Power feedback control method of solid pulse laser

Abstract

The invention provides a power feedback control method of a solid pulse laser, which comprises the following steps of: predicting the optimal working temperature of a crystal of the solid pulse laser according to the environment temperature by using a pre-trained interpolator, and providing a first predicted value to reduce the search range of the optimal working temperature of the crystal; and performing local search by taking the first predicted value as a baseline, and further determining an observation value (second predicted value) of the optimal working temperature of the crystal by performing local temperature scanning around the first predicted value. And the local error is compensated by combining the prior information (the first predicted value) and the real-time measurement data (the second predicted value), so that the prediction precision is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of solid-state pulsed lasers, and more specifically to a power feedback control method for solid-state pulsed lasers. Background Technology

[0002] When a solid-state pulsed laser operates at a high repetition rate and high pump power, changes in ambient temperature can affect the performance of the gain medium crystal or frequency doubling crystal, resulting in a decrease in the output power of the laser and severely impacting the application of pulsed lasers.

[0003] The relationship between the conversion efficiency of a crystal and temperature exhibits a parabolic characteristic, with the vertex of the parabola representing the crystal's optimal operating temperature. However, this vertex varies with ambient temperature, meaning the optimal operating temperature of the crystal changes with the ambient temperature. Currently, the industry commonly uses the crystal temperature scanning method to determine the optimal operating temperature of a crystal. This involves adjusting the crystal temperature in increments while simultaneously measuring the output power of the solid-state pulsed laser. The scanning temperature with the highest output power is selected as the optimal operating temperature, and then the crystal temperature is adjusted to reach this optimal temperature. However, this method is time-consuming, inefficient, and limited by the step size of the crystal temperature scan, resulting in low accuracy in determining the optimal operating temperature. Consequently, this approach does not effectively improve the performance of solid-state pulsed lasers. Summary of the Invention

[0004] One or more embodiments of this application describe a power feedback control method for a solid-state pulsed laser, which can at least partially overcome the above-mentioned technical problems.

[0005] One or more embodiments of this application provide a power feedback control method for a solid-state pulsed laser, the method comprising: Obtain the ambient temperature of the solid-state pulsed laser; The optimal operating temperature of the crystal is predicted based on the ambient temperature using a pre-trained interpolator, resulting in a first predicted value. A localized temperature scan of the crystal is performed around the first predicted value, and a second predicted value of the optimal operating temperature of the crystal is determined based on the change in the output power of the solid-state pulsed laser with the scan temperature. A prior distribution is constructed based on the first predicted value, and a likelihood function is constructed based on the second predicted value. The posterior distribution of the optimal operating temperature of the crystal is calculated to obtain a third predicted value of the optimal operating temperature of the crystal. An observation space model of the interpolator's predicted values ​​is constructed, the parameters of the observation space model are adjusted using the second predicted values, and the state estimate is updated by extended Kalman filtering to obtain the fourth predicted value. Calculate the error between the fourth predicted value and the second predicted value, and use the error to correct the third predicted value to obtain the optimal operating temperature of the crystal; Adjust the crystal temperature to the optimal operating temperature.

[0006] As an optional implementation of the above method, the training method of the interpolator includes: Based on multiple preset ambient temperatures, the crystal temperature of the solid-state pulsed laser is scanned at each ambient temperature. The crystal temperature is adjusted to the scanning temperature, and the output power of the solid-state pulsed laser is collected. The scanning temperature with the highest output power is taken as the optimal crystal temperature. The interpolator is trained using the ambient temperature and the corresponding optimal crystal temperature as training samples.

[0007] As an optional implementation of the above method, a localized crystal temperature scan is performed around the first predicted value, and a second predicted value for the optimal operating temperature of the crystal is determined based on the change in the output power of the solid-state pulsed laser with the scanned temperature. Specifically, this includes: The output power of the solid-state pulsed laser was collected at different scanning temperatures of the crystal, and a power curve showing the change of output power with the temperature of the crystal was fitted. Based on the power curve, the maximum likelihood estimate of the optimal operating temperature of the crystal is calculated to obtain the second predicted value.

[0008] As an optional implementation of the above method, adjusting the parameters of the observation space model using the second predicted value specifically includes: The observation noise covariance of the observation space model is adjusted using the second predicted value.

[0009] Specifically, adjusting the parameters of the observation space model using the second predicted value further includes: The process noise covariance matrix of the observation space model is adjusted using the second predicted value.

[0010] As an optional implementation of the above method, the error between the fourth predicted value and the second predicted value is calculated, and the third predicted value is corrected using the error to obtain the optimal operating temperature of the crystal, specifically including: The long-term bias is obtained by updating using an exponentially weighted moving average: ; in, This represents the error between the fourth predicted value and the second predicted value. Indicates the forgetting factor, This indicates the correction deviation from the previous correction. This indicates the current correction deviation. The initial value is , The third predicted value is corrected using the long-term deviation.

[0011] As an optional implementation of the above method, the method further includes: The laser pulse signal output by the solid-state pulse laser is converted into an electrical pulse signal by the laser power detection module, and the output power of the solid-state pulse laser is determined based on the electrical pulse signal.

[0012] Specifically, the laser power detection module is a transimpedance amplifier circuit.

[0013] Furthermore, the method also includes: The peak voltage hold module performs voltage peak hold processing on the electrical pulse signal output by the transimpedance amplifier circuit.

[0014] Furthermore, the method also includes: The voltage value output by the peak voltage holding module is acquired, and the output power of the solid-state pulsed laser is calculated based on the functional relationship between the voltage value and the output power of the solid-state pulsed laser.

[0015] Beneficial Effects: One or more embodiments of this application provide a power feedback control method for a solid-state pulsed laser. This method utilizes a pre-trained interpolator to predict the optimal operating temperature of the solid-state pulsed laser crystal based on the ambient temperature, providing a first predicted value to narrow the search range for the optimal operating temperature of the crystal. Then, a local search is performed with the first predicted value as a baseline, and the observed value (second predicted value) of the optimal operating temperature of the crystal is further determined by performing a local temperature scan around the first predicted value. Finally, prior information (the first predicted value) and real-time measurement data (the second predicted value) are combined to compensate for local errors, thereby significantly improving prediction accuracy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of a power feedback control method for a solid-state pulsed laser, which is involved in one or more embodiments of this application.

[0018] Figure 2This is a schematic diagram illustrating the relationship between crystal conversion efficiency and temperature in one or more embodiments of this application.

[0019] Figure 3 This is a schematic diagram of the power feedback control system of a solid-state pulsed laser according to one or more embodiments of this application.

[0020] Figure 4 This is a schematic diagram of the transimpedance amplifier circuit and peak voltage holding circuit involved in one or more embodiments of this application.

[0021] Figure 5 This is a schematic diagram of the peak voltage waveform involved in one or more embodiments of this application.

[0022] In the diagram: 1. Laser diode, 2. Coupler tube, 3. High-reflection mirror, 4. Gain medium, 5. Q switch, 6. Partial mirror, 7. Frequency doubling crystal, 8. High-reflection mirror. Detailed Implementation

[0023] First, it should be noted that the terminology used in the embodiments of this invention is for the purpose of describing specific embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0024] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0025] It should be noted that the steps of the corresponding methods in other embodiments are not necessarily performed in the order shown and described in this application. In some other embodiments, the methods may include more or fewer steps than those described in this application. Furthermore, a single step described in this application may be broken down into multiple steps in other embodiments; and multiple steps described in this application may be combined into a single step in other embodiments.

[0026] The power feedback control method for solid-state pulsed lasers described in this application will be further described in detail below with reference to the accompanying drawings and specific embodiments. However, this detailed description does not constitute a limitation on the embodiments of this application.

[0027] Please refer to Figure 1 , Figure 1 A schematic flowchart illustrating a power feedback control method for a solid-state pulsed laser is shown. Figure 1 As shown, the method includes steps S100 to S112.

[0028] S100: Obtain the ambient temperature of the solid-state pulsed laser.

[0029] S102: Using a pre-trained interpolator, the optimal operating temperature of the crystal is predicted based on the ambient temperature to obtain the first predicted value.

[0030] Before performing this step S102, the interpolator needs to be trained so that it can predict the optimal operating temperature of the crystal based on the ambient temperature.

[0031] In some implementations, the interpolator can be trained using the following methods, and the training process of the interpolator will be described in detail below.

[0032] like Figure 2 As shown, the relationship between the crystal's conversion efficiency and its temperature generally exhibits a parabolic relationship. Based on this characteristic, smooth spline interpolators, piecewise linear interpolators, etc., can be used as the aforementioned interpolators. In this embodiment, only the smooth spline interpolator is used as an example for illustration. However, it should be noted that this embodiment does not limit the selection of interpolators, and other suitable interpolators are also applicable to the method described in this embodiment.

[0033] The specific steps for training the interpolator include: S1020: Obtain training samples.

[0034] Based on multiple preset ambient temperatures, the crystal temperature of the solid-state pulsed laser is scanned at each ambient temperature. The crystal temperature is adjusted to the scanning temperature, and the output power of the solid-state pulsed laser is collected. The scanning temperature with the highest output power is taken as the optimal crystal temperature. Ambient temperature and the corresponding optimal crystal temperature As training samples, the training sample set is obtained. ,in, Indicates the ambient temperature sampling point. Indicates the ambient temperature sampling point Ambient temperature, Indicates ambient temperature The optimal crystal temperature was obtained by crystal temperature scanning.

[0035] S1022: Construct the objective function.

[0036] The objective function is constructed as follows: ; in, Describe the objective function. The spline function represents the smooth spline interpolator. This represents the total number of environmental temperature sampling points, which is also the total number of training samples. Indicates the first The weight coefficients of each training sample. , , This is the smoothing parameter (regularization coefficient). , Indicates the ambient temperature domain. , , It represents the second derivative of a spline function and is used to measure the curvature of the function. Indicates the first The measurement variance of each training sample is obtained by fitting a power curve. Indicates the first Number of temperature points in a temperature scan Indicates the first The first temperature scan Measurement power at each scanned temperature point In the fitted output power curve, the first... The first temperature scan Output power corresponding to each scanned temperature point.

[0037] S1024: Training the smooth spline interpolator.

[0038] The spline function is represented as: ; in, Describes the natural cubic spline basis functions, each At the node The value is 1 at one node and 0 at other nodes. Let be the spline coefficients to be determined. The basis functions are piecewise cubic polynomials, which are twice continuously differentiable at the nodes.

[0039] The objective function described above can be transformed into the following form: ; in, , yes The basis function matrix, elements , , , Represents the penalty matrix, elements .

[0040] Solving for the optimal coefficients : right Taking the derivative and setting it to zero, we get: ; Summarized as follows: ; Solving the system of linear equations yields the optimal coefficients: ; Calculate smoothing parameters : Use generalized cross-validation (GCV) to select the optimal one. : ; in, It is a smooth matrix. These are elements in the smoothing matrix. Solve smallest That is, the optimal one. .

[0041] Sure Then, the spline function is obtained: .

[0042] S1026: Predicts the optimal operating temperature of the crystal.

[0043] The ambient temperature collected in real time is The first predicted value for the optimal crystal temperature is: ; Calculate the prediction variance: ; in, Represents the residual variance. Represents the trace of a matrix.

[0044] S104: Perform a localized crystal temperature scan around the first predicted value, and determine a second predicted value for the optimal operating temperature of the crystal based on the change in the output power of the solid-state pulsed laser with the scan temperature.

[0045] In step S102, the interpolator provides a global smooth prediction, which is the first prediction value, thereby narrowing the search range for the optimal operating temperature of the crystal.

[0046] In this step S102, the first predicted value is used. Construct local scan range for baseline , The scanning radius is defined as follows: Crystal temperature scanning is performed within this local scanning range, the crystal temperature is adjusted to the scanning temperature, and the output power of the solid-state pulsed laser is measured.

[0047] Considering that the output power of the solid-state pulsed laser changes with scanning temperature in a parabolic manner during local scanning, a second-order function is used to fit the power curve of the solid-state pulsed laser as a function of scanning temperature: ; Indicates the crystal temperature. Indicates the scanning temperature is The output power of the solid-state pulsed laser, , , This represents the fitting coefficient.

[0048] The second predicted value of the optimal crystal temperature is obtained through maximum likelihood estimation: .

[0049] Calculate the estimated variance: , This indicates the total number of scan points in the local temperature scan.

[0050] S106: Construct a prior distribution based on the first predicted value, construct a likelihood function based on the second predicted value, calculate the posterior distribution of the optimal operating temperature of the crystal, and obtain the third predicted value of the optimal operating temperature of the crystal.

[0051] In this step, the first and second predicted values ​​are fused using Bayesian methods. The specific steps are as follows: Based on the first predicted value of the smooth spline interpolator and prediction variance Construct a prior distribution as a priori: ; in, This represents the prior variance.

[0052] Using the second predicted value obtained from the local temperature scan as the likelihood value, a likelihood function is constructed: ; in, This is the actual optimal operating temperature for crystals.

[0053] Calculate the posterior distribution based on the prior distribution and the likelihood function: ; This formula indicates that the optimal operating temperature of the crystal can be represented by a posterior mean. The posterior variance is It is described by a normal distribution. The posterior mean is This is the third predicted value mentioned above.

[0054] S108: Construct an observation space model for the optimal operating temperature of the crystal, adjust the parameters of the observation space model using the second predicted value, and then update the state estimate through extended Kalman filtering to obtain the fourth predicted value.

[0055] The optimal operating temperature predicted by the interpolator may be subject to errors caused by various factors, such as scanning process errors (measurement errors caused by thermal hysteresis during temperature scanning, errors caused by scanning step size limitations), power curve fitting errors, random measurement noise, etc. This embodiment uses system bias. This is used to characterize the aforementioned error.

[0056] Constructing state variables: ; in, Indicates the first The actual optimal crystal temperature during the first run. This represents the system deviation, with an initial value of 0. This represents the temperature-sensitive correction factor, initially assuming the interpolator is correct. .

[0057] The state equation is: ; in, Represents the state transition matrix. , This represents the persistence parameter of the deviation, with a value range of 0.9 to 0.99, and is used to describe the correlation between the current system deviation and the system deviation at the previous time. Represents the process noise vector. It follows a multivariate normal distribution (Gaussian distribution). , This represents the process noise covariance matrix. The expression is: ; , , All are noise terms, initially, The value typically ranges from 0.0001 to 0.001. The value typically ranges from 0.0001 to 0.002. The value of is usually between 0.00001 and 0.0001.

[0058] The observation equation is: ; Indicates observation noise. , Represents the observation noise covariance, initially... , The calibration error variance is a constant. For observation functions.

[0059] In the observation space model, a second predicted value is introduced as a reference to dynamically adjust the model parameters, so that the observation space model can approximate the actual changes in the optimal operating temperature of the crystal.

[0060] Based on this principle, we perform extended Kalman updates: (1) Prediction step Perform state prediction: ,in, This represents the current prior prediction value. This represents the previous posterior estimate.

[0061] Perform covariance prediction: ,in, This represents the current prior covariance. This represents the posterior covariance of the previous iteration.

[0062] (2) Obtaining observation data ; in, This represents the minimum observation noise and is a constant. Represents the sum of squared residuals. This represents the total sum of squares.

[0063] ; in, Indicates the first local temperature scan The scanning temperature of each scanning point When the crystal temperature is The output power of the solid-state pulsed laser measured at that time. The crystal temperature calculated using the power function is: Output power at that time This represents the average output power of the solid-state pulsed laser acquired during a local temperature scan.

[0064] (3) Calculate the observation function Jacobian matrix ;

[0065] (4) Calculate the Kalman gain ;

[0066] (5) Status update Calculate the new information: ;

[0067] Right now, ;

[0068] Status Update: ;

[0069] Expanding, we get: ;

[0070] Thus, the fourth predicted value mentioned above is obtained. .

[0071] In some implementations, if the prediction error is large in the prediction step of step (1) above, the process noise covariance matrix can also be adjusted. Update: ;

[0072] in, The error threshold is a constant (e.g., 0.5℃).

[0073] S110: Calculate the error between the fourth predicted value and the second predicted value, use the error to correct the third predicted value, and obtain the optimal operating temperature of the crystal.

[0074] Calculate the error between the fourth predicted value and the second predicted value. : ;

[0075] The long-term bias is obtained by updating using an exponentially weighted moving average: ;

[0076] in, This indicates the error between the fourth predicted value and the second predicted value. Indicates the forgetting factor, This indicates the correction deviation from the previous correction. This indicates the current correction deviation. The initial value is , .

[0077] The third predicted value was corrected using long-term bias, and the optimal operating temperature after correction is: .

[0078] S112: Adjust the crystal temperature to the optimal operating temperature.

[0079] The above describes a power feedback control method for a solid-state pulsed laser provided in this application. This method utilizes a pre-trained interpolator to predict the optimal operating temperature of the solid-state pulsed laser crystal based on the ambient temperature, providing a first predicted value to narrow the search range for the optimal operating temperature of the crystal. Then, a local search is performed using the first predicted value as a baseline, and the observed value (second predicted value) of the optimal operating temperature of the crystal is further determined by performing a local temperature scan around the first predicted value. Finally, prior information (the first predicted value) and real-time measurement data (the second predicted value) are combined to compensate for local errors, thereby significantly improving prediction accuracy.

[0080] Please refer to Figure 3 , Figure 3 The diagram shows a schematic of the power feedback control system of a solid-state pulsed laser used in a specific scenario when the power feedback control method of the above-mentioned solid-state pulsed laser is implemented.

[0081] like Figure 3 As shown, a solid-state pulsed laser typically includes a laser diode (LD) 1, a coupling tube 2, a high-reflection mirror 3, a gain medium 4, a Q switch 5, a partial reflector 6, a frequency doubling crystal 7, and a high-reflection mirror 8.

[0082] This embodiment adds a laser power detection module, a control module, and a crystal temperature control module to the external solid-state pulsed laser. The laser power detection module converts the laser pulse signal output by the solid-state pulsed laser into an electrical pulse signal. Since the voltage value of the electrical pulse signal and the output power of the solid-state pulsed laser typically exhibit a monotonically increasing functional relationship, the output power of the solid-state pulsed laser can be determined based on the electrical pulse signal. This function can be obtained through experimental fitting.

[0083] In some implementations, the laser power detection module described above can be implemented using a transimpedance amplifier circuit, which converts the laser pulse into an electrical pulse, such as... Figure 4 The image shows the waveform of the electrical pulse signal.

[0084] Because the electrical pulse signal output by the transimpedance amplifier circuit is unstable, directly acquiring its voltage peak value places high demands on subsequent acquisition equipment. Therefore, in some implementations, a peak voltage holding circuit can be connected after the transimpedance amplifier circuit to convert the nanosecond-level optical pulses output by the transimpedance amplifier circuit into a wide pulse or near-DC electrical signal. This design can reduce the requirements on the subsequent peak voltage acquisition circuit and maintain the accuracy of the acquired peak voltage.

[0085] Figure 5 The diagram shows the circuit structure of the transimpedance amplifier circuit and the continuous peak voltage acquisition circuit. Figure 5 In this circuit, D1 is a photodiode (selected based on the laser wavelength for sensitivity and linearity). D1, U1A, R1, C1, R2, and C2 form a transimpedance amplifier circuit, converting the optical pulse signal into an electrical pulse signal, such as... Figure 4 The pulse signal waveform in the image; Figure 5 In this circuit, U1B, R3, R4, C3, R5, and C4 form an inverting low-pass amplifier circuit to further filter and amplify the aforementioned pulse signal. Figure 5 In the circuit, U2A, U2B, and their related resistors, capacitors, and diodes, utilizing the unidirectional conductivity of diodes (D1, D3) and the non-sudden voltage drop of capacitor (C5), constitute the circuit for the peak voltage holding section.

[0086] The control module is used to calculate the output power of the solid-state pulsed laser based on the collected peak voltage, as well as to acquire ambient temperature data and crystal temperature data. Then, it uses the above-mentioned solid-state laser pulse power feedback control method to calculate the optimal operating temperature of the crystal (including gain medium 4 and frequency doubling crystal 7). Based on the optimal operating temperature, it generates control commands and controls the crystal temperature control module to adjust the temperature of the corresponding crystal.

[0087] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the system of the embodiments of this application. In other embodiments of the specification, the above system may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0088] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0089] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0090] It should be noted that the above examples are merely specific embodiments of the present invention, and the present invention is obviously not limited to the above embodiments, with many similar variations. All modifications that can be directly derived or conceived by those skilled in the art from the content disclosed in this invention should fall within the protection scope of this invention.

Claims

1. A power feedback control method for a solid-state pulsed laser, characterized in that, include: Obtain the ambient temperature of the solid-state pulsed laser; The optimal operating temperature of the crystal is predicted based on the ambient temperature using a pre-trained interpolator, resulting in a first predicted value. A localized temperature scan of the crystal is performed around the first predicted value, and a second predicted value of the optimal operating temperature of the crystal is determined based on the change in the output power of the solid-state pulsed laser with the scan temperature. A prior distribution is constructed based on the first predicted value, and a likelihood function is constructed based on the second predicted value. The posterior distribution of the optimal operating temperature of the crystal is calculated to obtain a third predicted value of the optimal operating temperature of the crystal. An observation space model for the optimal operating temperature of the crystal is constructed. The parameters of the observation space model are adjusted using the second predicted value. The state estimate is then updated using an extended Kalman filter to obtain a fourth predicted value. Calculate the error between the fourth predicted value and the second predicted value, and use the error to correct the third predicted value to obtain the optimal operating temperature of the crystal; Adjust the crystal temperature to the optimal operating temperature.

2. The method according to claim 1, characterized in that, The training method for the interpolator includes: Based on multiple preset ambient temperatures, the crystal temperature of the solid-state pulsed laser is scanned at each ambient temperature. The crystal temperature is adjusted to the scanning temperature, and the output power of the solid-state pulsed laser is collected. The scanning temperature with the highest output power is taken as the optimal crystal temperature. The interpolator is trained using the ambient temperature and the corresponding optimal crystal temperature as training samples.

3. The method according to claim 1, characterized in that, A localized temperature scan of the crystal is performed around the first predicted value. A second predicted value for the optimal operating temperature of the crystal is determined based on the change in the output power of the solid-state pulsed laser with the scanned temperature. Specifically, this includes: The output power of the solid-state pulsed laser was collected at different scanning temperatures of the crystal, and a power curve showing the change of output power with the temperature of the crystal was fitted. Based on the power curve, the maximum likelihood estimate of the optimal operating temperature of the crystal is calculated to obtain the second predicted value.

4. The method according to claim 1, characterized in that, Adjusting the parameters of the observation space model using the second predicted value specifically includes: The observation noise covariance of the observation space model is adjusted using the second predicted value.

5. The method according to claim 4, characterized in that, Adjusting the parameters of the observation space model using the second predicted value further includes: The process noise covariance matrix of the observation space model is adjusted using the second predicted value.

6. The method according to claim 1, characterized in that, Calculate the error between the fourth predicted value and the second predicted value, and use the error to correct the third predicted value to obtain the optimal operating temperature of the crystal, specifically including: The long-term bias is obtained by updating using an exponentially weighted moving average: ； in, This represents the error between the fourth predicted value and the second predicted value. Indicates the forgetting factor, This indicates the correction deviation from the previous correction. This indicates the current correction deviation. The initial value is , ; The third predicted value is corrected using the long-term deviation.

7. The method according to claim 1, characterized in that, The method further includes: The laser pulse signal output by the solid-state pulse laser is converted into an electrical pulse signal by the laser power detection module, and the output power of the solid-state pulse laser is determined based on the electrical pulse signal.

8. The method according to claim 7, characterized in that, The laser power detection module is a transimpedance amplifier circuit.

9. The method according to claim 8, characterized in that, The method further includes: The peak voltage hold module performs voltage peak hold processing on the electrical pulse signal output by the transimpedance amplifier circuit.

10. The method according to claim 9, characterized in that, The method further includes: The voltage value output by the peak voltage holding module is acquired, and the output power of the solid-state pulsed laser is calculated based on the functional relationship between the voltage value and the output power of the solid-state pulsed laser.

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