage factor set according to the confidence requirement; The intensity layering unit is configured to divide the preprocessed two-dimensional scattering pattern into a high-intensity scattering signal region and a medium-intensity scattering signal region based on the median absolute deviation filtering algorithm, perform separation marking on signals of different intensity levels, and output marked two-dimensional scattering intensity data, which comprises the following steps: calculate the median M of all pixel intensity values in the two-dimensional scattering pattern, calculate the absolute value of the difference between the intensity value of each pixel and the median, and obtain an absolute deviation set ; calculate the median of the absolute deviation set, that is, the median absolute deviation MAD, the definition of which is as follows: ; wherein, I i represents the intensity value of the i-th pixel, median(•) represents a median operation, and M is the median of the pixel intensity values; based on the median M of the pixel intensity values, the layering threshold T for distinguishing high-intensity signals and medium-intensity signals is dynamically calculated and determined according to a preset intensity layering coefficient k and the median absolute deviation MAD, specifically calculated by the following formula: ; wherein, k is the intensity layering coefficient, and T is the layering threshold for distinguishing high-intensity and medium-intensity signals; when the pixel intensity I i ≧T, the pixel is determined to belong to the high-intensity scattering signal region; when I i <T, the pixel is determined to belong to the medium-intensity scattering signal region.

[0026] the anisotropy quantification module comprises a vectorization analysis unit and a parameter calculation unit; the vectorization analysis unit is configured to perform omni-directional vectorization analysis on the layered two-dimensional scattering intensity data, integrate the scattering pattern along different azimuth angles, and obtain a distribution function of scattering intensity along with azimuth angles, that is, a one-dimensional anisotropy curve, which comprises the following steps: taking the center of the two-dimensional scattering intensity data as the origin, establish a polar coordinate system (r, θ), from 0 degree to 360 degrees, with a preset azimuth angle interval Δθ as the step size, integrate the two-dimensional scattering intensity data radially along each azimuth θ j direction to obtain the integrated intensity S(θ j ) at this azimuth angle, the calculation formula is: ; wherein, I(r,θ j ) represents the scattering intensity value at the polar coordinate (r,θ j ), rmin and r max For the preset radial integration range, θ j Let be the j-th azimuth angle, and r be the radial distance in polar coordinates; The obtained series S(θ) j Arranged in azimuth order, a one-dimensional anisotropic curve S(θ) of scattering intensity distribution with azimuth angle is generated; The parameter calculation unit is used to calculate parameters that quantify the degree of anisotropy based on a one-dimensional anisotropy curve. These parameters include the anisotropy intensity ratio, orientation order parameter, and Hermanns orientation factor, transforming the degree of anisotropy of the material structure into a comparable numerical index. The process includes the following steps: Based on the one-dimensional anisotropic curve S(θ), find its maximum scattering intensity value S. max With minimum scattering intensity value S min ; Calculate the ratio of the maximum scattering intensity to the minimum scattering intensity as the anisotropic intensity ratio R: ; Perform a Fourier series expansion on the one-dimensional anisotropic curve S(θ) and extract its second-order orientation factor. As an orientation order parameter, its calculation formula is: ; in, For orientation order parameters, It is a second-order Legendre polynomial, and θ is the azimuth angle; Based on the one-dimensional anisotropy curve S(θ), the Hermann orientation factor f is calculated using the following formula: ; Where Φ is the angle between the characteristic orientation axis of the material's internal microstructure and the reference direction. Its second-order orientation cosine average value is derived from the orientation order parameter. Through relational formulas It is deduced that, i.e. .

[0027] The dynamic evolution tracking module includes a time series construction unit and an evolution pattern recognition unit; The time series construction unit is used to arrange the anisotropic parameters that are acquired and quantized in time sequence using the time stamps provided by the signal synchronization unit, forming a time evolution sequence corresponding to the acquisition time sequence; The evolution pattern recognition unit is used to analyze the time evolution sequence, identify the dynamic patterns of anisotropic state changes of materials under the action of external fields, and compare them with theoretical models of the evolution of material microstructure. The identification of the dynamic modes of anisotropic state changes in materials under the action of an external field includes the following steps: The anisotropic parameters, denoted as A(t), are obtained from the time evolution sequence and arranged in chronological order, where t is time. Analyze the trend of parameter A(t) with time t in the time evolution sequence; Calculate the rate of change of the parameter within adjacent time windows. This quantifies its changing trend. The rate of change is calculated using the discrete difference method, and its formula is as follows: ; Among them, T n With T n+1 For two adjacent time points in the sequence, A(t) n ) and A(t n+1 ) represents the corresponding anisotropy parameter value; By judgment The sign and magnitude of the parameter are used to match the changing trend with a pre-stored library of typical patterns. This library includes monotonically increasing parameter patterns, monotonically decreasing parameter patterns, parameter first increasing then decreasing relaxation patterns, and parameter periodic fluctuation patterns. The specific judgment method is based on a series of calculated... The values ​​are identified, and their sign continuity, zero crossings, and extreme points in the time series are determined. The presented feature combinations are then matched with a pre-stored library of typical patterns. When all If , then it matches a monotonically increasing parameter pattern; when all If the parameter is monotonically decreasing, then it matches the pattern; when If the sequence shows a zero-crossing point where the value changes from positive to negative, it matches a relaxation pattern where the parameter first increases and then decreases; when If the sequence shows periodic alternation of signs, it matches a parametric periodic fluctuation pattern; Based on the matching results, the specific dynamic pattern identifier currently identified is output; The comparison with theoretical models of material microstructure evolution includes the following steps: Based on the type of in-situ external field applied by the in-situ external field loading unit, the corresponding pre-stored theoretical model is invoked. The theoretical model provides the predicted relationship between the material's microstructure parameters and anisotropy parameters under a specific external field. ; The anisotropy parameter A actually measured in the time evolution sequence meas (t) Input the theoretical model and calculate the theoretical prediction value A. pred (t); The actual measured values ​​are compared with the theoretical predicted values, and their root mean square deviation (RMSD) is calculated as a consistency evaluation index. ; Where, N pts A represents the total number of data points in the time series. meas (t i ) represents the time point t i The anisotropy parameter value obtained from actual measurement, A pred (t i ) represents the time point t i The anisotropy parameter values ​​predicted by the theoretical model, t i This refers to the i-th time point; The substation assessment and adaptation module includes an equipment and materials database module, a condition assessment model module, and a risk assessment and reporting module. The equipment and materials database module includes a standard parameter storage unit and an aging spectrum unit; The standard parameter storage unit is used to establish and store the standard X-ray scattering anisotropy parameter benchmarks of power equipment materials for substations of different models, batches and health conditions under defect-free conditions, forming a standard parameter range; The aging profile unit is used to store characteristic profiles and correlation models of the evolution of anisotropy parameters of typical insulating materials under combined thermal, electrical, and mechanical stress aging with aging time and aging degree. The establishment and retrieval of this correlation model includes the following steps: The anisotropy of X-ray scattering intensity was evaluated on standard samples at different aging stages to obtain their anisotropy parameter vector A. vec And record the corresponding aging time t aging Compared with the macroscopic performance test results P; A mathematical correlation model between anisotropic parameters, aging time, and macroscopic performance is established using multiple linear regression. The expression is as follows: ; Among them, A vec Let w be the anisotropic parameter vector. t and b t These are the weight coefficient vector and bias term of the model for predicting aging time, respectively. p and b p These are the weight coefficient vector and bias term of the model for predicting macroscopic performance, respectively. aging P represents the predicted aging time, P represents the predicted macroscopic performance, and T represents the transpose of the vector. The condition assessment model module includes a real-time comparison unit and a defect location unit; The real-time comparison unit is used to compare the anisotropic parameters generated in real time by the anisotropic quantification module with the standard range in the standard parameter storage unit in real time to determine whether the current sample state deviates from the healthy baseline. The defect localization unit is used to spatially locate microscopic defects, stress concentration areas, and aging initiation points within the material when abnormal anisotropic signals are detected, by combining the azimuth distribution characteristics of the scattered signals and the scanning position information of the sample stage. The process includes the following steps: When at a specific scan position coordinate (X s ,Y s When an abnormal anisotropic signal is detected, its corresponding one-dimensional anisotropic curve S(θ) is extracted; By analyzing the one-dimensional anisotropy curve S(θ), and finding its extreme values, we can determine the dominant azimuth angle θ that causes the scattering intensity to exhibit anomalous enhancement and weakening. dominant : ; According to the dominant azimuth angle θ dominant The known relationship with the sample's crystallographic orientation and stress direction, combined with the specific scanning position coordinates (X... s ,Y s This method determines the two-dimensional planar location of micro-defects and stress concentration areas within the sample.

[0028] The risk assessment and reporting module includes a failure probability prediction unit and an assessment report generation unit; The failure probability prediction unit, based on the results of real-time comparison and defect location, calls the model in the aging spectrum unit to predict the probability of operational failure of the power equipment sample under test during its future operating cycle, and classifies it into safe, caution, warning, and high-risk levels, including the following steps: Based on the output of the real-time comparison unit, it is determined that the current anisotropy parameter A deviates from its standard range [A]. min A max The degree of D A The calculation formula is: ; Among them, D A This represents the degree to which the current anisotropy parameter value A deviates from its standard range, where A is the current anisotropy parameter value calculated in real time. min A max These are the lower and upper limits of the standard range for this parameter under healthy conditions; Based on the output of the defect localization unit, the severity and spatial distribution density ρ of the defect are determined. depect ; The above deviation level D A Defect severity and distribution density ρ depect The input feature vector F is fed into the association model in the aging map unit; The correlation model outputs a quantified failure probability value P. failureIts value range is [0,1], which represents the probability of an operational failure occurring within the set future running time window; The assessment report generation unit is used to automatically generate a structured assessment report that includes anisotropic parameter evolution curves, defect location images, risk levels, and maintenance recommendations. The report is then output to the substation equipment management system via a data interface. Additionally, when the risk level reaches the warning level, an escalation alarm is triggered.

[0029] The operation steps of the quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers are as follows: Step 1: Signal Excitation, Environmental Simulation, and Synchronous Acquisition Stage The core of this stage is to utilize a free-electron laser source to generate X-rays, excite the sample under simulated real-world substation conditions, and collect scattered signals. First, the free-electron laser control module at the signal excitation and acquisition end sets excitation parameters that match the insulating material under test. The optical path control unit automatically adjusts the beam according to the sample's shape and position, ensuring the X-rays act on a specific area of ​​the sample. Simultaneously, the in-situ external field loading unit of the sample environment interaction module applies temperature, mechanical stress, and electric fields simulating actual operating conditions to the sample, while the environment simulation unit recreates the specific temperature, humidity, and insulating gas atmosphere of a substation within the sample chamber. The high-speed area array detector unit captures, according to a preset time sequence, a two-dimensional scattering pattern containing Debye-Scheller rings and diffuse scattering signals generated after the X-rays interact with the sample. The raw data processing unit then performs preliminary preprocessing on the pattern, including background subtraction, geometric correction, and polarization factor correction, to obtain clean scattering data. The signal synchronization unit is responsible for synchronizing the change signal of the external field loading with the acquisition time of each frame of the scattering pattern, establishing a temporal correspondence for subsequent dynamic analysis.

[0030] Step Two: Noise Filtering, Parameter Quantization, and Dynamic Tracking Stage This stage involves in-depth processing of the acquired scattering data to extract and track the quantitative characteristics of anisotropy in the material's microstructure. The data filtering and layering module of the dynamic quantification analysis unit works first: its noise analysis unit establishes a dynamic noise background model by analyzing experimental technical noise, background scattering noise, and system electronic noise; the intensity layering unit, based on an absolute median filtering algorithm, automatically distinguishes the preprocessed two-dimensional scattering pattern into high-intensity and medium-intensity scattering signal regions and outputs labeled two-dimensional scattering intensity data. Next, the vectorization analysis unit of the anisotropy quantification module performs full vectorization analysis on this data, obtaining the distribution function of scattering intensity with azimuth angle by integrating along different azimuth angles, i.e., a one-dimensional anisotropy curve. Based on this curve, the parameter calculation unit calculates the anisotropy intensity ratio, orientation order parameter, and Hermanns orientation factor in real time. Finally, the time series construction unit of the dynamic evolution tracking module uses synchronous time markers to arrange the anisotropic parameters obtained in time order to form a time evolution sequence; the evolution pattern recognition unit analyzes the rate of change of the sequence parameters to identify the dynamic mode of material anisotropy under the action of external field and compares it with the theoretical model.

[0031] Step 3: Status Assessment, Risk Prediction, and Report Generation Stage This stage applies the quantitative analysis results to the actual assessment of the substation equipment condition. The equipment and material database module of the substation assessment adapter provides the assessment benchmark. Its standard parameter storage unit stores the standard parameter ranges for healthy materials, while the aging spectrum unit stores the characteristic spectra and correlation models of anisotropic parameters evolving with aging. The real-time comparison unit of the condition assessment model module compares the real-time calculated anisotropic parameters with the standard ranges to determine if the condition deviates from the healthy benchmark. When an anomaly is detected, the defect location unit combines the azimuth characteristics of the scattered signal with the sample scanning position to spatially locate microscopic defects, stress concentration areas, and aging initiation points. The failure probability prediction unit of the risk assessment and reporting module integrates the comparison and location results, calls the correlation model in the aging spectrum, predicts the probability of future operational failures of the sample, and classifies them into safe, caution, warning, and high-risk levels. Finally, the assessment report generation unit automatically generates a structured report containing parameter curves, defect images, risk levels, and maintenance recommendations, outputting it to the management system, and executing an escalation alarm when the risk reaches the warning level.

[0032] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0033] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers, characterized in that: The system includes a signal excitation and acquisition terminal, a dynamic quantization analysis terminal, and a power distribution station evaluation and adaptation terminal. The signal excitation and acquisition end is used to generate X-rays through a free electron laser source, to control and excite the X-ray scattering signal from the power equipment sample under test in the substation in real time, and to perform high-speed acquisition and preprocessing of the scattering pattern. The power equipment sample under test includes key insulating material components in the substation equipment that bear mechanical and electrical stress. The signal excitation and acquisition end includes a free electron laser control module, a sample environment interaction module, and a scattering signal acquisition module. The scattering signal acquisition module includes a high-speed area array detector unit, a raw data processing unit, and a signal synchronization unit. The dynamic quantization analysis terminal is used to receive and process the scattering pattern, distinguish scattering signals of different intensities through background noise filtering and data layering technology, and use quantization algorithms to calculate the anisotropy parameters of scattering intensity in real time, and synchronously and dynamically track the evolution process of material microstructure anisotropy. The dynamic quantization analysis terminal includes a data filtering and layering module, an anisotropic quantization module, and a dynamic evolution tracking module. The dynamic evolution tracking module includes a time series construction unit and an evolution pattern recognition unit. The time series construction unit is used to arrange the anisotropic parameters that are collected and quantized in time order using the time markers provided by the signal synchronization unit, so as to form a time evolution sequence corresponding to the collection time order. The evolution pattern recognition unit is used to analyze the time evolution sequence, identify the dynamic patterns of anisotropic state changes of materials under the action of external fields, and compare them with theoretical models of material microstructure evolution. The substation assessment adapter is used to evaluate and classify the mechanical stress distribution, insulation aging degree, and potential defects of the power equipment sample under test in real time based on the quantified anisotropic parameters and in combination with the pre-set substation equipment material standard database and aging failure model.

2. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron laser according to claim 1, characterized in that: The signal excitation and acquisition end includes a free electron laser control module, a sample environment interaction module, and a scattering signal acquisition module; The free-electron laser control module includes a laser parameter preset unit, an optical path control unit, and a light source status monitoring unit; The laser parameter preset unit is used to set free electron laser excitation parameters that match the material types of different power distribution station equipment. The excitation parameters include X-ray photon energy, pulse width, repetition frequency, and beam size. The optical path control unit is used to acquire the shape and position information of the power equipment sample under test, and adjust the beam direction, focus point and incident angle based on the information. The light source status monitoring unit is used to monitor the brightness stability, beam center position, and pulse time jitter of the free electron laser light source in real time, and sends a primary warning signal to the dynamic quantization analysis terminal when the parameters deviate from the preset range.

3. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers according to claim 2, characterized in that: The sample environment interaction module includes a sample stage control unit, an in-situ external field loading unit, and an environment simulation unit. The sample stage control unit is used to carry and fix the power equipment sample to be tested from the power distribution station, and can drive the sample to perform three-dimensional translation, rotation and tilting movements according to preset programs and instructions. The in-situ external field loading unit is used to apply an in-situ external field simulating actual operating conditions to the sample during the detection process. The in-situ external field includes a temperature field, a mechanical stress field, and an electric field. The environmental simulation unit is used to simulate a real environment in the sample chamber that is consistent with the actual operating conditions of the power distribution station equipment. The environment includes specific temperature, humidity and insulating gas atmosphere.

4. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers according to claim 3, characterized in that: The scattering signal acquisition module includes a high-speed area array detector unit, a raw data processing unit, and a signal synchronization unit; The high-speed array detector unit is used to capture two-dimensional scattering patterns generated after X-rays interact with the sample according to a preset time sequence. The scattering patterns include Debye-Scheller rings and diffuse scattering signals. The raw data processing unit is used to perform preliminary preprocessing on the acquired two-dimensional scattering patterns, including background subtraction, geometric correction, and polarization factor correction, to obtain clean scattering data that can be used for intensity analysis. The signal synchronization unit is used to receive the external field change signal applied by the in-situ external field loading unit, and synchronize it with each frame of scattering pattern collected by the high-speed array detector unit by time stamping, so as to establish the correspondence between the external field structure evolution.

5. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron laser according to claim 1, characterized in that: The dynamic quantization analysis terminal includes a data filtering and layering module, an anisotropic quantization module, and a dynamic evolution tracking module. The data filtering and layering module includes a noise analysis unit and an intensity layering unit; The noise analysis unit is used to analyze the degree of interference of experimental technical noise, background scattering noise and system electronic noise on the fluctuation of sample scattering intensity, and to establish a dynamic noise background model. The intensity layering unit is used to classify the preprocessed two-dimensional scattering pattern into high-intensity scattering signal regions and medium-intensity scattering signal regions based on the absolute median difference filtering algorithm, and to separate and label the signals at different intensity levels, outputting the labeled two-dimensional scattering intensity data.

6. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron laser according to claim 5, characterized in that: The anisotropic quantization module includes a vectorization analysis unit and a parameter calculation unit; The vectorization analysis unit is used to perform full vectorization analysis on the layered two-dimensional scattering intensity data, integrate the scattering pattern along different azimuth angles, and obtain the distribution function of scattering intensity with azimuth angle, i.e., a one-dimensional anisotropy curve. The parameter calculation unit is used to calculate parameters that quantify the degree of anisotropy based on the one-dimensional anisotropy curve. The parameters include the anisotropy intensity ratio, orientation order parameter, and Hermanns orientation factor, which convert the degree of anisotropy of the material structure into a comparable numerical index.

7. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron laser according to claim 5, characterized in that: The substation assessment and adaptation terminal includes an equipment and material database module, a condition assessment model module, and a risk assessment and reporting module. The equipment material database module includes a standard parameter storage unit and an aging spectrum unit; The standard parameter storage unit is used to establish and store the standard X-ray scattering anisotropy parameter benchmarks of power equipment materials for substations of different models, batches and health conditions under a defect-free state, forming a standard parameter range. The aging spectrum unit is used to store characteristic spectra and correlation models of the evolution of anisotropy parameters of typical insulating materials under combined thermal, electrical, and mechanical stress aging with aging time and aging degree.

8. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron laser according to claim 7, characterized in that: The condition assessment model module includes a real-time comparison unit and a defect location unit; The real-time comparison unit is used to compare the anisotropic parameters calculated in real time by the anisotropic quantification module with the standard range in the standard parameter storage unit in real time to determine whether the current sample state deviates from the health benchmark. The defect localization unit is used to spatially locate micro-defects, stress concentration areas, and aging initiation points inside the material when an abnormal anisotropic signal is detected, by combining the azimuth distribution characteristics of the scattered signal and the scanning position information of the sample stage.

9. The quantitative X-ray scattering intensity anisotropy assessment system based on free-electron laser according to claim 7, characterized in that: The risk assessment and reporting module includes a failure probability prediction unit and an assessment report generation unit; The failure probability prediction unit is used to predict the probability of the power equipment sample under test experiencing operational failure in the future operating cycle based on the results of real-time comparison and defect location, and to classify it into safety, caution, warning and high-risk levels. The assessment report generation unit is used to automatically generate a structured assessment report containing anisotropic parameter evolution curves, defect location images, risk levels, and maintenance recommendations, and outputs it to the substation equipment management system through a data interface. At the same time, when the risk level reaches the warning level, an escalation alarm is executed.

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