阅读说明：本技术 激光器谐振腔的智能调节系统和方法 (Intelligent adjustment system and method for laser resonant cavity ) 是由 马文静 张军伟 袁晓东 胡东霞 徐振源 向勇 陈良明 周丽丹 房奇 李可欣 于 2020-07-01 设计创作，主要内容包括：本发明的实施例提供了一种激光器谐振腔的智能调节系统和方法,涉及激光器谐振腔调节技术领域。所述系统包括激光器、图像采集模块、图像处理计算模块及谐振腔调节模块,其中,所述激光器、所述图像采集模块、所述图像处理计算模块及所述谐振腔调节模块依次连接,所述图像采集模块用于采集所述激光器的谐振腔的输出光场信息,所述谐振腔调节模块包括谐振腔反射镜,所述图像处理计算模块用于对所述输出光场信息进行处理计算,并输出所述谐振腔反射镜的调整参数,所述谐振腔调节模块用于根据所述调整参数、对所述谐振腔反射镜进行调节,提高谐振腔的调节速度,保证激光器的高效稳定运行。(The embodiment of the invention provides an intelligent adjusting system and method for a laser resonant cavity, and relates to the technical field of laser resonant cavity adjustment. The system comprises a laser, an image acquisition module, an image processing calculation module and a resonant cavity adjusting module, wherein the laser, the image acquisition module, the image processing calculation module and the resonant cavity adjusting module are sequentially connected, the image acquisition module is used for acquiring output light field information of a resonant cavity of the laser, the resonant cavity adjusting module comprises a resonant cavity reflector, the image processing calculation module is used for processing and calculating the output light field information and outputting adjusting parameters of the resonant cavity reflector, and the resonant cavity adjusting module is used for adjusting the resonant cavity reflector according to the adjusting parameters, so that the adjusting speed of the resonant cavity is increased, and the efficient and stable operation of the laser is ensured.)

1. An intelligent adjustment system for laser resonant cavity, which is characterized in that the system comprises a laser (110), an image acquisition module (120), an image processing calculation module (130) and a resonant cavity adjustment module (140), wherein the laser (110), the image acquisition module (120), the image processing calculation module (130) and the resonant cavity adjusting module (140) are connected in sequence, the image acquisition module (120) is used for acquiring output optical field information of a resonant cavity of the laser (110), the resonant cavity adjusting module (140) comprises a resonant cavity reflector, the image processing and calculating module (130) is used for processing and calculating the output light field information, and outputting the adjustment parameter of the resonant cavity reflector, wherein the resonant cavity adjustment module (140) is used for adjusting the resonant cavity reflector according to the adjustment parameter.

2. A system for intelligent tuning of a laser resonator according to claim 1, characterized in that the laser (110) is a solid state laser with a resonator.

3. The system for intelligently tuning a laser resonator according to claim 1, wherein the image acquisition module (120) comprises a power meter (121) and a photovoltaic panel (122), the system further comprising a beam splitter (150), the beam splitter (150) being configured to split the output beam of the laser (110) into a transmitted beam and a reflected beam, the power meter (121) being configured to receive the transmitted beam in real time and obtain the output power of the laser, and the photovoltaic panel (122) being configured to receive the reflected beam in real time and obtain the output optical field information.

4. The system for intelligent tuning of a laser resonator according to claim 1, wherein the image processing computation module (130) comprises a near-field image processing module for image denoising and image enhancement of the output light field information.

5. The system for intelligent tuning of a laser resonator according to claim 1, wherein the image processing computation module (130) comprises a convolutional neural network model (200) based on deep learning, the convolutional neural network model (200) being configured to compute the tuning parameters of the resonator mirrors from the output light field information.

6. The system of claim 5, wherein the convolutional neural network model (200) comprises an input layer, a convolutional layer, a pooling layer, a fully-connected layer, and an output layer, wherein parameters of the convolutional layer, the pooling layer, and the fully-connected layer have been modified and updated by model learning and training, and wherein an error of the output layer is smaller than a training target.

7. An intelligent tuning system for a laser resonator according to claim 1, wherein the resonator mirrors comprise an electronically controlled input mirror (141) and an electronically controlled output mirror (142), the electronically controlled input mirror (141) and the electronically controlled output mirror (142) being arranged on either side of the laser (110), respectively, the electronically controlled input mirror (141) and the electronically controlled output mirror (142) being piezo-ceramic driven mirrors.

8. An intelligent tuning system for a laser resonator according to claim 7, wherein the electrically controlled input mirror (141) is adapted to perform curvature tuning in accordance with the tuning parameter, and the electrically controlled output mirror (142) is adapted to perform angle tuning in accordance with the tuning parameter.

9. A method of intelligent tuning of a laser resonator, the method comprising:

collecting output light field information of a resonant cavity of a laser (110);

processing and calculating the output light field information, and outputting an adjustment parameter of a resonant cavity reflector;

and adjusting the resonant cavity reflector according to the adjusting parameter.

Technical Field

The invention relates to the technical field of laser resonant cavity adjustment, in particular to an intelligent adjustment system and method for a laser resonant cavity.

Background

In the working process of the laser, due to internal or external factors, such as distortion caused by the thermal effect of a working substance, change of relative space positions of the cavity mirror caused by vibration, change of external environment temperature or humidity and the like, output beams of the laser deviate from an ideal state, the beam quality is poor, and the output power is reduced. The resonant cavity is used as an important component of the laser, has a decisive influence on the output performance of the laser, and needs to be precisely adjusted in many application scenes. At present, the adjustment mode of the resonant cavity is mainly that technicians analyze a near-field image such as a light spot pattern and a light intensity distribution diagram according to experience and adjust the cavity mirror by a hill climbing method. The method has high requirements on technicians, complicated adjusting steps and low adjusting efficiency. In order to ensure high quality operation of the laser, it is necessary to monitor the cavity in the laser in real time and fine tune it in real time.

Therefore, the design of an intelligent adjustment system and method for a laser resonant cavity can improve the efficiency and accuracy of resonant cavity adjustment, which is a technical problem that needs to be solved urgently at present.

Disclosure of Invention

The invention aims to provide an intelligent adjusting system and method for a laser resonant cavity, which can quickly and accurately give adjusting parameters of a cavity mirror and remarkably improve the adjusting efficiency and accuracy of the resonant cavity, thereby realizing the intelligent adjustment of the resonant cavity.

Embodiments of the invention may be implemented as follows:

in a first aspect, an embodiment of the present invention provides an intelligent adjustment system for a laser resonator, where the system includes a laser, an image acquisition module, an image processing calculation module, and a resonator adjustment module, where the laser, the image acquisition module, the image processing calculation module, and the resonator adjustment module are sequentially connected, the image acquisition module is configured to acquire output light field information of a resonator of the laser, the resonator adjustment module includes a resonator mirror, the image processing calculation module is configured to process and calculate the output light field information and output an adjustment parameter of the resonator mirror, and the resonator adjustment module is configured to adjust the resonator mirror according to the adjustment parameter.

In an alternative embodiment, the laser is a solid state laser having a resonant cavity.

In an optional implementation manner, the image acquisition module includes a power meter and a photovoltaic panel, the system further includes a beam splitter, the beam splitter is configured to split an output light beam of the laser into a transmitted light beam and a reflected light beam, the power meter is configured to receive the transmitted light beam in real time and acquire output power of the laser, and the photovoltaic panel is configured to receive the reflected light beam in real time and acquire the output light field information.

In an alternative embodiment, the image processing calculation module includes a near-field image processing module, and the near-field image processing module is configured to perform image denoising and image enhancement on the output light field information.

In an optional embodiment, the image processing calculation module includes a convolutional neural network model based on deep learning, and the convolutional neural network model is configured to calculate the adjustment parameter of the resonator mirror according to the output light field information.

In an optional embodiment, the convolutional neural network model includes an input layer, a convolutional layer, a pooling layer, a fully-connected layer, and an output layer, parameters of the convolutional layer, the pooling layer, and the fully-connected layer have been corrected and updated through learning and training of the model, and an error of the output layer is smaller than a training target.

In an optional embodiment, the resonator mirrors include an electrically controlled input mirror and an electrically controlled output mirror, the electrically controlled input mirror and the electrically controlled output mirror are respectively disposed on two sides of the laser, and the electrically controlled input mirror and the electrically controlled output mirror are both mirrors driven by piezoelectric ceramics.

In an alternative embodiment, the electrically controlled input mirror is configured to perform curvature adjustment according to the adjustment parameter, and the electrically controlled output mirror is configured to perform angle adjustment according to the adjustment parameter.

In a second aspect, an embodiment of the present invention provides a method for intelligently adjusting a laser resonator, where the method includes:

acquiring output light field information of a resonant cavity of a laser;

processing and calculating the output light field information, and outputting an adjustment parameter of a resonant cavity reflector;

and adjusting the resonant cavity reflector according to the adjusting parameter.

The intelligent adjusting system of the laser resonant cavity provided by the embodiment of the invention has the following beneficial effects:

the method comprises the steps of acquiring output light field information of a resonant cavity of the laser in real time, judging whether the resonant cavity of the laser deflects, calculating an adjusting parameter of a resonant cavity reflector if the resonant cavity of the laser deflects, and adjusting the resonant cavity reflector by the resonant cavity adjusting module according to the adjusting parameter, so that the adjusting speed of the resonant cavity is increased, and the efficient and stable operation of the laser is guaranteed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

FIG. 1 is a block diagram of an intelligent tuning system for a laser cavity according to a first embodiment of the present invention;

FIG. 2 is a schematic structural diagram of an intelligent tuning system for a laser resonator according to a first embodiment of the present invention;

FIG. 3 is a schematic diagram of the components of a convolutional neural network model;

fig. 4 is a flowchart of a method for intelligently adjusting a laser cavity according to a second embodiment of the present invention.

Icon: 100-an intelligent tuning system for the laser resonator; 110-a laser; 120-an image acquisition module; 121-a power meter; 122-a photovoltaic panel; 130-an image processing calculation module; 140-a resonant cavity adjustment module; 141-electrically controlled input mirror; 142-an electrically controlled output mirror; 150-a beam splitter; 200-convolutional neural network model; 210-an input layer; 220-a convolutional layer; 230-a pooling layer; 240-full connectivity layer; 250-output layer.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. indicate an orientation or a positional relationship based on that shown in the drawings or that the product of the present invention is used as it is, this is only for convenience of description and simplification of the description, and it does not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention.

Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.

It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.

The core of resonant cavity regulation is to judge the regulation direction and regulation quantity of cavity mirror according to output performance, so how to determine the relation between the output performance of resonant cavity and the position, angle and curvature of different cavity mirrors is the key point of resonant cavity regulation. For the problem of coupling input information, the deep learning technology can rapidly extract and learn sample characteristics and establish a mapping relation between different parameters, thereby realizing the efficient processing of complex input data. Therefore, the near-field image of the output light field of the resonant cavity is identified and processed by utilizing the deep learning technology, the adjustment direction and the adjustment quantity of the cavity mirror can be quickly and accurately given, the efficiency and the precision of resonant cavity adjustment are obviously improved, and the intelligent adjustment of the resonant cavity is realized.

Referring to fig. 1 and fig. 2, the present embodiment provides an intelligent adjustment system 100 for a laser resonator, which includes a laser 110, a beam splitter 150, an image acquisition module 120, an image processing and calculating module 130, and a resonator adjustment module 140. The laser 110, the image acquisition module 120, the image processing and calculating module 130, and the resonant cavity adjusting module 140 are sequentially connected. The laser 110 is a solid state laser 110 having a resonant cavity.

Specifically, the image capturing module 120 includes a power meter 121 and a photovoltaic panel 122, and the resonant cavity adjusting module 140 includes a resonant cavity mirror, which includes an electrically controlled input mirror 141 and an electrically controlled output mirror 142.

The electronic control input reflector 141 and the electronic control output reflector 142 are respectively arranged at two sides of the laser 110, and the electronic control input reflector 141 and the electronic control output reflector 142 are both reflectors driven by piezoelectric ceramics.

The image processing and calculating module 130 is electrically connected with the electronic control input reflector 141, the electronic control output reflector 142 and the photovoltaic panel 122, the beam splitter 150 is installed on one side of the electronic control output reflector 142 away from the laser 110, and the power meter 121 is installed on one side of the beam splitter 150 away from the electronic control output reflector 142.

The image collecting module 120 is configured to collect output light field information of the resonant cavity of the laser 110, where the output light field information includes an output light field near-field image of the resonant cavity of the laser 110, and send the output light field information to the image processing and calculating module 130.

The image processing calculation module 130 comprises a near-field image processing module and a convolutional neural network model 200 based on deep learning, and both the near-field image processing module and the convolutional neural network model 200 based on deep learning can be integrally packaged in a chip of the image processing calculation module 130. The image processing and calculating module 130 is configured to process and calculate the output light field information, and output an adjustment parameter of the resonator mirror, where the adjustment parameter includes an adjustment direction and an adjustment amount of the resonator mirror. The resonant cavity adjusting module 140 is configured to adjust the resonant cavity mirror according to the adjustment parameter.

Referring to fig. 3, the convolutional neural network model 200 includes an input layer 210, a convolutional layer 220, a pooling layer 230, a fully-connected layer 240, and an output layer 250, wherein the convolutional layer 220 and the pooling layer 230 are alternately stacked. The convolutional neural network model 200 is used to calculate the adjustment direction and the adjustment amount of the resonator mirror according to the output light field information. The parameters of the convolutional layer 220, the pooling layer 230, and the fully-connected layer 240 have been modified and updated by model learning and training, and the error of the output layer 250 is smaller than a training target.

The specific work flow of the intelligent adjustment system 100 for the laser resonator provided by this embodiment is as follows:

firstly, the laser 110 is connected with the image acquisition module 120, the image processing calculation module 130 and the resonant cavity adjustment module 140 in sequence to acquire and process the resonant cavity output light field of the laser 110;

secondly, the laser 110 is operated, the beam splitter 150 splits the output light beam of the laser 110 into a transmitted light beam and a reflected light beam, the transmitted light beam is transmitted to the power meter 121, the reflected light beam is transmitted to the photovoltaic panel 122, the power meter 121 receives the transmitted light beam in real time and obtains the output power of the laser, the photovoltaic panel 122 is used for receiving the reflected light beam in real time and obtaining the output light field information, whether the resonant cavity of the laser 110 is shifted or not is judged by comparing the power of the output light beam with the near-field image data, and if the resonant cavity is shifted, the near-field image collected by the photovoltaic panel 122 is input to the image processing and calculating module 130;

then, the near-field image processing module is used for carrying out image denoising, image enhancement and other operations on the output optical field near-field image of the resonant cavity, the processed image is input into the convolutional neural network model 200 for calculation, and the calculation result is output to the resonant cavity adjusting module 140;

finally, the resonant cavity adjusting module 140 receives the calculation result sent by the image processing and calculating module 130, and drives the electrically controlled input mirror 141 to perform curvature adjustment, and drives the electrically controlled output mirror 142 to perform angle adjustment.

The intelligent adjustment system 100 for the laser resonant cavity provided by the embodiment has the following beneficial effects:

the system 100 for intelligently adjusting a laser cavity according to the present embodiment includes a laser 110, an image capturing module 120, an image processing and calculating module 130, and a cavity adjusting module 140. After the laser 110 operates, the image acquisition module 120 acquires a near-field image of an output optical field of the resonant cavity of the laser 110 in real time, the near-field image is input into the image processing and calculating module 130 for processing and calculation, the resonant cavity adjusting module 140 is controlled according to an output result to complete adjustment of the resonant cavity, the optical field distribution of output laser when the laser 110 operates can be monitored in real time, whether the resonant cavity of the laser 110 deviates or not is judged, the adjustment direction and the adjustment amount of a resonant cavity reflector of the laser 110 can be judged according to the variation trend of the output optical field, and the adjustment direction and the adjustment amount are fed back to the resonant cavity adjusting module 140 for adjustment, so that the adjustment speed of the resonant cavity is improved, and efficient and stable operation.

Second embodiment

Referring to fig. 4, the present embodiment provides an intelligent tuning method for a laser resonator, which can be directly implemented by using the intelligent tuning system 100 for a laser resonator provided in the first embodiment.

The method comprises the following steps:

s1: the output optical field information of the cavity of laser 110 is collected.

The image acquisition module 120 includes a power meter 121 and a photovoltaic panel 122, the beam splitter 150 splits an output light beam of the laser 110 into a transmitted light beam and a reflected light beam, the power meter 121 is configured to receive the transmitted light beam in real time and obtain an output power of the laser, and the photovoltaic panel 122 is configured to receive the reflected light beam in real time and obtain the output light field information. The output light field information includes an output light field near-field image of the resonant cavity of the laser 110.

S2: and processing and calculating the output light field information, and outputting the adjustment parameters of the resonant cavity reflector.

The image processing and calculating module 130 is configured to process and calculate the output light field information, the image processing and calculating module 130 includes a near-field image processing module and a convolutional neural network model 200 based on deep learning, the image processing and calculating module 130 is configured to process and calculate the output light field information and output adjustment parameters of the resonant cavity mirror, and the adjustment parameters include an adjustment direction and an adjustment amount of the resonant cavity mirror.

Specifically, the near-field image processing module is used for performing operations such as image denoising and image enhancement on the output optical field near-field image of the resonant cavity. The convolutional neural network model 200 includes an input layer 210, a convolutional layer 220, a pooling layer 230, a fully-connected layer 240, and an output layer 250, wherein the convolutional layer 220 and the pooling layer 230 are alternately stacked. The convolutional neural network model 200 is used to calculate the adjustment direction and the adjustment amount of the resonator mirror according to the output light field information.

Specifically, whether the resonant cavity of the laser 110 is shifted is determined by comparing the power of the output light beam with the near-field image data, and if the resonant cavity is shifted, the near-field image collected by the photovoltaic panel 122 is input to the image processing and calculating module 130. And then, the near-field image processing module is used for carrying out image denoising, image enhancement and other operations on the near-field image of the light field output by the resonant cavity, inputting the processed image into the convolutional neural network model 200 for calculation, and then outputting the calculation result to the resonant cavity adjusting module 140. The calculation results here include the tuning parameters of the resonator mirrors.

S3: and adjusting the resonant cavity reflector according to the adjusting parameter.

Specifically, the resonant cavity adjusting module 140 receives the calculation result sent by the image processing and calculating module 130, and drives the electrically controlled input mirror 141 to perform curvature adjustment, and drives the electrically controlled output mirror 142 to perform angle adjustment.

The intelligent adjustment method for the laser resonant cavity provided by the embodiment has the beneficial effects that:

the intelligent adjustment method for the laser resonator provided in this embodiment can monitor the optical field distribution of the output laser of the laser 110 during operation in real time, determine whether the resonator of the laser 110 is shifted, determine the adjustment direction and adjustment amount of the resonator mirror of the laser 110 according to the variation trend of the output optical field, and feed back the adjustment direction and adjustment amount to the resonator adjustment module 140 for adjustment, thereby increasing the adjustment speed of the resonator and ensuring efficient and stable operation of the laser 110.

The technical core of the intelligent adjustment system 100 and method for the laser resonant cavity provided by the embodiment of the invention is as follows: aiming at the problem that the resonant cavity of the laser 110 is easy to be out of order in a complex scene, the resonant cavity is monitored in real time, the self-intelligent adjustment of the resonant cavity of the laser 110 is realized through a deep learning training control network, and the high quality and the high stability of output light beams are ensured. It is obvious to those skilled in the art that other extended schemes can be made on the basis of the technical core of the embodiment of the present invention, and the extended schemes shall fall into the protection scope of the present application.

The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.