Laser power comparison instrument and method thereof

Abstract

The invention relates to the technical field of laser power, in particular to a laser power comparison instrument and a method thereof, and the comparison instrument comprises a curvature calculation module, a medium model module, a power attenuation prediction module, a Markov simulation module, an environmental influence module and a stability analysis module. According to the method, the curvature and the torsion rate of the geometrical morphology of the light beam are calculated, so that the measurement precision of the laser power under different medium conditions is improved, the attenuation of the laser power can be predicted more effectively, and the reliability and the safety of laser application are greatly improved especially in the face of complex environmental factors; by simulating laser power fluctuation under differentiated environmental conditions and analyzing stability in combination with a probability model, performance fluctuation of the laser in different environments is effectively predicted, the overall working efficiency and output quality of the laser comparison instrument are optimized, and the laser comparison instrument is high in reliability. And the applicability and efficiency of the laser comparison instrument in scientific research, medical treatment and industrial application are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of laser power technology, and in particular to a laser power comparison instrument and a method thereof. Background Art

[0002] The field of laser power technology involves methods and equipment for laser generation, measurement, and control. Experts develop various tools and techniques to accurately measure the power output of lasers to ensure the safety and efficiency of lasers. This includes the use of various detectors and sensors to detect the energy density and power level of laser beams. Accurate measurement of laser power is critical to many applications such as scientific research, medical treatment, and industrial processing, because it is directly related to the performance of laser equipment and the quality of processing results. Laser power technology also includes comparators that control and adjust laser power to adapt to different operating requirements and environmental conditions.

[0003] Among them, a laser power comparator is a device used to measure and compare the output power of different laser sources. The instrument can provide accurate laser power readings and calibrate or verify the power output of laser equipment through comparison. The uses of the instrument include calibration of laser equipment in scientific research laboratories, maintenance and inspection of laser processing equipment on industrial production lines, and performance verification of laser comparators used for treatment or diagnosis in medical facilities. By using a laser power comparator, it can be ensured that the laser equipment achieves the expected effect and safety standards in actual applications.

[0004] Existing laser power technology shows obvious deficiencies in actual operation, especially in the accurate measurement and control of laser power in complex or changing environments. Existing laser power measurement technology relies on a standardized test environment and lacks adaptability to environmental changes, which leads to inaccurate power measurement in actual applications, affecting the quality and safety of laser processing. For example, when external environmental factors such as temperature and humidity change drastically, traditional measurement tools cannot accurately reflect the actual changes in laser power, resulting in the inability of laser equipment to operate at optimal performance. When processing laser power data, existing technologies lack consideration of nonlinear influencing factors, limiting the effects to special application scenarios, such as in fiber optic communications or precision machining, where nonlinear effects have a decisive influence on the results. In actual applications, the shortcomings lead to increased equipment failure rates, higher maintenance costs, and even affect the long-term stability and reliability of laser equipment. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a laser power comparison instrument and method.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, a laser power comparison instrument comprises:

[0007] The curvature calculation module calculates the curvature of the differentiated beam mode in the target medium based on the geometric shape of the laser beam, measures the torsion of the beam in the propagation direction, and generates the torsion calculation result;

[0008] The medium model module uses the torsion rate calculation result to simulate the influence of differentiated environmental factors on the laser beam by analyzing the refractive index and nonlinear effect of the target medium, and generates a medium influence analysis result;

[0009] The power attenuation prediction module uses the media impact analysis results and real-time laser power measurement data to calculate power attenuation and analyze the impact of nonlinear effects to obtain a deviation dynamic prediction analysis result;

[0010] The Markov simulation module performs Markov chain analysis based on the offset dynamic prediction analysis results, converts laser power fluctuation data into state transition data, defines discrete states of power levels, and constructs a state transition probability matrix;

[0011] The environmental impact module simulates the laser power fluctuation under differentiated environmental conditions according to the state transition probability matrix, performs multiple Monte Carlo simulations, and generates power fluctuation simulation results;

[0012] The stability analysis module analyzes the stability of the laser under differentiated environmental conditions through the power fluctuation simulation results, evaluates the state residence time and the transition probability, and obtains the stability evaluation result.

[0013] As a further solution of the present invention, the torsion calculation results include the bending degree of the laser beam in the differentiated mode and the torsion in the propagation direction, the medium impact analysis results include the refractive index of the target medium, the nonlinear effect and the influence of differentiated environmental factors on the laser beam, the offset dynamic prediction analysis results include the analysis results of the attenuation degree and nonlinear effect of the laser power, the state transition probability matrix includes the state transition representation of the laser power fluctuation data, the discrete states of the power level and the associated transition probabilities, the power fluctuation simulation results include the power fluctuation data under differentiated environmental conditions and the laser power fluctuation conditions under differentiated environments obtained through multiple Monte Carlo simulations, and the stability evaluation results include the stability analysis results of the laser under differentiated environmental conditions, the evaluation results of the laser state residence time and the state transition probability.

[0014] As a further solution of the present invention, the curvature calculation module includes:

[0015] The beam width calculation submodule identifies the beam width and divergence angle of the differentiated beam mode in the target medium based on the geometric shape of the laser beam, calculates the curvature of each mode, and obtains the beam mode curvature measurement result by combining the beam width and divergence angle data of the differentiated mode;

[0016] The torsion angle identification submodule measures the lateral offset and the twist angle of the laser beam in the propagation direction according to the beam mode curvature measurement result, records the distortion of the beam mode, makes adjustments based on the beam curvature data, and generates a torsion measurement result;

[0017] The geometry integration submodule integrates the curvature and torsion data of each beam mode through the torsion measurement result, calculates the parameters of the laser beam geometry, and obtains the torsion calculation result.

[0018] As a further solution of the present invention, the media model module includes:

[0019] The refractive index analysis submodule uses the torsion calculation result to collect the refractive index data of the target medium at the differentiated position, calculates the refractive deviation of the laser beam during propagation by measuring the refractive index of the differentiated area, and generates the refractive index change result;

[0020] The impact simulation submodule simulates the impact on the beam propagation by setting differentiated nonlinear effect intensities based on the refractive index variation results, and calculates the morphological changes of the laser beam under differentiated intensities to obtain the nonlinear effect impact results;

[0021] The environmental factor integration submodule utilizes the nonlinear effect impact results to integrate and simulate the impact of environmental factors on light beam propagation, evaluates the impact of environmental factors on the light beam, and generates media impact analysis results.

[0022] As a further solution of the present invention, the power attenuation prediction module includes:

[0023] The data processing submodule collects real-time laser power measurement data based on the media impact analysis results, performs data cleaning and formatting, eliminates measurement noise and extracts associated signals, and generates processed power data;

[0024] The attenuation calculation submodule uses the processed power data and applies a power attenuation model to calculate the attenuation value of the laser under differentiated media conditions, analyzes the power variation trend over time, and obtains a power attenuation analysis result;

[0025] The nonlinear effect evaluation submodule analyzes the influence of the nonlinear effect on the power attenuation through the power attenuation analysis result, performs nonlinear adjustment and correction, evaluates the degree of correction of the nonlinear effect on the power, and generates the deviation dynamic prediction analysis result.

[0026] As a further solution of the present invention, the Markov simulation module includes:

[0027] The data conversion submodule converts the laser power fluctuation data into state transition data based on the offset dynamic prediction analysis result, defines the conversion relationship between the differentiated states, and generates a state transition data set;

[0028] The state division submodule uses the state transition data set to define the discrete states of the laser power level, divides and marks the states, and identifies the power levels to obtain the power discrete state definition;

[0029] The matrix construction submodule uses the Markov chain method to calculate the transition probability between differentiated states through the power discrete state definition, identify and analyze the probability distribution of state transition, and generate a state transition probability matrix.

[0030] As a further solution of the present invention, the formula of the Markov chain method is as follows:

[0031]

[0032] Among them, p ij is the transition probability, n ij is the number of observed transfers, n i is the total number of transfers, α is the smoothing parameter, f ij For state s i and j The additional fitness measure between β, γ and δ are weight coefficients, g ij 、h ij and k ij Adjustment parameters for differentiating types of environmental impacts.

[0033] As a further solution of the present invention, the environmental impact module includes:

[0034] The fluctuation identification submodule models the laser power fluctuation based on the state transition probability matrix, sets differentiated environmental conditions, simulates the fluctuation of the laser power under the environmental conditions, and obtains a laser power fluctuation model;

[0035] The Monte Carlo simulation submodule adopts the laser power fluctuation model to perform multiple Monte Carlo simulations, output power fluctuation data under multiple environmental conditions, and generate a fluctuation sample set;

[0036] The simulation analysis submodule identifies the characteristics and change trends of the samples through the fluctuation sample set, summarizes the laser power fluctuation data under differentiated environmental conditions, and generates power fluctuation simulation results.

[0037] As a further solution of the present invention, the stability analysis module includes:

[0038] The stability identification submodule performs stability analysis of the laser under differentiated environmental conditions based on the power fluctuation simulation results, analyzes stability characteristics in the power fluctuation data, and obtains stability analysis results;

[0039] The time evaluation submodule uses the stability analysis results to calculate the residence time of the laser in multiple discrete states, evaluates the distribution characteristics of the residence time, and generates a state residence time distribution diagram;

[0040] The transition probability evaluation submodule evaluates the state transition probability of the laser under differentiated environmental conditions based on the state residence time distribution diagram, and generates a stability evaluation result according to the state residence time and the transition probability distribution characteristics.

[0041] A laser power comparison method is implemented based on the above-mentioned laser power comparison instrument, comprising the following steps:

[0042] S1: Collect the geometric data of the laser beam, collect the width and edge curve of the laser beam, calculate the propagation curvature and torsion of the laser beam in the target medium, and obtain the curvature and torsion calculation results;

[0043] S2: Based on the curvature and torsion calculation results, the refractive index and nonlinear effect data of the target medium are analyzed, the propagation behavior of the laser under differentiated environmental factors is simulated, and the medium influence simulation results are obtained;

[0044] S3: using the media impact simulation results and combining them with the real-time measured laser power data, calculating the attenuation of the laser power, evaluating the impact of the nonlinear effect on the power, and generating a power attenuation analysis result;

[0045] S4: Based on the power attenuation analysis result, perform Markov chain analysis, process laser power fluctuation data, analyze the state transition probability and distribution of power levels, and generate a state transition matrix;

[0046] S5: Apply the state transfer matrix to simulate the fluctuation of laser power under various environmental conditions, perform multiple Monte Carlo simulations, evaluate the stability of the laser under differentiated environmental conditions, and generate stability evaluation results.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, the measurement accuracy of laser power under different media conditions is improved by calculating the curvature and torsion based on the geometric shape of the beam. The accuracy is achieved by considering the physical changes of the laser during the propagation process, which can make more effective predictions of laser power attenuation, especially in the face of complex environmental factors. Through the comprehensive analysis of real-time power data and media influences, the power prediction is not only based on historical data, but also dynamically reflects the current operating conditions, and the real-time performance greatly improves the reliability and safety of laser applications. By simulating laser power fluctuations under differentiated environmental conditions and analyzing the stability in combination with a probability model, the performance fluctuations of the laser in different environments can be effectively predicted, and the overall working efficiency and output quality of the laser comparator can be optimized, so that the applicability and efficiency of the laser comparator in scientific research, medical and industrial applications are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of the comparison instrument of the present invention;

[0050] Figure 2 It is a schematic diagram of the framework of the comparator of the present invention;

[0051] Figure 3 is a flow chart of the curvature calculation module of the present invention;

[0052] Figure 4 is a flow chart of the media model module of the present invention;

[0053] Figure 5 It is a flow chart of the power attenuation prediction module of the present invention;

[0054] Figure 6 It is a flow chart of the Markov simulation module of the present invention;

[0055] Figure 7 It is the flow chart of the environmental impact module of the present invention;

[0056] Figure 8 is a flow chart of the stability analysis module of the present invention;

[0057] Fig. 9 It is a schematic diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0059] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0060] See also Figure 1 to Figure 2 The present invention provides a technical solution, a laser power comparison instrument comprising:

[0061] The curvature calculation module calculates the curvature of the differentiated beam mode in the target medium based on the geometric shape of the laser beam, measures the torsion of the beam in the propagation direction, and generates the torsion calculation result;

[0062] The media model module uses the torsion calculation results to simulate the impact of differentiated environmental factors on the laser beam by analyzing the refractive index and nonlinear effects of the target medium, including optical fiber, air and liquid media, and generates media impact analysis results;

[0063] The power attenuation prediction module uses the media impact analysis results and real-time laser power measurement data to calculate the power attenuation, analyze the impact of nonlinear effects, evaluate the degree of correction of nonlinear effects on power, and obtain the deviation dynamic prediction analysis results;

[0064] The Markov simulation module performs Markov chain analysis based on the results of the offset dynamic prediction analysis and the real-time measured power fluctuation data, converts the laser power fluctuation data into state transition data, defines the discrete states of the power level, and constructs the state transition probability matrix;

[0065] The environmental impact module simulates the laser power fluctuation under differentiated environmental conditions according to the state transition probability matrix, performs multiple Monte Carlo simulations, and generates power fluctuation simulation results;

[0066] The stability analysis module analyzes the stability of the laser under differentiated environmental conditions through power fluctuation simulation results, evaluates the state residence time and transition probability, and obtains the stability evaluation results.

[0067] The torsion calculation results include the bending degree of the laser beam in the differentiated mode and the torsion in the propagation direction. The media impact analysis results include the refractive index of the target medium, nonlinear effects and the influence of differentiated environmental factors on the laser beam. The offset dynamic prediction analysis results include the analysis results of the attenuation degree of laser power and nonlinear effects. The state transition probability matrix includes the state transition representation of the laser power fluctuation data, the discrete states of the power level and the associated transition probabilities. The power fluctuation simulation results include the power fluctuation data under differentiated environmental conditions and the laser power fluctuation under differentiated environments obtained through multiple Monte Carlo simulations. The stability evaluation results include the stability analysis results of the laser under differentiated environmental conditions, the evaluation results of the laser state residence time and the state transition probability.

[0068] See also Figure 2 , 3 , the curvature calculation module includes:

[0069] The beam width calculation submodule identifies the beam width and divergence angle of the differentiated beam mode in the target medium based on the geometric shape of the laser beam, calculates the curvature of each mode, and obtains the beam mode curvature measurement result by combining the beam width and divergence angle data of the differentiated mode. The execution process is as follows;

[0070] Based on the geometry of the laser beam, the beam width and divergence angle of the differentiated beam mode in the target medium are identified, and the curvature of each mode is calculated, which involves the use of optical measurement technology to accurately measure the diffusivity and curvature of the beam. By combining the beam width and divergence angle data of the differentiated mode, the beam mode curvature measurement result is obtained, using the formula:

[0071]

[0072] Among them, D bw represents the beam mode curvature measurement result, W a,i ,θ a,i and R a,i represent the beam width, divergence angle and curvature of the ith data point respectively, exp represents the natural exponential function, and n represents the total number of data points.

[0073] The torsion angle identification submodule measures the lateral offset and twist angle of the laser beam in the propagation direction according to the beam mode curvature measurement result, records the distortion of the beam mode, and makes adjustments based on the beam curvature data to generate the torsion measurement result. The execution process is as follows;

[0074] According to the beam mode curvature measurement results, the lateral offset and distortion angle of the laser beam in the propagation direction are measured, and the distortion of the beam mode is recorded. It involves accurate angle measurement to determine the degree of beam distortion, and adjusts it in combination with the beam curvature data to provide an accurate basis for further beam control and adjustment, and generate the torsion measurement results. The formula used is:

[0075]

[0076] Among them, D tor Represents the torsion measurement result, S b,i ,φ b,i and R a,i They represent the lateral offset, distortion angle and curvature of the i-th data point respectively, and n represents the total number of data points.

[0077] The geometry integration submodule integrates the curvature and torsion data of each beam mode through the torsion measurement results, calculates the parameters of the laser beam geometry, and obtains the torsion calculation results. The execution process is as follows;

[0078] Through the torsion measurement results, the curvature and torsion data of each beam mode are integrated to calculate the parameters of the laser beam geometry and obtain the torsion calculation results. The process involves using mathematical models and algorithms to integrate data to provide accurate geometric descriptions for laser control and applications, and obtain torsion calculation results using the formula:

[0079]

[0080] Among them, D geom Represents the torsion calculation result, R a,i and T c,i Represent the curvature and torsion data of the i-th data point respectively, and n represents the total number of data points.

[0081] See also Figure 2 , 4 , the media model module includes:

[0082] The refractive index analysis submodule uses the torsion calculation results to collect the refractive index data of the target medium at the differentiated position, and calculates the refractive deviation of the laser beam during propagation by measuring the refractive index of the differentiated area. The execution process of generating the refractive index change result is as follows;

[0083] The torsion calculation results are used to collect and analyze the refractive index data of each area of ​​the target medium. Through accurate measurement of the data, the deflection phenomenon of the laser beam caused by the inhomogeneity of the medium refractive index during propagation can be observed. The refractive index is quantitatively sampled and recorded. The data of each sampling point corresponds to a specific spatial position, ensuring that the refractive deviation of the laser beam under different medium conditions can be accurately calculated. By integrating the refractive deviation data, the refractive index change result is generated, and the formula used is:

[0084]

[0085] Among them, D refractive Represents the result of refractive index change, R d,i represents the refractive index of the ith data point, exp represents the natural exponential function, σR d,i represents the standard deviation of the refractive index, D d,i represents the distance from the reference point, L is the attenuation length, and n represents the total number of data points.

[0086] The impact simulation submodule simulates the impact on beam propagation by setting differentiated nonlinear effect intensities based on the refractive index change results, and calculates the morphological changes of the laser beam under differentiated intensities. The execution process of obtaining the nonlinear effect impact results is as follows;

[0087] Based on the results of the refractive index change, the intensity of different nonlinear effects is set and simulated to further explore the impact on the propagation and morphological changes of the laser beam. By adjusting the nonlinear effect parameters, such as beam self-focusing, frequency doubling generation, etc., the behavior changes of the beam when passing through media with different refractive indices are simulated. The process involves complex physical models, and it is necessary to accurately calculate how various effects change the propagation path and intensity of the beam. It not only provides theoretical simulation results, but also helps researchers optimize the design of optical comparators to adapt to specific application scenarios and obtain the results of the nonlinear effect. The formula used is:

[0088]

[0089] Among them, D impact Represents the nonlinear effect affecting the result, I f,i represents the nonlinear effect strength of the ith data point, F f,i represents the impact factor, and n represents the total number of data points.

[0090] The environmental factor integration submodule uses nonlinear effects to influence the results, integrates and simulates the impact of environmental factors on beam propagation, evaluates the degree of impact of environmental factors on the beam, and generates the execution process of media impact analysis results as follows;

[0091] Using nonlinear effects to influence the results, consider how various environmental factors, such as temperature, humidity, air pressure, etc., work together to affect the propagation of the laser beam. By comprehensively considering the factors, a more comprehensive assessment of the impact of the environment on the propagation of the laser beam can be made. It can also help develop more effective control strategies to reduce the adverse effects of environmental changes on beam propagation in precision measurement and industrial applications, and generate media impact analysis results using the formula:

[0092]

[0093] Among them, D environment Represents the results of media impact analysis, G g,i Represents the environmental factor influence of the i-th data point, varG g,i represents the coefficient of variation of environmental factors, E g,i represents the additional parameter of environmental influence, and n represents the total number of data points.

[0094] See also Figure 2 , 5 , the power attenuation prediction module includes:

[0095] The data processing submodule collects real-time laser power measurement data based on the media impact analysis results, performs data cleaning and formatting, eliminates measurement noise and extracts associated signals, and generates processed power data. The execution flow is as follows;

[0096] Based on the results of media impact analysis, the real-time laser power measurement data collected from experiments and actual operations are processed and purified. The collected data is thoroughly cleaned to eliminate data anomalies caused by equipment failure, environmental interference and external factors. Advanced signal processing techniques such as Fourier transform and filter are used to remove measurement noise to ensure data purity and accuracy. Data formatting is performed to convert the raw data into a unified format for subsequent analysis and processing, extract signals closely related to laser power, provide support for further data analysis and application, and generate processed power data using the formula:

[0097]

[0098] Among them, E data Represents the processed power data, P h,i Represents the power measurement value of the ith data point, noiseP h,i It represents the ratio of measurement noise to signal, and n represents the total number of data points.

[0099] The attenuation calculation submodule uses the processed power data, applies the power attenuation model, calculates the attenuation value of the laser under the conditions of differentiated media, analyzes the trend of power change over time, and obtains the execution process of the power attenuation analysis result as follows;

[0100] Using the processed power data, physical and mathematical models are applied to calculate the attenuation value of the laser under different media conditions. A power attenuation model based on physical principles is defined and applied. The model takes into account the optical properties of the medium such as absorption coefficient and scattering coefficient. Through the model, the trend of laser power changes over time and space is analyzed and calculated, and the impact of various environmental and operating conditions on laser transmission efficiency is explored. It not only helps to understand the behavior of lasers under specific conditions, but also predicts the performance of laser comparison instruments in different application scenarios, and obtains power attenuation analysis results. The formula used is:

[0101]

[0102] Among them, D attenuation Represents the power attenuation analysis result, P k,i represents the power of the ith data point, exp represents the natural exponential function, A k,i represents the absorption coefficient, d k,i represents the propagation distance, and n represents the total number of data points.

[0103] The nonlinear effect evaluation submodule analyzes the impact of nonlinear effect on power attenuation through power attenuation analysis results, performs nonlinear adjustment and correction, evaluates the degree of correction of nonlinear effect on power, and generates the execution process of offset dynamic prediction analysis results as follows;

[0104] Through the power attenuation analysis results, the influence of nonlinear effects such as self-phase modulation and Kerr effect on laser power attenuation is deeply analyzed. Advanced mathematical models and calculation methods are used to quantitatively adjust and correct nonlinear effects and evaluate the specific impact of the effects on laser power. Through comparative analysis of simulation and experimental data, the effectiveness of nonlinear adjustment is verified, the model is further optimized, and the offset dynamic prediction analysis results are generated. The formula used is:

[0105]

[0106] Among them, D nonlinear represents the result of dynamic prediction analysis of migration, P l,i Represents the original power, ΔP l,i represents the increased power after nonlinear correction, β l,i represents the nonlinear coefficient, and n represents the total number of data points.

[0107] See also Figure 2 , 6 , the Markov simulation module includes:

[0108] The data conversion submodule converts the laser power fluctuation data into state transition data based on the offset dynamic prediction analysis results, and defines the conversion relationship between differentiated states. The execution process of generating the state transition data set is as follows;

[0109] Based on the results of the dynamic prediction analysis of the offset, the laser power fluctuation data is converted into state transition data. This involves identifying the key change points in the laser power data, that is, the time points that indicate a significant change in the power level. The change points are regarded as potential state transition points. By detecting the change points and defining the states, the conversion relationship between the differentiated states is established. The relationship is based on the amplitude and direction of the power change. Not only does it convert continuous power readings into discrete state data, but it also builds a complete state transition framework to provide data support for subsequent analysis and decision-making, and generate a state transition data set. The formula used is:

[0110]

[0111] Among them, D data represents the state transition dataset, P m,i Represents the power change of the i-th data point, varP m,i represents the variance of the power variation, and n represents the total number of data points.

[0112] The state division submodule uses the state transition data set to define the discrete states of the laser power level, divides and marks the states, and identifies the power levels. The execution flow of the power discrete state definition is as follows;

[0113] The state transition data set is used to define the discrete states of the laser power level, and the states are divided and marked. Different power states are defined according to the statistical distribution of the power level. For example, the power range is divided into three main states: low, medium, and high. The state of each data point is marked according to the power value of the actual power data point. Data mining techniques such as cluster analysis are used to determine the boundaries of the state, ensure the scientificity and accuracy of the state division, clearly mark each power level, and obtain the definition of the power discrete state. The formula used is:

[0114]

[0115] Among them, D state Represents the power discrete state definition score, P o,i Represents the power of the i-th data point, labelP o,i Indicates the state of the data point being marked, sdP o,i represents the standard deviation of power, and n represents the total number of data points.

[0116] The matrix construction submodule uses the Markov chain method to calculate the transition probability between differentiated states through power discrete state definition, identify and analyze the probability distribution of state transition, and generate the state transition probability matrix. The execution process is as follows;

[0117] Through the definition of power discrete states, the Markov chain method is used to calculate the transition probability between different states. The statistical characteristics of state transitions, such as the frequency and conditional probability of transitioning from one state to another, are analyzed in detail. It not only reflects the transition probability between states, but also reveals the dynamic characteristics of laser power changes. By identifying and analyzing the probability distribution of state transitions, it provides a powerful tool for predicting the behavior of the laser alignment instrument and generates a state transition probability matrix.

[0118] The formula of the Markov chain method is as follows:

[0119]

[0120] Among them, p ij is the transition probability, n ij is the number of observed transfers, n i is the total number of transfers, α is the smoothing parameter, f ij For state s i and j The additional fitness measure between β, γ and δ are weight coefficients, g ij 、h ij and k ij Adjustment parameters for differentiating types of environmental impacts.

[0121] The execution flow is as follows:

[0122] Record each state s i To state s j The number of transfers n ij , introducing an additional similarity measure f ij To increase the correlation between states, calculate from each state s i The total number of transfers n i , and increase the response to different environments or contexts through g ij 、h ij and k ij , use the numerical value and weight coefficients β, γ and δ to adjust the denominator to enhance the adaptability of the model, and calculate the transition probability p through the adjusted value ij ,The method of determining the weight coefficient includes using historical data analysis or ,expert evaluation to optimize the parameters to ensure the most accurate reflection of the ,changes in actual transfer probabilities.

[0123] See also Figure 2 , 7 , the environmental impact module includes:

[0124] The fluctuation identification submodule models the laser power fluctuation based on the state transition probability matrix, sets differentiated environmental conditions, simulates the fluctuation of laser power under environmental conditions, and obtains the execution process of the laser power fluctuation model as follows;

[0125] Based on the state transition probability matrix, the fluctuation of laser power under different environmental conditions is understood and predicted, and the variation law of laser power under specific environmental factors is accurately described. Differentiation of environmental conditions, such as changes in temperature, humidity or optical density, are taken into account to simulate how laser power responds to changes in variables. By combining physical modeling and statistical analysis methods, the power fluctuation under any given environmental conditions can be predicted, which is of great significance for optimizing the design and operation of laser alignment instruments. The laser power fluctuation model is obtained, and the formula is:

[0126]

[0127] Among them, D fluct represents the laser power fluctuation model, P r,i represents the predicted power of the ith data point, exp represents the natural exponential function, and E r,i represents the environmental conditions, k r is the adjustment coefficient, C r is the environmental threshold, and n represents the total number of data points.

[0128] The Monte Carlo simulation submodule uses the laser power fluctuation model to perform multiple Monte Carlo simulations, output power fluctuation data under multiple environmental conditions, and generate the execution process of the fluctuation sample set as follows;

[0129] The laser power fluctuation model is used to perform batch random simulations. The simulation is repeated to output power fluctuation data under multiple environmental conditions. By setting different environmental parameters and running thousands or even tens of thousands of simulations, the samples cover the performance of laser power in various environments. The data is crucial for evaluating the stability and reliability of laser comparison instruments. It can help engineers and researchers understand the various situations encountered in actual applications and generate fluctuation sample sets. The formula used is:

[0130]

[0131] Among them, D carlo represents the fluctuation sample set, S s,i represents the power of the sth simulation sample, varS s,i represents the variance of the sample, n s Represents the total number of samples.

[0132] The simulation analysis submodule uses the fluctuation sample set to identify the characteristics and change trends of the samples, summarize the laser power fluctuation data under differentiated environmental conditions, and generate the power fluctuation simulation results. The execution process is as follows;

[0133] Through the fluctuation sample set, the changing trend and characteristics of laser power under different environmental conditions are identified. The analysis work includes statistical analysis, trend identification and pattern extraction, which can summarize the main characteristics of laser power fluctuation under specific environmental conditions. It can also evaluate the specific impact of different environmental factors on laser power fluctuation and generate power fluctuation simulation results. The formula used is:

[0134]

[0135] Among them, D sim Represents the power fluctuation simulation result, T t,i Represents the power fluctuation characteristics of the i-th data point, varT t,i represents the variance of the fluctuation characteristic, and n represents the total number of data points.

[0136] See also Figure 2 , 8 , the stability analysis module includes:

[0137] The stability identification submodule performs stability analysis of the laser under differentiated environmental conditions based on the power fluctuation simulation results, analyzes the stability characteristics in the power fluctuation data, and obtains the execution process of the stability analysis results as follows;

[0138] Based on the power fluctuation simulation results, the stability characteristics of the laser performance are explored in depth. Through statistical analysis methods such as standard deviation and coefficient of variation, the fluctuation amplitude in the power fluctuation data is evaluated, and the state showing smaller fluctuations is identified, which is considered to be a more stable state. At the same time, through advanced algorithms such as kurtosis and skewness analysis, the distribution characteristics of the data are further verified to determine the statistical significance of stability. Considering the impact of environmental factors such as temperature and humidity on stability, an accurate reference is provided for adjusting the laser, and the stability analysis results are obtained. The formula used is:

[0139]

[0140] Among them, D stability Represents the stability analysis results, P u,i is the power fluctuation data of the ith data point, σP u,i Represents the standard deviation of the power fluctuation data of the ith data point, μP u,i represents the average power, varP u,i represents the variance of the power data, and n represents the total number of data points.

[0141] The time evaluation submodule uses the stability analysis results to calculate the laser's residence time in multiple discrete states and evaluates the distribution characteristics of the residence time. The execution process of generating the state residence time distribution diagram is as follows;

[0142] Using the stability analysis results, analyze the laser's residence time in each discrete state and evaluate the distribution characteristics of the residence time. By collecting and analyzing the duration of different states, stable and unstable stages in laser operation can be identified. Using probabilistic statistical methods, such as probability density function and cumulative distribution function, the residence time distribution of each state is calculated to depict the time stability map of laser performance. The data is crucial for predicting the behavior pattern of the laser in long-term operation, and also helps engineers optimize the control strategy of the laser to improve stability and efficiency in various operating environments. The state residence time distribution map is generated using the formula:

[0143]

[0144] Among them, D tim Represents the state residence time distribution diagram, T v,i represents the residence time of the vth state, sdT v,i represents the standard deviation of the residence time, n v Represents the total number of states.

[0145] The transition probability evaluation submodule evaluates the state transition probability of the laser under differentiated environmental conditions based on the state residence time distribution diagram. According to the state residence time and transition probability distribution characteristics, the execution process of generating the stability evaluation result is as follows;

[0146] Based on the state dwell time distribution diagram, the state transition probability of the laser under different environmental conditions is evaluated. Based on the state dwell time distribution diagram, the probability of transitioning from one state to another is calculated by statistical analysis methods. Using the Markov chain model, the module not only calculates the transition probability between states, but also analyzes how the probability changes with environmental conditions. Through analysis, the sensitivity of laser performance to specific environmental variables can be identified, which provides a basis for further optimization of the comparator and generates stability evaluation results.

[0147] See also Fig. 9 A laser power comparison method is provided, and the laser power comparison method is performed based on the above-mentioned laser power comparison instrument, comprising the following steps:

[0148] S1: Collect the geometric data of the laser beam, collect the width and edge curve of the laser beam, calculate the propagation curvature and torsion of the laser beam in the target medium, and obtain the curvature and torsion calculation results;

[0149] S2: Based on the curvature and torsion calculation results, analyze the refractive index and nonlinear effect data of the target medium, simulate the propagation behavior of the laser under differentiated environmental factors, and obtain the medium impact simulation results;

[0150] S3: Using the media impact simulation results and the real-time measured laser power data, the attenuation of the laser power is calculated, the impact of nonlinear effects on the power is evaluated, and the power attenuation analysis results are generated;

[0151] S4: Based on the power attenuation analysis results, perform Markov chain analysis, process laser power fluctuation data, analyze the state transition probability and distribution of power levels, and generate a state transition matrix;

[0152] S5: Apply the state transfer matrix to simulate the fluctuation of laser power under various environmental conditions, perform multiple Monte Carlo simulations, evaluate the stability of the laser under differentiated environmental conditions, and generate stability evaluation results.

[0153] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A laser power comparator, characterized in that: The comparator comprises: The curvature calculation module calculates the curvature of the differentiated beam mode in the target medium based on the geometric shape of the laser beam, measures the torsion of the beam in the propagation direction, and generates the torsion calculation result; The medium model module uses the torsion rate calculation result to simulate the influence of differentiated environmental factors on the laser beam by analyzing the refractive index and nonlinear effect of the target medium, and generates a medium influence analysis result; The power attenuation prediction module uses the media impact analysis results and real-time laser power measurement data to calculate power attenuation and analyze the impact of nonlinear effects to obtain a deviation dynamic prediction analysis result; The Markov simulation module performs Markov chain analysis based on the offset dynamic prediction analysis results, converts laser power fluctuation data into state transition data, defines discrete states of power levels, and constructs a state transition probability matrix; The environmental impact module simulates the laser power fluctuation under differentiated environmental conditions according to the state transition probability matrix, performs multiple Monte Carlo simulations, and generates power fluctuation simulation results; The stability analysis module analyzes the stability of the laser under differentiated environmental conditions through the power fluctuation simulation results, evaluates the state residence time and the transition probability, and obtains the stability evaluation result.

2. The laser power comparator according to claim 1, characterized in that: The torsion calculation results include the bending degree of the laser beam in the differentiated mode and the torsion in the propagation direction, the medium impact analysis results include the refractive index of the target medium, the nonlinear effect and the impact of differentiated environmental factors on the laser beam, the offset dynamic prediction analysis results include the analysis results of the attenuation degree of laser power and the nonlinear effect, the state transition probability matrix includes the state transition representation of laser power fluctuation data, the discrete state of the power level and the associated transition probability, the power fluctuation simulation results include the power fluctuation data under differentiated environmental conditions and the laser power fluctuation under differentiated environments obtained through multiple Monte Carlo simulations, and the stability evaluation results include the stability analysis results of the laser under differentiated environmental conditions, the evaluation results of the laser state residence time and the state transition probability.

3. The laser power comparator according to claim 1, characterized in that: The curvature calculation module comprises: The beam width calculation submodule identifies the beam width and divergence angle of the differentiated beam mode in the target medium based on the geometric shape of the laser beam, calculates the curvature of each mode, and obtains the beam mode curvature measurement result by combining the beam width and divergence angle data of the differentiated mode; The torsion angle identification submodule measures the lateral offset and the twist angle of the laser beam in the propagation direction according to the beam mode curvature measurement result, records the distortion of the beam mode, makes adjustments based on the beam curvature data, and generates a torsion measurement result; The geometry integration submodule integrates the curvature and torsion data of each beam mode through the torsion measurement result, calculates the parameters of the laser beam geometry, and obtains the torsion calculation result.

4. The laser power comparator according to claim 1, characterized in that: The media model module includes: The refractive index analysis submodule uses the torsion calculation result to collect the refractive index data of the target medium at the differentiated position, calculates the refractive deviation of the laser beam during propagation by measuring the refractive index of the differentiated area, and generates the refractive index change result; The impact simulation submodule simulates the impact on the beam propagation by setting differentiated nonlinear effect intensities based on the refractive index variation results, and calculates the morphological changes of the laser beam under differentiated intensities to obtain the nonlinear effect impact results; The environmental factor integration submodule utilizes the nonlinear effect impact results to integrate and simulate the impact of environmental factors on light beam propagation, evaluates the impact of environmental factors on the light beam, and generates media impact analysis results.

5. The laser power comparator according to claim 1, characterized in that: The power attenuation prediction module comprises: The data processing submodule collects real-time laser power measurement data based on the media impact analysis results, performs data cleaning and formatting, eliminates measurement noise and extracts associated signals, and generates processed power data; The attenuation calculation submodule uses the processed power data and applies a power attenuation model to calculate the attenuation value of the laser under differentiated media conditions, analyzes the power variation trend over time, and obtains a power attenuation analysis result; The nonlinear effect evaluation submodule analyzes the influence of the nonlinear effect on the power attenuation through the power attenuation analysis result, performs nonlinear adjustment and correction, evaluates the degree of correction of the nonlinear effect on the power, and generates the deviation dynamic prediction analysis result.

6. The laser power comparator according to claim 1, characterized in that: The Markov simulation module includes: The data conversion submodule converts the laser power fluctuation data into state transition data based on the offset dynamic prediction analysis result, defines the conversion relationship between the differentiated states, and generates a state transition data set; The state division submodule uses the state transition data set to define the discrete states of the laser power level, divides and marks the states, and identifies the power levels to obtain the power discrete state definition; The matrix construction submodule uses the Markov chain method to calculate the transition probability between differentiated states through the power discrete state definition, identify and analyze the probability distribution of state transition, and generate a state transition probability matrix.

7. The laser power comparator according to claim 1, characterized in that: The formula of the Markov chain method is as follows: Among them, p ij is the transition probability, n ij is the number of observed transfers, n i is the total number of transfers, α is the smoothing parameter, f ij For state s i and j The additional fitness measure between β, γ and δ are weight coefficients, g ij 、h ij and k ij Adjustment parameters for differentiating types of environmental impacts.

8. The laser power comparator according to claim 1, characterized in that: The environmental impact module includes: The fluctuation identification submodule models the laser power fluctuation based on the state transition probability matrix, sets differentiated environmental conditions, simulates the fluctuation of the laser power under the environmental conditions, and obtains a laser power fluctuation model; The Monte Carlo simulation submodule adopts the laser power fluctuation model to perform multiple Monte Carlo simulations, output power fluctuation data under multiple environmental conditions, and generate a fluctuation sample set; The simulation analysis submodule identifies the characteristics and change trends of the samples through the fluctuation sample set, summarizes the laser power fluctuation data under differentiated environmental conditions, and generates power fluctuation simulation results.

9. The laser power comparator according to claim 1, characterized in that: The stability analysis module includes: The stability identification submodule performs stability analysis of the laser under differentiated environmental conditions based on the power fluctuation simulation results, analyzes stability characteristics in the power fluctuation data, and obtains stability analysis results; The time evaluation submodule uses the stability analysis results to calculate the residence time of the laser in multiple discrete states, evaluates the distribution characteristics of the residence time, and generates a state residence time distribution diagram; The transition probability evaluation submodule evaluates the state transition probability of the laser under differentiated environmental conditions based on the state residence time distribution diagram, and generates a stability evaluation result according to the state residence time and the transition probability distribution characteristics.

10. A laser power comparison method, characterized in that: The laser power comparison instrument according to any one of claims 1 to 9 comprises the following steps: Collecting geometric data of the laser beam, collecting the width and edge curve of the laser beam, calculating the propagation curvature and torsion of the laser beam in the target medium, and obtaining the curvature and torsion calculation results; Based on the curvature and torsion calculation results, the refractive index and nonlinear effect data of the target medium are analyzed, the propagation behavior of the laser under differentiated environmental factors is simulated, and the medium influence simulation results are obtained; Utilizing the media impact simulation results and combining them with real-time measured laser power data, the attenuation of the laser power is calculated, the influence of the nonlinear effect on the power is evaluated, and a power attenuation analysis result is generated; Based on the power attenuation analysis results, performing Markov chain analysis, processing laser power fluctuation data, analyzing the state transition probability and distribution of power levels, and generating a state transition matrix; The state transfer matrix is ​​applied to simulate the fluctuation of laser power under various environmental conditions, and multiple Monte Carlo simulations are performed to evaluate the stability of the laser under differentiated environmental conditions and generate stability evaluation results.

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