Dynamic adjustment method and device for laser equipment processing environment

Abstract

The present invention discloses a method and device for dynamically adjusting the processing environment of a laser device, and relates to the field of environmental adjustment technology, including: constructing a first predetermined environmental feature group of the laser device under a first processing scenario; when the laser device meets the first processing scenario, collecting a real-time environmental feature group, taking the first predetermined environmental feature group as a target, optimizing the control parameters of the temperature control device, the humidity control device, and the dust removal device, and generating a first optimized environmental control parameter group; performing additional impact analysis of non-equipment control environmental indicators on the temperature control device, the humidity control device, and the dust removal device, optimizing the additional impact of the first optimized environmental control parameter group according to the analysis results, and generating an optimal environmental control parameter group to control the processing environment of the laser device. The present invention solves the technical problems of insufficient control accuracy and poor environmental adaptability of the prior art on the processing environment of laser equipment, and achieves the technical effect of accurate control and dynamic adjustment of the processing environment.

Description

Technical Field

[0001] The present invention relates to the technical field of environment adjustment, and in particular to a method and device for dynamically adjusting a processing environment of a laser device. Background Art

[0002] With the rapid development of laser technology, laser equipment is increasingly being used in materials processing, welding, cutting, and other fields. The processing environment of laser equipment significantly impacts processing quality and equipment stability, making dynamic adjustment and control of the processing environment particularly important. However, traditional methods for controlling the processing environment of laser equipment often suffer from insufficient control accuracy and poor environmental adaptability, making it difficult to meet the efficiency, precision, and reliability requirements of modern laser processing technology. Summary of the Invention

[0003] The present application provides a method and device for dynamically adjusting the processing environment of a laser device, which is used to solve the technical problems of insufficient control accuracy and poor environmental adaptability of the existing technology for the processing environment of a laser device.

[0004] In view of the above problems, the present application provides a method and device for dynamically adjusting the processing environment of a laser device.

[0005] A first aspect of the present application provides a method for dynamically adjusting a laser equipment processing environment, the method comprising:

[0006] Construct a first predetermined environmental feature group for the laser equipment in a first processing scenario, wherein the first predetermined environmental feature group includes a first predetermined temperature feature value, a first predetermined humidity feature value, and a first predetermined dust feature value; when the laser equipment meets the first processing scenario, collect a real-time environmental feature group, and with the first predetermined environmental feature group as the target, optimize the control parameters of the temperature control equipment, the humidity control equipment, and the dust removal equipment to generate a first optimized environmental control parameter group; perform additional impact analysis of non-equipment control environmental indicators on the temperature control equipment, the humidity control equipment, and the dust removal equipment, perform additional impact optimization on the first optimized environmental control parameter group based on the additional impact analysis results, and generate an optimal environmental control parameter group; control the processing environment of the laser equipment according to the optimal environmental control parameter group.

[0007] A second aspect of the present application provides a dynamic adjustment device for a laser equipment processing environment, the device comprising:

[0008] An environmental feature group construction module, wherein the environmental feature group construction module constructs a first predetermined environmental feature group for the laser equipment under a first processing scenario, wherein the first predetermined environmental feature group includes a first predetermined temperature feature value, a first predetermined humidity feature value, and a first predetermined dust feature value; a control parameter optimization module, wherein when the laser equipment meets the first processing scenario, the control parameter optimization module collects a real-time environmental feature group, and optimizes the control parameters of the temperature control equipment, the humidity control equipment, and the dust removal equipment with the first predetermined environmental feature group as the target, to generate a first optimized environmental control parameter group; an additional impact optimization module, wherein the additional impact optimization module performs additional impact analysis of non-equipment control environmental indicators on the temperature control equipment, the humidity control equipment, and the dust removal equipment, and performs additional impact optimization on the first optimized environmental control parameter group based on the additional impact analysis results to generate an optimal environmental control parameter group; a processing environment control module, wherein the processing environment control module controls the processing environment of the laser equipment according to the optimal environmental control parameter group.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] The present application constructs a first predetermined environmental characteristic group for a laser device under a first processing scenario, wherein the first predetermined environmental characteristic group includes a first predetermined temperature characteristic value, a first predetermined humidity characteristic value, and a first predetermined dust characteristic value; when the laser device meets the first processing scenario, a real-time environmental characteristic group is collected, and with the first predetermined environmental characteristic group as the target, the temperature control device, the humidity control device, and the dust removal device are optimized for control parameters to generate a first optimized environmental control parameter group; an additional impact analysis of non-equipment control environmental indicators is performed on the temperature control device, the humidity control device, and the dust removal device, and the additional impact optimization is performed on the first optimized environmental control parameter group based on the additional impact analysis results to generate an optimal environmental control parameter group; and the processing environment of the laser device is controlled according to the optimal environmental control parameter group. The present invention solves the technical problems of insufficient control accuracy and poor environmental adaptability of the existing technology for the laser device processing environment, and achieves the technical effect of precise control and dynamic adjustment of the processing environment by real-time monitoring of key parameters in the processing process and combining control algorithms and data processing technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1A schematic flow chart of a method for dynamically adjusting a laser equipment processing environment provided in an embodiment of the present application.

[0013] Figure 2 A schematic diagram of the structure of a device for dynamically adjusting the laser equipment processing environment provided in an embodiment of the present application.

[0014] Explanation of the accompanying symbols: environmental feature group construction module 11, control parameter optimization module 12, additional impact optimization module 13, processing environment control module 14. DETAILED DESCRIPTION

[0015] This application provides a dynamic adjustment method and equipment for the laser equipment processing environment, aiming to solve the technical problems of insufficient control accuracy and poor environmental adaptability of the existing technology for the laser equipment processing environment. By real-time monitoring of key parameters in the processing process, combined with control algorithms and data processing technology, the technical effect of precise control and dynamic adjustment of the processing environment is achieved.

[0016] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0017] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0018] Example 1

[0019] like Figure 1 As shown, the present application provides a method for dynamically adjusting a laser equipment processing environment, the method comprising:

[0020] Step S100: constructing a first predetermined environmental characteristic group for a laser device in a first processing scenario, wherein the first predetermined environmental characteristic group includes a first predetermined temperature characteristic value, a first predetermined humidity characteristic value, and a first predetermined dust characteristic value.

[0021] In the embodiment of the present application, a technical expert sets a first predetermined environmental characteristic group for the laser device in a first processing scenario based on the operating requirements of the laser device. The first predetermined environmental characteristic group includes a first predetermined temperature characteristic value, a first predetermined humidity characteristic value, and a first predetermined dust characteristic value.

[0022] Step S200: When the laser equipment meets the first processing scenario, a real-time environmental feature group is collected, and with the first predetermined environmental feature group as the target, the control parameters of the temperature control equipment, the humidity control equipment and the dust removal equipment are optimized to generate a first optimized environmental control parameter group.

[0023] In the embodiment of the present application, when the laser device meets the first processing scenario, i.e., this scenario meets the previously set processing requirements, sensors and monitoring equipment are used to collect the temperature, humidity, and dust concentration of the current environment in real time. The collected data is organized into a real-time environmental feature group, including real-time temperature values, real-time humidity values, and real-time dust concentration values.

[0024] Compare the real-time temperature value with the first predetermined temperature characteristic value and calculate the temperature deviation. Adjust the parameters of the temperature control device based on the temperature deviation to optimize temperature control. For example, if the real-time temperature is lower than the predetermined temperature, increase the heating power; if it is higher than the predetermined temperature, increase the cooling power. Compare the real-time humidity value with the first predetermined humidity characteristic value and calculate the humidity deviation. Adjust the parameters of the humidity control device based on the humidity deviation to optimize humidity control. For example, if the real-time humidity is lower than the predetermined humidity, increase the humidification amount; if it is higher than the predetermined humidity, increase the dehumidification amount. Compare the real-time dust concentration value with the first predetermined dust characteristic value and calculate the dust deviation. Adjust the parameters of the dust removal device based on the dust deviation to optimize dust control. For example, if the real-time dust concentration is higher than the predetermined dust concentration, increase the working intensity of the dust removal device.

[0025] The first optimized environment control parameter group is generated by combining the optimized parameters of the temperature control device, the humidity control device and the dust removal device.

[0026] Step S300: Perform additional impact analysis of non-equipment control environmental indicators on the temperature control equipment, the humidity control equipment and the dust removal equipment, and perform additional impact optimization on the first optimized environmental control parameter group based on the additional impact analysis results to generate an optimal environmental control parameter group.

[0027] In an embodiment of the present application, when analyzing the additional impact of a temperature control device, the parameters of the temperature control device are set as variables, and the parameters of the humidity control device and the dust removal device are set as quantitative values. Changes in humidity and dust concentration under different temperature control parameters are recorded. The additional impact of changes in the temperature control device parameters on humidity and dust concentration is analyzed, generating an analysis result for the additional impact of the temperature control device. When analyzing the additional impact of a humidity control device, the parameters of the humidity control device are set as variables. The parameters of the temperature control device and the dust removal device are set as quantitative values. Changes in temperature and dust concentration under different humidity control parameters are recorded. The additional impact of changes in the humidity control device parameters on temperature and dust concentration is analyzed, generating an analysis result for the additional impact of the humidity control device. When analyzing the additional impact of a dust removal device, the parameters of the dust removal device are set as variables. The parameters of the temperature control device and the humidity control device are set as quantitative values. Changes in temperature and humidity under different dust removal device parameters are recorded. The additional impact of changes in the dust removal device parameters on temperature and humidity is analyzed, generating an analysis result for the additional impact of the dust removal device. The analysis results for the additional impacts of temperature, humidity, and dust removal devices are integrated to form an analysis result for the additional impact. Finally, based on the additional impact analysis results, the first optimized environmental control parameter group is optimized for additional impact to generate the optimal environmental control parameter group.

[0028] Step S400: Controlling the processing environment of the laser device according to the optimal environmental control parameter group.

[0029] In the embodiment of the present application, the optimal environmental control parameter set includes the optimal parameters of the temperature control device, the optimal parameters of the humidity control device, and the optimal parameters of the dust removal device. The optimal temperature parameter is input into the temperature control device, the optimal humidity parameter is input into the humidity control device, and the optimal dust control parameter is input into the dust removal device. Then, the temperature control device, the humidity control device, and the dust removal device are activated to control the processing environment.

[0030] Furthermore, step S200 in the method provided in the application embodiment further includes:

[0031] Determine whether the real-time environmental feature group satisfies the first predetermined environmental feature group; if not, locate the abnormal environmental indicator type, abnormal environmental indicator value sequence and abnormal environmental control target; locate the device to be controlled in the temperature control device, the humidity control device and the dust removal device based on the abnormal environmental indicator type; take the abnormal environmental control target as the control target, perform target arrival stage control and target continuous stability stage control on the device to be controlled based on the abnormal environmental indicator value sequence, and generate first stage control parameters and second stage control parameters; generate the first optimized environmental control parameter group with the first stage control parameters and the second stage control parameters.

[0032] In an embodiment of the present application, the real-time environmental feature group is compared with a preset first predetermined environmental feature group. If the real-time environmental feature group does not meet the first predetermined environmental feature group, the abnormal environmental indicator type is located. For example, one or more of the temperature, humidity or dust concentration exceeds the predetermined range. At the same time, the abnormal environmental parameter values ​​over a period of time are recorded to form a sequence of abnormal environmental indicator values. According to the predetermined environmental parameter values, the abnormal environmental control target is set, that is, the abnormal environmental parameters are controlled to the predetermined environmental parameters. According to the abnormal environmental indicator type, the device to be controlled is located among the temperature control device, the humidity control device and the dust removal device. That is, if the temperature does not meet the requirements, the temperature control device is selected as the device to be controlled. If the humidity does not meet the requirements, the humidity control device is selected as the device to be controlled. If the dust concentration does not meet the requirements, the dust removal device is selected as the device to be controlled.

[0033] Next, data analysis algorithms, such as moving average and linear regression, are used to identify environmental change trends. Initial control parameters are set based on the abnormal indicator value sequence and the control target. For example, when the humidity is high, the initial control parameter is to set the dehumidification equipment's operating power to the maximum. The initial control parameters are executed to quickly bring the environmental parameters close to the target value. This is the target arrival stage control. When the control target is about to be reached, the equipment's operating power is gradually reduced. This is the target sustained stability stage control. This process generates the first-stage control parameters and the second-stage control parameters. Finally, the generated first-stage control parameters and the second-stage control parameters are integrated to obtain the first optimized environmental control parameter group. The first optimized environmental control parameter group includes the equipment control parameters for the target arrival stage control and the target sustained stability stage control.

[0034] Furthermore, in the method provided in the embodiment of the application, the abnormal environment control target is used as the control target, and the target arrival stage control and the target continuous stability stage control are performed on the controlled device based on the abnormal environment indicator value sequence, and the first stage control parameters and the second stage control parameters are generated, including:

[0035] Based on the abnormal environment indicator value sequence, abnormal environment change trends are identified to generate abnormal change trends; based on the abnormal environment indicator value sequence and the abnormal change trend, target arrival stage control optimization is performed to generate the first stage control parameters; based on the abnormal change trend, the control target is stably controlled in a preset continuous operation time zone to generate the second stage control parameters.

[0036] In the embodiments of the present application, time series analysis algorithms, such as moving average, linear regression, and ARIMA models, are used to identify the changing trends of abnormal environmental parameters. For example, by analyzing the humidity value sequence data in the abnormal environmental indicator value sequence, the upward or downward trend of humidity is identified, and its change rate and trend direction are calculated. Through this process, the abnormal change trend is generated.

[0037] Next, a control strategy is developed based on the sequence of abnormal environmental indicator values ​​and their changing trends. For example, if the temperature is rising rapidly, the power of the temperature control device is increased. Optimization algorithms, such as gradient descent and genetic algorithms, are used to automatically adjust the device's control parameters. The optimization goal is to reach the target environmental indicator value as quickly and stably as possible. The optimal control parameter combination is used as the first-stage control parameters.

[0038] During the set continuous operating period, environmental parameters are continuously monitored and adjusted. Stable control strategies are developed and adjusted based on previously identified abnormal change trends. For example, when humidity approaches the preset value, the operating power of the humidity control device is reduced to avoid unnecessary energy waste or adverse effects on the equipment caused by excessively low humidity. During the stable control process, the parameters of the control device are adjusted through real-time monitoring and feedback. This adjustment is dynamic, responding quickly to real-time changes in environmental parameters and automatically adjusting the operating status of the control device. In this way, environmental parameters are ensured to remain within the predetermined range, achieving efficient and stable control. Finally, after continuous monitoring and adjustment, the control parameters for the second stage are generated.

[0039] Furthermore, in the method provided in the embodiment of the application, the abnormal environment indicator value sequence and the abnormal change trend are combined to perform target arrival stage control optimization and generate the first stage control parameters, including:

[0040] The abnormal environment control step length is calculated using the endpoint indicator value in the abnormal environment indicator value sequence and the control target; the control center of the device to be controlled is connected to match the control parameters of the abnormal environment control step length to generate the first-stage initialization control parameters and the first control duration; the control error feedback optimization is performed in combination with the first control duration and the abnormal change trend to generate the first-stage control parameters.

[0041] In the embodiments of the present application, the abnormal environment control step size is first calculated based on the endpoint indicator value in the abnormal environment indicator value sequence and the predetermined control target. This step uses methods such as difference calculation or proportional control to determine the amount of adjustment required for the control device. For example, if the endpoint value of the humidity indicator is 55% and the control target is 45%, the humidity needs to be reduced by 10%. This 10% is the control step size. The calculated control step size is then transmitted to the control center of the device to be controlled, where a control parameter matching algorithm is used to generate the first-stage initial control parameters and the first control duration. Based on the step size and the device's response characteristics, the control center determines appropriate parameter settings and operating time to quickly adjust the environmental parameters to approach the predetermined target. For example, the humidity control device needs to operate at what power and for how long to reduce the humidity by 10%. After the initial control phase, control error feedback optimization is performed based on the first control duration and the abnormal change trend. This process uses a feedback control algorithm, such as PID control, to continuously monitor the difference between the actual environmental parameters and the predetermined target and adjust the control parameters in real time to reduce the error. Through multiple iterative optimizations, the device operating parameters are gradually adjusted to generate the first-stage control parameters.

[0042] Furthermore, step S300 in the method provided in the application embodiment further includes:

[0043] Taking the control parameters of the temperature control device as variables and the control parameters of the humidity control device and the dust removal device as quantities, control records are collected to generate temperature control parameter samples, humidity additional control samples and dust additional control samples; based on the temperature control parameter samples, the humidity additional control samples and the dust additional control samples, the correlation impact analysis of the humidity index and the dust index of the temperature control device is performed to generate a first additional impact analysis result of the temperature control device; similarly, taking the control parameters of the humidity control device as variables and the control parameters of the temperature control device and the dust removal device as quantities, an additional impact analysis of the non-equipment control environment index is performed to generate a second additional impact analysis result of the humidity control device; taking the control parameters of the dust removal device as variables and the control parameters of the temperature control device and the humidity control device as quantities, an additional impact analysis of the non-equipment control environment index is performed to generate a third additional impact analysis result of the dust removal device; the additional impact analysis result is generated based on the first additional impact analysis result, the second additional impact analysis result and the third additional impact analysis result.

[0044] In an embodiment of the present application, the control parameters of the temperature control device are set as variables, while the control parameters of the humidity control device and the dust removal device are kept quantitative. Under this setting, environmental control is performed and data is recorded. A temperature control parameter sample is generated, and the changes in humidity and dust caused by changes in the temperature control device are recorded to form a humidity additional control sample and a dust additional control sample. Based on the temperature control parameter sample, the humidity additional control sample and the dust additional control sample, the associated impact of the temperature control device on the humidity and dust indicators is determined through correlation impact analysis. During the analysis process, statistical analysis and multiple regression analysis are used to evaluate the comprehensive impact of the control parameters of each device on the environmental indicators. Descriptive statistics are performed on the temperature control parameter sample, and statistical quantities such as the mean and standard deviation are calculated. A multiple regression model is established, with humidity and dust concentration as dependent variables and temperature control parameters as independent variables, to analyze the impact of temperature control on humidity and dust. The influence coefficient and correlation of temperature control on humidity and dust are output to generate the first additional impact analysis result.

[0045] Similarly, set the humidity control parameters as variables, while keeping the temperature control and dust removal parameters constant. Under this setup, perform environmental control and record the data. Generate humidity control parameter samples, and record the temperature and dust changes caused by the humidity control changes. Analyze the impact of the humidity control on temperature and dust indicators, and generate the results of a second additional impact analysis.

[0046] Similarly, set the control parameters of the dust removal equipment as variables, while keeping the control parameters of the temperature and humidity control equipment constant. Under this setting, perform environmental control and record the data. Generate dust removal control parameter samples, and record the temperature and humidity changes caused by the changes in the dust removal equipment. Analyze the correlation between the dust removal equipment and the temperature and humidity indicators to generate the results of the third additional impact analysis.

[0047] Next, the results of the first, second, and third additional impact analyses are aggregated to form a comprehensive dataset. Association analysis techniques are used to discover association rules between control equipment parameters and environmental indicators. Association rule mining is performed using the Apriori algorithm or the FP-Growth algorithm. Based on the association analysis results, association rules are mined between each control equipment parameter and environmental indicator. Based on the mined association rules, the final additional impact analysis results are generated. These results detail the specific impact of each control equipment parameter on the environmental indicator. For example, for every 1°C increase in temperature, humidity decreases by 0.5% and dust concentration increases by 0.1 mg / m³.

[0048] Furthermore, in the method provided in the embodiment of the application, the additional impact optimization is performed on the first optimized environmental control parameter group based on the additional impact analysis result to generate the optimal environmental control parameter group, including:

[0049] Based on the first additional impact analysis result, the first optimized environmental control parameter group is subjected to a first feedback optimization to generate a first optimized parameter group; based on the second additional impact analysis result, the first optimized parameter group is subjected to a second feedback optimization to generate a second optimized parameter group; based on the third additional impact analysis result, the second optimized parameter group is subjected to a third feedback optimization to generate the optimal environmental control parameter group.

[0050] In an embodiment of the present application, multiple feedback optimizations are performed on the environmental control parameters through correlation analysis to ensure precise control of environmental conditions. First, the results of the first additional impact analysis are obtained, and the influence coefficients of the temperature control equipment on humidity and dust are determined through correlation analysis. Based on these influence coefficients, the initial environmental control parameter group is linearly adjusted to optimize humidity and dust concentration, thereby generating a primary optimization parameter group. Next, the results of the second additional impact analysis are used to obtain the influence coefficients of the humidity control equipment on temperature and dust. Based on the primary optimization parameter group, the temperature and dust concentration are further optimized through a multivariable adjustment method, and the humidity settings are adjusted to generate a secondary optimization parameter group. Finally, the results of the third additional impact analysis are used to determine the influence coefficients of the dust removal equipment on temperature and humidity. Based on the secondary optimization parameter group, the dust removal equipment settings are adjusted through a nonlinear optimization method to optimize temperature and humidity, and ultimately generate the optimal environmental control parameter group.

[0051] Furthermore, in the method provided in the embodiment of the application, after controlling the processing environment of the laser device according to the optimal environmental control parameter group, the method includes:

[0052] The laser equipment is continuously monitored for its environment to generate a continuous temperature monitoring data stream, a continuous humidity monitoring data stream, and a continuous dust monitoring data stream; and a cyclic optimization of an environmental control parameter group is performed based on the continuous temperature monitoring data stream, the continuous humidity monitoring data stream, and the continuous dust monitoring data stream.

[0053] In this embodiment, sensors and a data acquisition system are first used to continuously monitor temperature, humidity, and dust concentration, recording environmental parameters in real time and generating continuous temperature, humidity, and dust monitoring data streams. These data streams record changes in temperature, humidity, and dust concentration at different points in time.

[0054] Based on these continuous data streams, a cyclic optimization search is performed on the environmental control parameter set. First, the data stream is analyzed, and through time series analysis and statistical methods, the changing trends and periodic fluctuations of environmental parameters are identified. Through correlation analysis of temperature, humidity, and dust data, the mutual influence and correlation between the various parameters are discovered. Using these analysis results, the environmental control parameters are cyclically optimized. Specifically, optimization algorithms such as PID control and adaptive control are used to dynamically adjust the control parameters of temperature, humidity, and dust removal equipment based on real-time monitoring data. Through continuous iteration and feedback adjustment, the environmental parameters are ensured to always remain within the optimal range.

[0055] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0056] The present application constructs a first predetermined environmental characteristic group for a laser device under a first processing scenario, wherein the first predetermined environmental characteristic group includes a first predetermined temperature characteristic value, a first predetermined humidity characteristic value, and a first predetermined dust characteristic value; when the laser device meets the first processing scenario, a real-time environmental characteristic group is collected, and with the first predetermined environmental characteristic group as the target, the temperature control device, the humidity control device, and the dust removal device are optimized for control parameters to generate a first optimized environmental control parameter group; an additional impact analysis of non-equipment control environmental indicators is performed on the temperature control device, the humidity control device, and the dust removal device, and the additional impact optimization is performed on the first optimized environmental control parameter group based on the additional impact analysis results to generate an optimal environmental control parameter group; and the processing environment of the laser device is controlled according to the optimal environmental control parameter group. The present invention solves the technical problems of insufficient control accuracy and poor environmental adaptability of the existing technology for the laser device processing environment, and achieves the technical effect of precise control and dynamic adjustment of the processing environment by real-time monitoring of key parameters in the processing process and combining control algorithms and data processing technologies.

[0057] Example 2

[0058] Based on the same inventive concept as the method for dynamically adjusting the laser equipment processing environment in the aforementioned embodiment, Figure 2 As shown, the present application provides a dynamic adjustment device for a laser equipment processing environment. The device and method embodiments in the present application are based on the same inventive concept. The device includes:

[0059] An environmental feature group construction module 11 is configured to construct a first predetermined environmental feature group for the laser device in a first processing scenario, wherein the first predetermined environmental feature group includes a first predetermined temperature feature value, a first predetermined humidity feature value, and a first predetermined dust feature value;

[0060] a control parameter optimization module 12, wherein when the laser device satisfies the first processing scenario, the control parameter optimization module 12 collects a real-time environmental feature group, and optimizes the control parameters of the temperature control device, the humidity control device, and the dust removal device based on the first predetermined environmental feature group to generate a first optimized environmental control parameter group;

[0061] an additional impact optimization module 13, which performs additional impact analysis on non-equipment control environmental indicators of the temperature control device, the humidity control device, and the dust removal device, and performs additional impact optimization on the first optimized environmental control parameter group based on the additional impact analysis results to generate an optimal environmental control parameter group;

[0062] The processing environment control module 14 controls the processing environment of the laser device according to the optimal environment control parameter group.

[0063] Furthermore, the device is also used to implement the following functions:

[0064] Determine whether the real-time environmental feature group satisfies the first predetermined environmental feature group; if not, locate the abnormal environmental indicator type, abnormal environmental indicator value sequence and abnormal environmental control target; locate the device to be controlled in the temperature control device, the humidity control device and the dust removal device based on the abnormal environmental indicator type; take the abnormal environmental control target as the control target, perform target arrival stage control and target continuous stability stage control on the device to be controlled based on the abnormal environmental indicator value sequence, and generate first stage control parameters and second stage control parameters; generate the first optimized environmental control parameter group with the first stage control parameters and the second stage control parameters.

[0065] Furthermore, the device is also used to implement the following functions:

[0066] Based on the abnormal environment indicator value sequence, abnormal environment change trends are identified to generate abnormal change trends; based on the abnormal environment indicator value sequence and the abnormal change trend, target arrival stage control optimization is performed to generate the first stage control parameters; based on the abnormal change trend, the control target is stably controlled in a preset continuous operation time zone to generate the second stage control parameters.

[0067] Furthermore, the device is also used to implement the following functions:

[0068] The abnormal environment control step length is calculated using the endpoint indicator value in the abnormal environment indicator value sequence and the control target; the control center of the device to be controlled is connected to match the control parameters of the abnormal environment control step length to generate the first-stage initialization control parameters and the first control duration; the control error feedback optimization is performed in combination with the first control duration and the abnormal change trend to generate the first-stage control parameters.

[0069] Furthermore, the device is also used to implement the following functions:

[0070] Taking the control parameters of the temperature control device as variables and the control parameters of the humidity control device and the dust removal device as quantities, control records are collected to generate temperature control parameter samples, humidity additional control samples and dust additional control samples; based on the temperature control parameter samples, the humidity additional control samples and the dust additional control samples, the correlation impact analysis of the humidity index and the dust index of the temperature control device is performed to generate a first additional impact analysis result of the temperature control device; similarly, taking the control parameters of the humidity control device as variables and the control parameters of the temperature control device and the dust removal device as quantities, an additional impact analysis of the non-equipment control environment index is performed to generate a second additional impact analysis result of the humidity control device; taking the control parameters of the dust removal device as variables and the control parameters of the temperature control device and the humidity control device as quantities, an additional impact analysis of the non-equipment control environment index is performed to generate a third additional impact analysis result of the dust removal device; the additional impact analysis result is generated based on the first additional impact analysis result, the second additional impact analysis result and the third additional impact analysis result.

[0071] Furthermore, the device is also used to implement the following functions:

[0072] Based on the first additional impact analysis result, the first optimized environmental control parameter group is subjected to a first feedback optimization to generate a first optimized parameter group; based on the second additional impact analysis result, the first optimized parameter group is subjected to a second feedback optimization to generate a second optimized parameter group; based on the third additional impact analysis result, the second optimized parameter group is subjected to a third feedback optimization to generate the optimal environmental control parameter group.

[0073] Furthermore, the device is also used to implement the following functions:

[0074] The laser equipment is continuously monitored for its environment to generate a continuous temperature monitoring data stream, a continuous humidity monitoring data stream, and a continuous dust monitoring data stream; and a cyclic optimization of an environmental control parameter group is performed based on the continuous temperature monitoring data stream, the continuous humidity monitoring data stream, and the continuous dust monitoring data stream.

[0075] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0076] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0077] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A method for dynamically adjusting a laser equipment processing environment, characterized in that: The method comprises: Constructing a first predetermined environmental feature group for the laser device in a first processing scenario, wherein the first predetermined environmental feature group includes a first predetermined temperature feature value, a first predetermined humidity feature value, and a first predetermined dust feature value; When the laser device meets the first processing scenario, a real-time environmental feature group is collected, and the first predetermined environmental feature group is used as a target to optimize the control parameters of the temperature control device, the humidity control device and the dust removal device to generate a first optimized environmental control parameter group; Performing additional impact analysis of non-equipment controlled environmental indicators on the temperature control device, the humidity control device, and the dust removal device, and performing additional impact optimization on the first optimized environmental control parameter group based on the additional impact analysis results to generate an optimal environmental control parameter group; Controlling the processing environment of the laser device according to the optimal environmental control parameter group; The additional impact analysis of non-equipment controlled environmental indicators on the temperature control equipment, the humidity control equipment and the dust removal equipment includes: Taking the control parameters of the temperature control device as variables and the control parameters of the humidity control device and the dust removal device as quantities, control records are collected to generate temperature control parameter samples, humidity additional control samples, and dust additional control samples; Based on the temperature control parameter sample, the humidity additional control sample and the dust additional control sample, a correlation impact analysis of the humidity index and the dust index of the temperature control device is performed to generate a first additional impact analysis result of the temperature control device; Similarly, taking the control parameters of the humidity control device as variables and the control parameters of the temperature control device and the dust removal device as quantities, an additional impact analysis of non-equipment controlled environmental indicators is performed to generate a second additional impact analysis result of the humidity control device; Taking the control parameters of the dust removal equipment as variables and the control parameters of the temperature control equipment and the humidity control equipment as quantities, an additional impact analysis of non-equipment controlled environmental indicators is performed to generate a third additional impact analysis result of the dust removal equipment; The additional impact analysis result is generated by using the first additional impact analysis result, the second additional impact analysis result, and the third additional impact analysis result.

2. The method for dynamically adjusting the processing environment of a laser device according to claim 1, characterized in that: Optimizing the control parameters of the temperature control equipment, the humidity control equipment, and the dust removal equipment to generate a first optimized environment control parameter group, including: Determine whether the real-time environmental feature group meets the first predetermined environmental feature group, and if not, locate the abnormal environmental indicator type, abnormal environmental indicator value sequence and abnormal environmental control target; Locating the device to be controlled among the temperature control device, the humidity control device, and the dust removal device based on the abnormal environment indicator type; Taking the abnormal environment control target as the control target, performing target arrival stage control and target continuous stability stage control on the device to be controlled based on the abnormal environment indicator value sequence, and generating first stage control parameters and second stage control parameters; The first optimization environment control parameter group is generated using the first stage control parameters and the second stage control parameters.

3. The method for dynamically adjusting the processing environment of a laser device according to claim 2, characterized in that: Taking the abnormal environment control target as the control target, the target arrival stage control and the target continuous stability stage control are performed on the controlled device based on the abnormal environment indicator value sequence, and the first stage control parameters and the second stage control parameters are generated, including: Identify abnormal environment change trends based on the abnormal environment indicator value sequence and generate abnormal change trends; Combining the abnormal environment indicator value sequence with the abnormal change trend, performing target arrival stage control optimization, and generating the first stage control parameters; Based on the abnormal change trend, the control target is stably controlled in a preset continuous operation time zone to generate the second-stage control parameters.

4. The method for dynamically adjusting the processing environment of a laser device according to claim 3, characterized in that: Combining the abnormal environment indicator value sequence with the abnormal change trend, performing target arrival stage control optimization, and generating the first stage control parameters, including: Calculating the abnormal environment control step length based on the endpoint index value in the abnormal environment index value sequence and the control target; Connecting to the control center of the device to be controlled, matching the control parameters of the abnormal environment control step, and generating the first stage initialization control parameters and the first control duration; The control error feedback optimization is performed in combination with the first control duration and the abnormal change trend to generate the first stage control parameters.

5. The method for dynamically adjusting the processing environment of a laser device according to claim 1, characterized in that: The additional impact analysis result is used to perform additional impact optimization on the first optimized environmental control parameter group to generate an optimal environmental control parameter group, including: Performing a feedback optimization on the first optimized environment control parameter group based on the first additional impact analysis result to generate a primary optimized parameter group; Performing secondary feedback optimization on the primary optimization parameter group based on the second additional impact analysis result to generate a secondary optimization parameter group; Based on the third additional impact analysis result, the secondary optimization parameter group is subjected to a tertiary feedback optimization to generate the optimal environmental control parameter group.

6. The method for dynamically adjusting the processing environment of a laser device according to claim 1, characterized in that: After controlling the processing environment of the laser device according to the optimal environment control parameter group, the method further includes: Continuously monitoring the environment of the laser equipment to generate a continuous temperature monitoring data stream, a continuous humidity monitoring data stream, and a continuous dust monitoring data stream; A cyclic optimization search for an environmental control parameter group is performed based on the continuous temperature monitoring data stream, the continuous humidity monitoring data stream, and the continuous dust monitoring data stream.

7. A dynamic adjustment device for a laser equipment processing environment, characterized in that: For implementing the method according to any one of claims 1 to 6, the device comprises: An environmental feature group construction module, wherein the environmental feature group construction module constructs a first predetermined environmental feature group of the laser device in a first processing scenario, wherein the first predetermined environmental feature group includes a first predetermined temperature feature value, a first predetermined humidity feature value, and a first predetermined dust feature value; A control parameter optimization module, wherein when the laser device meets the first processing scenario, the control parameter optimization module collects a real-time environmental feature group, and optimizes the control parameters of the temperature control device, the humidity control device, and the dust removal device with the first predetermined environmental feature group as the target, to generate a first optimized environmental control parameter group; an additional impact optimization module, which performs additional impact analysis on the temperature control device, the humidity control device, and the dust removal device on non-equipment control environment indicators, and performs additional impact optimization on the first optimized environment control parameter group based on the additional impact analysis result to generate an optimal environment control parameter group; A processing environment control module is used to control the processing environment of the laser device according to the optimal environment control parameter group.

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