Narrowing linewidth and power stabilization system of fiber laser based on low-loss wave-locked grating

Abstract

This invention discloses a fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating, relating to the field of fiber laser technology. The system includes: a laser type matching module, an operating parameter monitoring module, a grating parameter adaptation module, and a performance stability determination module. The laser type matching module, connected to the operating parameter monitoring module and the grating parameter adaptation module, determines the corresponding target laser type and linewidth narrowing and power stabilization control task based on the stabilization control scheme selected by the operator, and sends the target laser type and control task to the operating parameter monitoring module and the grating parameter adaptation module, respectively. This invention eliminates the need for customizing wavelocked gratings and control schemes for different types of fiber lasers, allowing direct adaptation to multiple laser types, significantly reducing the costs of customized development, inventory management, and long-term maintenance.

Description

Technical Field

[0001] This invention relates to the technical field of fiber lasers, and more particularly to a fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating. Background Technology

[0002] With the continuous development of fiber laser technology, it has been widely used in many key fields such as lidar, precision spectral analysis, industrial precision processing, and fiber optic communication due to its characteristics of high brightness, narrow linewidth, and high stability. It is one of the core components in the modern optoelectronic technology system. For fiber lasers, the linewidth narrowing effect and output power stability are the core indicators that determine their application performance, and they need to be precisely controlled through key components such as low-loss wavelocked gratings.

[0003] Currently, there are many types of fiber lasers, and lasers with different gain media have significantly different requirements for gain bandwidth, output wavelength, and pump power. The core parameters of low-loss volume-locked gratings (such as period, refractive index modulation depth, and material dispersion characteristics) need to be strictly matched with the output wavelength and linewidth requirements of the laser. This means that existing technologies require custom-designed volume-locked grating structures and corresponding linewidth-power stabilization control schemes for different types of fiber lasers.

[0004] The aforementioned customized approach has several drawbacks. First, it complicates the inventory management of wave-locked gratings for fiber lasers, increases the cost of iterating dedicated control algorithms and troubleshooting, and significantly raises long-term maintenance costs. Second, different application scenarios have varying requirements for linewidth narrowing and power stability. The control logic of existing customized systems is rigid and cannot be quickly switched to adapt to the performance requirements of different scenarios, making it difficult to flexibly respond to the performance adjustment requests in actual applications. Summary of the Invention

[0005] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0006] In view of the problems existing in the prior art, the present invention is proposed.

[0007] To solve the above technical problems, the present invention provides the following technical solution: a fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating, the system comprising: a laser type matching module, an operating parameter monitoring module, a grating parameter adaptation module, and a performance stability determination module; The laser type matching module is connected to the operating parameter monitoring module and the grating parameter adaptation module. It is used to determine the corresponding target laser type and linewidth narrowing and power stabilization control task according to the stabilization control scheme selected by the operator, and send the target laser type and control task to the operating parameter monitoring module and the grating parameter adaptation module respectively. The operating parameter monitoring module is connected to the grating parameter adaptation module. It is used to collect the linewidth, power fluctuation rate, and center wavelength parameters of the laser output end according to the received target laser type and control task, generate an operating parameter sequence, and send it to the grating parameter adaptation module. The control task is a performance optimization task matching the target laser category; the grating parameter adaptation module is connected to the performance stability determination module and is used to retrieve the corresponding grating adaptation parameter library according to the control task; for each set of parameters in the running parameter sequence, it is compared with the benchmark parameter set of the same type of laser in the library to obtain the parameter deviation corresponding to each set of parameters, and then sent to the performance stability determination module. The parameter deviation is the difference between the measured parameters and the benchmark parameters in terms of performance indicators; the benchmark parameter set is a set of parameters in the grating adaptation parameter library that matches the current operating state of the laser; the performance stability determination module is used to determine the stability effect of each control node based on the parameter deviation of each set; and based on the effect of all control nodes, to generate the overall stability determination result of this control task.

[0008] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on low-loss wavelocked gratings described in this invention, the operating parameter optimization module is connected to the operating parameter monitoring module and the grating parameter adaptation module, respectively, and is used to match a corresponding adaptive noise reduction strategy for each set of parameters according to the received operating parameter sequence; the parameter sequence is processed by the noise reduction strategy to generate an optimized parameter sequence, and then sent to the grating parameter adaptation module.

[0009] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating described in this invention, the operating parameter optimization module includes a power spectrum analysis submodule and an adaptive noise reduction submodule. The power spectrum analysis submodule, connected to the operating parameter monitoring module and the adaptive noise reduction submodule, receives the operating parameter sequence and control task, analyzes the power fluctuation spectrum proportion of each set of parameters, obtains the fluctuation severity value, and sends this value along with the control task to the adaptive noise reduction submodule. The adaptive noise reduction submodule determines the filtering coefficients based on the control task; combines the filtering coefficients and the fluctuation severity value to construct an adaptive noise reduction strategy corresponding to each set of parameters; processes the operating parameter sequence through the strategy to generate an optimized parameter sequence and sends it to the grating parameter adaptation module.

[0010] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on low-loss wavelocked gratings described in this invention, the grating parameter adaptation module includes: a parameter library generation submodule and a parameter adaptation comparison submodule; the parameter library generation submodule, connected to the parameter adaptation comparison submodule, is used to input multiple sets of reference parameters for various types of lasers into the corresponding category's parameter fitting model to generate an extended reference parameter set; based on the extended reference parameter sets for all categories, a grating adaptation parameter library is constructed and sent to the parameter adaptation comparison submodule; the parameter adaptation comparison submodule, connected to the operating parameter monitoring module and the performance stability determination module respectively, is used to retrieve a specific parameter subset from the grating adaptation parameter library according to the control task; using the parameter fitting model, the operating parameter sequence is compared with the specific parameter subset to obtain the parameter deviation and sent to the performance stability determination module.

[0011] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on low-loss wavelocked gratings described in this invention, the parameter library generation submodule is further used to calculate the pairwise deviation values ​​between extended reference parameter groups and generate a deviation matrix; to filter extended reference parameter groups in the deviation matrix that exceed a preset threshold as standard input parameter groups; and to construct a grating adaptation parameter library based on the standard input parameter groups.

[0012] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on low-loss wavelocked gratings described in this invention, the grating parameter adaptation module further includes a fitting model training submodule; the fitting model training submodule is used to train an initial fitting model based on multiple sets of reference parameters for various lasers to obtain a high-precision parameter fitting model corresponding to various lasers.

[0013] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating described in this invention, the parameter adaptation and comparison submodule includes: a parameter subset retrieval unit and a parameter deviation calculation unit; the parameter subset retrieval unit, connected to the parameter library generation submodule and the parameter deviation calculation unit, is used to retrieve a specific parameter subset from the grating adaptation parameter library according to the control task and send it to the parameter deviation calculation unit; the parameter deviation calculation unit, connected to the performance stability determination module, is used to compare the running parameter sequence with the specific parameter subset using a high-precision parameter fitting model, obtain the parameter deviation amount, and send it to the performance stability determination module.

[0014] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on low-loss wavelocked grating described in this invention, the parameter adaptation and comparison submodule further includes a model optimization unit; the model optimization unit is connected to the parameter deviation calculation unit and is used to train a parameter extraction network based on a twin network architecture and using parameter samples covering all types of lasers to obtain a high-precision parameter fitting model that can output parameter deviation.

[0015] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating described in this invention, the system comprises: a control node determination unit and a task result integration unit; the control node determination unit, connected to the grating parameter adaptation module and the task result integration unit, is used to determine the stabilization effect of each control node based on the parameter deviation and a preset threshold, and send the result to the task result integration unit; the task result integration unit is used to integrate the stabilization effects of all control nodes to generate an overall stability determination result for this control task.

[0016] As a preferred embodiment of the fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating described in this invention, the performance stability determination module is further configured to generate a final overall stability determination result by combining the control response time of the laser in completing the control task. The beneficial effects of this invention include: Adaptability and cost optimization: It eliminates the need for custom-designed wavelocked gratings and control schemes for different types of fiber lasers, directly adapting to multiple laser categories and significantly reducing customized R&D, inventory management, and long-term maintenance costs. Combined with the characteristics of low-loss wavelocked gratings, it effectively narrows laser linewidth, suppresses wavelength drift, and improves the accuracy of laser output parameters and long-term operational reliability. Through parameter optimization and grating adaptation, it reduces nonlinear interference, ensuring spectral purity at high power output while extending the lifespan of the wavelocked grating. It supports rapid switching of performance indicators for different application scenarios without hardware replacement or complex debugging, efficiently responding to diverse linewidth and power stability requirements. The modular, highly integrated architecture reduces engineering deployment difficulty, and the low-power design reduces operating energy consumption, further compressing user usage and secondary development costs. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a schematic diagram of the overall system framework of the fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating proposed in this invention. Detailed Implementation

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0019] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0020] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0021] Reference Figure 1 As an embodiment of the present invention, a fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked grating is provided. This system includes: a laser type matching module, an operating parameter monitoring module, a grating parameter adaptation module, and a performance stability determination module. The laser type matching module connects the operating parameter monitoring module and the grating parameter adaptation module. It is used to determine the corresponding target laser type (e.g., ytterbium-doped Yb) based on the operator's selected stability control scheme (a pre-defined standardized scheme including laser type, linewidth narrowing target value, power stability threshold, and core parameters of the adaptation grating; for example, a scheme of "1μm band - subkHz linewidth - ±0.1% power stability" for ytterbium-doped lasers, and a scheme of "1.5μm band - 100kHz linewidth - ±0.2% power stability" for erbium-doped lasers; the parameters within the scheme are calibrated using previously measured data from multiple laser types). 3+ Erbium doping 3 + Thulium-doped Tm 3+ The laser (based on the type of laser gain medium) and the linewidth narrowing and power stability control tasks are sent to the operation parameter monitoring module and the grating parameter adaptation module, respectively. The operation parameter monitoring module, connected to the grating parameter adaptation module, is used to collect the linewidth, power fluctuation rate, and center wavelength parameters of the laser output end based on the received target laser type and control task through high-precision optical detection components, such as a linewidth meter (resolution ≤1kHz), a power meter (accuracy ±0.01%), and a wavelength meter (accuracy ±0.001nm). It generates an operation parameter sequence, which is a set of parameters continuously collected at 50ms intervals. Every 10 sets of parameters form a data unit, which includes the collection timestamp, linewidth value, power fluctuation rate value, and center wavelength value, and is sent to the grating parameter adaptation module. The control task is a performance optimization task matching the target laser type. The grating parameter adaptation module, connected to the performance stability determination module, is used to retrieve the corresponding grating adaptation parameter library according to the control task. The grating adaptation parameter library stores a set of reference parameters categorized by laser type. The library contains reference values ​​for linewidth, power fluctuation rate, and center wavelength for that laser type under different operating conditions, as well as matching low-loss wavelock grating parameters—such as grating period and refractive index modulation depth. For example, for ytterbium-doped lasers, the library stores "linewidth reference value ≤150kHz, power fluctuation rate reference value ≤0.15%, grating period..." The parameters include "500nm" and others. For each set of parameters in the operating parameter sequence, a parameter comparison algorithm (such as mean square error method or cosine similarity method) is used to compare them with the benchmark parameter set of the same type of laser in the library to obtain the parameter deviation corresponding to each set of parameters. The difference between the measured parameters and the benchmark parameters is the performance index difference. For example, the difference between the measured linewidth of 180kHz and the benchmark linewidth of 150kHz is 30kHz, and the difference between the measured power fluctuation rate of 0.2% and the benchmark power fluctuation rate of 0.15% is 0.05%. The unit of the difference is matched with the parameter type. It is used to quantify the degree of deviation between the measured performance and the benchmark performance and is sent to the performance stability judgment module. The parameter deviation is the difference between the measured parameters and the reference parameters in terms of performance indicators (such as the difference between the measured linewidth and the reference linewidth, the difference between the measured power fluctuation rate and the reference power fluctuation rate, in kHz and %, respectively). The difference is calculated using the absolute value or mean square error method, which is set according to the accuracy requirements of the control task. The reference parameter set is a set of parameters in the grating adaptation parameter library that matches the current operating state of the laser (such as pump power and ambient temperature). (It is determined by querying the "Operating State - Reference Parameter" mapping table in the library. For example, when the pump power is 50W and the ambient temperature is 25℃, the reference parameter set corresponding to the operating condition is called.) Performance stability judgment The module is used to determine the stability effect of each control node based on the deviation of each set of parameters, according to node judgment rules (e.g., deviation ≤ preset threshold is judged as "stable", deviation > preset threshold is judged as "unstable", threshold is set according to the control task accuracy, for example, linewidth deviation threshold ≤ 30kHz, power fluctuation rate deviation threshold ≤ 0.05%). Based on the effect of all control nodes, the module generates the overall stability judgment result of this control task through result integration algorithm (e.g., weighted summation method, the weight of each node is set according to its influence on the overall performance, such as linewidth node weight 0.6, power fluctuation rate node weight 0.4).

[0022] The system also includes an operating parameter optimization module (used to denoise the collected raw operating parameters, eliminate environmental interference—such as parameter fluctuations caused by vibration and temperature fluctuations, and improve the accuracy of subsequent parameter comparisons); the operating parameter optimization module is connected to the operating parameter monitoring module and the grating parameter adaptation module, respectively, and is used to match corresponding adaptive denoising strategies (such as Kalman filtering strategy for high-frequency noise, moving average filtering strategy for low-frequency noise, and the strategy parameters are dynamically adjusted according to the intensity of fluctuation) for each set of parameters based on the received operating parameter sequence and a fluctuation feature identification algorithm (analyzing the power spectrum distribution of the parameter sequence and identifying high-frequency noise components); the parameter sequence is processed through the denoising strategy to generate an optimized parameter sequence (the denoised data set, which retains the core change trend of the parameters and removes noise interference, such as eliminating the random fluctuations of ±5kHz in the original linewidth sequence, making the parameters closer to the real operating state), and sent to the grating parameter adaptation module. The operating parameter optimization module includes: a power spectrum analysis submodule (used to analyze the spectral characteristics of parameter fluctuations and determine the noise frequency range) and an adaptive noise reduction submodule (used to construct and execute noise reduction strategies based on spectral characteristics). The power spectrum analysis submodule connects the operating parameter monitoring module and the adaptive noise reduction submodule. It receives the operating parameter sequence and control tasks, analyzes the proportion of power fluctuation spectrum for each set of parameters using Fast Fourier Transform (FFT), and obtains a fluctuation severity value (quantifying the strength of parameter fluctuations; for example, if the proportion of high-frequency components in the spectrum is >30%, it is judged as "severe fluctuation," and if the proportion is ≤10%, it is judged as "smooth fluctuation," represented by a value from 0 to 10, with larger values ​​indicating more severe fluctuations). This value is then compared with... The control task is sent to the adaptive noise reduction submodule. This submodule determines the filtering coefficients based on the control task's accuracy requirements (e.g., a filtering coefficient of 0.8 for high-precision tasks—strong filtering effect; a filtering coefficient of 0.5 for regular tasks—balancing filtering and response speed). Combining the filtering coefficients with the fluctuation severity value, it constructs an adaptive noise reduction strategy for each set of parameters (e.g., when the fluctuation severity value is 8 and the filtering coefficient is 0.8, a combination of "Kalman filtering + moving average filtering" is used; when the fluctuation severity value is 3 and the filtering coefficient is 0.5, a single moving average filtering strategy is used). The strategy processes the running parameter sequence, generates an optimized parameter sequence, and sends it to the grating parameter adaptation module.

[0023] Specifically, the grating parameter adaptation module includes: a parameter library generation submodule (used to build and update the grating adaptation parameter library, ensuring the integrity and accuracy of the parameters in the library) and a parameter adaptation comparison submodule (used to perform comparison between measured parameters and reference parameters, and output the deviation); the parameter library generation submodule is connected to the parameter adaptation comparison submodule, used to input multiple sets of reference parameters of various lasers into the corresponding category's parameter fitting model (based on measured parameter samples covering different operating states of the laser category—such as linewidth and power fluctuation data at different pump powers and ambient temperatures—trained model, using least squares multivariate fitting or Siamese network parameter mapping algorithm, can realize dynamic expansion of reference parameters, for example, after training with 1000 sets of measured data, the model can generate derived reference parameters under unmeasured operating conditions), generating extended reference parameter sets (in the original Based on the initial reference parameters, derivative parameters for different operating conditions are added, such as the linewidth threshold and allowable power fluctuation range corresponding to pump power of 50W / 100W / 150W, expanding the operating condition coverage of the parameter library; based on the extended reference parameter groups of all categories, a grating adaptation parameter library is constructed and sent to the parameter adaptation comparison submodule; the parameter adaptation comparison submodule is connected to the operation parameter monitoring module and the performance stability judgment module respectively, and is used to retrieve a specific parameter subset from the grating adaptation parameter library according to the control task (selecting reference parameters that match the accuracy requirements of the current control task from the library, such as retrieving a parameter subset with a linewidth reference value ≤100kHz corresponding to the "sub-kHz linewidth control task", excluding low-precision reference parameters); using the parameter fitting model, the operation parameter sequence is compared with the specific parameter subset to obtain the parameter deviation and send it to the performance stability judgment module.

[0024] The parameter library generation submodule is also used to calculate the pairwise deviation values ​​between extended reference parameter groups using distance calculation algorithms (such as Euclidean distance and Manhattan distance), generate a deviation matrix (with the extended reference parameter groups as rows and columns, and the matrix elements as the deviation values ​​between the two sets of parameters, used to quantify the degree of difference between parameter groups); filter extended reference parameter groups in the deviation matrix that exceed a preset threshold (set according to parameter accuracy requirements, such as a linewidth deviation threshold of 50kHz and a power volatility deviation threshold of 0.2%) as standard input parameter groups (ensuring the uniqueness and representativeness of the input parameters and avoiding parameter redundancy, such as filtering parameter groups with deviations > 50kHz and excluding duplicate or similar parameter groups); and construct a grating adaptation parameter library based on the standard input parameter groups.

[0025] The grating parameter adaptation module also includes a fitting model training submodule (used to train and optimize the parameter fitting model to improve the parameter expansion accuracy of the model); the fitting model training submodule is used to train the initial fitting model (such as the initial least squares model, the initial twin network model) based on multiple sets of reference parameters of various lasers (each set of parameters includes operating status parameters - pump power, ambient temperature, and performance parameters - linewidth, power fluctuation rate, center wavelength) through model training algorithms (such as gradient descent method, backpropagation algorithm) to obtain high-precision parameter fitting models corresponding to various lasers (model error ≤5%, which can accurately generate extended reference parameters under different operating conditions, such as input pump power 60W, the model outputs the corresponding linewidth reference value and power fluctuation rate reference value, with a deviation of ≤5% from the measured value).

[0026] The parameter adaptation and comparison submodule includes: a parameter subset retrieval unit (used to select reference parameters from the parameter library that match the control task) and a parameter deviation calculation unit (used to calculate the deviation between the measured parameters and the reference parameters); the parameter subset retrieval unit, connected to the parameter library generation submodule and the parameter deviation calculation unit, is used to retrieve a specific parameter subset from the grating adaptation parameter library according to the control task and send it to the parameter deviation calculation unit; the parameter deviation calculation unit, connected to the performance stability determination module, is used to fit a model using high-precision parameters and calculate the deviation using the deviation calculation formula (e.g., deviation = |measured parameter value - reference parameter value| / reference parameter value × 100%, or deviation = √[(measured parameter value - reference parameter value)]). 2 The system compares the sequence of running parameters with a subset of dedicated parameters to obtain the parameter deviation and sends it to the performance stability determination module.

[0027] The parameter adaptation and comparison submodule also includes a model optimization unit (used to continuously optimize the parameter fitting model to adapt to long-term changes in laser performance); the model optimization unit, connected to the parameter deviation calculation unit, is used to train the parameter extraction network (used to extract feature information of parameters, such as the frequency distribution characteristics of linewidth and the fluctuation characteristics of power) based on a Siamese network architecture (composed of two feature extraction networks with the same structure and shared parameters, which can efficiently learn the mapping relationship between parameters) using parameter samples covering all types of lasers (including measured parameters of each type of laser under different life cycles and different operating conditions, with a sample size of ≥10,000 sets to ensure the generalization ability of the model) to obtain a high-precision parameter fitting model that can output parameter deviation.

[0028] In one embodiment, the performance stability determination module includes: a control node determination unit (used to determine the stable state of a single control node) and a task result integration unit (used to integrate the results of all nodes and generate an overall determination result); the control node determination unit, connected to the grating parameter adaptation module and the task result integration unit, is used to determine the stability effect of each control node based on the parameter deviation and a preset threshold (set according to the control task type, such as threshold ≤20kHz for precision measurement scenarios and threshold ≤50kHz for industrial processing scenarios), through determination logic (such as "if all parameter deviations ≤ the threshold, the node is stable; if any parameter deviation > the threshold, the node is unstable"), and send it to the task result integration unit; the task result integration unit is used to determine the stability effect of each control node through the result integration unit. The system integrates the stability effects of all control nodes according to the integration rules (such as "if the proportion of stable nodes is ≥90%, the overall result is 'qualified'; if the proportion of stable nodes is <90%, the overall result is 'unqualified'" or "if the weighted sum score is ≥80, the result is 'qualified'") to generate the overall stability judgment result for this control task. The performance stability judgment module is also used to combine the control response time of the laser to complete the control task (the total time from parameter acquisition to output judgment result, such as ≤500ms is "fast response" and >500ms is "response delay") and generate the final overall stability judgment result through the time weighting algorithm (such as adding 10 points to the overall result if the response time is ≤500ms and subtracting 10 points if it is >500ms, with a maximum score of 100 points).

[0029] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A fiber laser linewidth narrowing and power stabilization system based on a low-loss wavelocked bulk grating, characterized in that, The system includes: a laser type matching module, an operating parameter monitoring module, a grating parameter adaptation module, and a performance stability determination module; The laser type matching module is connected to the operating parameter monitoring module and the grating parameter adaptation module. It is used to determine the corresponding target laser type and linewidth narrowing and power stabilization control task according to the stabilization control scheme selected by the operator, and send the target laser type and control task to the operating parameter monitoring module and the grating parameter adaptation module respectively. The operating parameter monitoring module is connected to the grating parameter adaptation module. It is used to collect the linewidth, power fluctuation rate, and center wavelength parameters of the laser output end according to the received target laser type and control task, generate an operating parameter sequence, and send it to the grating parameter adaptation module. The control task is a performance optimization task matching the target laser category; the grating parameter adaptation module is connected to the performance stability determination module and is used to retrieve the corresponding grating adaptation parameter library according to the control task; for each set of parameters in the running parameter sequence, it is compared with the benchmark parameter set of the same type of laser in the library to obtain the parameter deviation corresponding to each set of parameters, and then sent to the performance stability determination module. The parameter deviation is the difference between the measured parameters and the benchmark parameters in terms of performance indicators; the benchmark parameter set is a set of parameters in the grating adaptation parameter library that matches the current operating state of the laser; the performance stability determination module is used to determine the stability effect of each control node based on the parameter deviation of each set; and based on the effect of all control nodes, to generate the overall stability determination result of this control task.

2. The system according to claim 1, characterized in that, The system further includes an operating parameter optimization module; the operating parameter optimization module is connected to the operating parameter monitoring module and the grating parameter adaptation module respectively, and is used to match a corresponding adaptive noise reduction strategy for each set of parameters according to the received operating parameter sequence; the parameter sequence is processed by the noise reduction strategy to generate an optimized parameter sequence, and then sent to the grating parameter adaptation module.

3. The system according to claim 2, characterized in that, The operating parameter optimization module includes a power spectrum analysis submodule and an adaptive noise reduction submodule. The power spectrum analysis submodule, connected to the operating parameter monitoring module and the adaptive noise reduction submodule, receives the operating parameter sequence and control task, analyzes the power fluctuation spectrum proportion of each group of parameters, obtains the fluctuation severity value, and sends this value along with the control task to the adaptive noise reduction submodule. The adaptive noise reduction submodule determines the filtering coefficients based on the control task; combines the filtering coefficients with the fluctuation severity value to construct an adaptive noise reduction strategy corresponding to each group of parameters; processes the operating parameter sequence using the strategy to generate an optimized parameter sequence and sends it to the grating parameter adaptation module.

4. The system according to claim 1, characterized in that, The grating parameter adaptation module includes a parameter library generation submodule and a parameter adaptation comparison submodule. The parameter library generation submodule, connected to the parameter adaptation comparison submodule, is used to input multiple sets of reference parameters for various lasers into the corresponding category's parameter fitting model to generate an extended reference parameter set. Based on the extended reference parameter sets for all categories, a grating adaptation parameter library is constructed and sent to the parameter adaptation comparison submodule. The parameter adaptation comparison submodule, connected to the operating parameter monitoring module and the performance stability determination module, is used to retrieve a specific parameter subset from the grating adaptation parameter library according to the control task. Using the parameter fitting model, the operating parameter sequence is compared with the specific parameter subset to obtain the parameter deviation, which is then sent to the performance stability determination module.

5. The system according to claim 4, characterized in that, The parameter library generation submodule is also used to calculate the pairwise deviation values ​​between extended reference parameter groups and generate a deviation matrix; to filter extended reference parameter groups in the deviation matrix that exceed a preset threshold as standard input parameter groups; and to construct a grating adaptation parameter library based on the standard input parameter groups.

6. The system according to claim 4, characterized in that, The grating parameter adaptation module also includes a fitting model training submodule; the fitting model training submodule is used to train an initial fitting model based on multiple sets of benchmark parameters of various lasers to obtain a high-precision parameter fitting model corresponding to various lasers.

7. The system according to claim 4, characterized in that, The parameter adaptation and comparison submodule includes a parameter subset retrieval unit and a parameter deviation calculation unit. The parameter subset retrieval unit is connected to the parameter library generation submodule and the parameter deviation calculation unit, and is used to retrieve a specific parameter subset from the grating adaptation parameter library according to the control task and send it to the parameter deviation calculation unit. The parameter deviation calculation unit is connected to the performance stability determination module, and is used to compare the running parameter sequence with the specific parameter subset using a high-precision parameter fitting model to obtain the parameter deviation and send it to the performance stability determination module.

8. The system according to claim 7, characterized in that, The parameter adaptation and comparison submodule also includes a model optimization unit; the model optimization unit is connected to the parameter deviation calculation unit and is used to train the parameter extraction network based on the twin network architecture and using parameter samples covering all types of lasers to obtain a high-precision parameter fitting model that can output parameter deviation.

9. The system according to claim 1, characterized in that, The performance stability determination module includes: a control node determination unit and a task result integration unit; the control node determination unit is connected to the grating parameter adaptation module and the task result integration unit, and is used to determine the stability effect of each control node according to the parameter deviation and preset threshold, and send it to the task result integration unit; the task result integration unit is used to integrate the stability effects of all control nodes and generate the overall stability determination result of this control task.

10. The system according to any one of claims 1-9, characterized in that, The performance stability determination module is also used to combine the control response time of the laser to complete the control task to generate the final overall stability determination result.

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