Self-adaptive cooling control method and device of air compressor for laser cutting

Abstract

The invention discloses a self-adaptive cooling control method and device for an air compressor for laser cutting, and relates to the technical field related to non-electrical variable control, and the method comprises the steps: carrying out the temperature rise data analysis under various operation loads for the air compressor for laser cutting, building a plurality of temperature rise consistent monitoring regions, and correspondingly determining a plurality of temperature monitoring modules. And performing temperature control influence sensitivity analysis on the plurality of temperature rise consistent monitoring areas to generate a plurality of temperature control sensitivities. And performing liquid cooling channel configuration based on the plurality of temperature control sensitivities, establishing a plurality of liquid cooling systems, performing construction of temperature control models, and establishing a plurality of temperature control models. And receiving a plurality of temperature monitoring data through a plurality of temperature monitoring modules, inputting the temperature monitoring data into a plurality of temperature control models to generate cooling control parameters, and performing cooling control. The technical problems that in the prior art, a cooling method of an air compressor for laser cutting is difficult to conduct self-adaptive adjustment based on different operation loads, so that the temperature control precision is poor, and the equipment performance and efficiency are affected are solved.

Description

Technical Field

[0001] This application relates to the field of non-electric variable control technology, specifically to an adaptive cooling control method and device for an air compressor used in laser cutting. Background Technology

[0002] In laser cutting equipment, the air compressor is a crucial auxiliary device, providing the necessary air pressure to ensure efficient operation of the cutting process. Air compressors generate a significant amount of heat when operating under high loads. If cooling is not timely and effective, excessively high temperatures can lead to decreased equipment performance, shortened lifespan, and even safety hazards. However, traditional cooling methods typically employ fixed cooling strategies, making it difficult to adaptively adjust to the temperature under different operating loads of the air compressor, thus affecting the efficiency and reliability of laser cutting.

[0003] Therefore, in the existing technology, the air compressor cooling method for laser cutting is difficult to adaptively adjust based on different operating loads, resulting in poor temperature control accuracy and technical problems that affect equipment performance and efficiency. Summary of the Invention

[0004] This application provides an adaptive cooling control method and device for air compressors used in laser cutting, solving the technical problem that existing cooling methods for air compressors used in laser cutting are difficult to adaptively adjust based on different operating loads, resulting in poor temperature control accuracy and affecting equipment performance and efficiency. It achieves precise management of air compressor temperature, ensuring the equipment operates within the optimal temperature range, thus improving the performance and efficiency of laser cutting.

[0005] This application provides an adaptive cooling control method for an air compressor used in laser cutting. The method includes: analyzing temperature rise data of the air compressor under various operating loads to establish multiple temperature rise consistent monitoring zones, and correspondingly determining multiple temperature monitoring modules. Performing temperature control sensitivity analysis on the multiple temperature rise consistent monitoring zones to generate multiple temperature control sensitivities. Based on the multiple temperature control sensitivities, configuring liquid cooling channels to establish multiple liquid cooling systems, and then constructing temperature control models for the multiple temperature rise consistent monitoring zones to establish multiple temperature control models. Receiving multiple temperature monitoring data through the multiple temperature monitoring modules and inputting them into the multiple temperature control models to generate cooling control parameters, and then performing cooling control through the multiple liquid cooling systems.

[0006] In the implementation method, temperature rise data analysis is performed on the air compressor used for laser cutting under various operating loads to establish multiple temperature rise consistency monitoring areas. This includes: analyzing temperature rise data of the air compressor used for laser cutting under various operating loads to generate multiple operating temperature fields; segmenting the multiple operating temperature fields according to a preset temperature consistency deviation to generate multiple temperature field segmentation results; and performing temperature fluctuation analysis and fusion on the multiple temperature field segmentation results to generate the multiple temperature rise consistency monitoring areas.

[0007] In the implementation, temperature fluctuation analysis and fusion are performed on the multiple temperature field segmentation results to generate multiple temperature rise consistent monitoring regions. This includes: taking an edge position of the laser cutting air compressor as a base point, extracting multiple first sub-temperature fields starting from the base point from the multiple temperature field segmentation results. Fluctuation consistency analysis is performed on the multiple first sub-temperature fields to generate a first fluctuation consistency index. It is determined whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index. If so, the largest field area among the multiple first sub-temperature fields is taken as the first temperature rise consistent monitoring region and added to the multiple temperature rise consistent monitoring regions. Continuing with the first temperature rise consistent monitoring region as the starting point, the next sub-temperature field is extracted from the multiple temperature field segmentation results, and overlapping positions with the first temperature rise consistent monitoring region are deleted to generate multiple second sub-temperature fields, which are added to the multiple temperature rise consistent monitoring regions. This process is repeated until all positions in the multiple temperature field segmentation results are traversed to generate the multiple temperature rise consistent monitoring regions.

[0008] In the implementation, determining whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index further includes: if not, calculating multiple temperature differences between the minimum and maximum temperatures of the plurality of first sub-temperature fields. Based on the multiple temperature differences, the plurality of first sub-temperature fields are arranged in descending order of temperature difference to generate a first sub-temperature field sequence. The plurality of first sub-temperature fields are sequentially deleted according to the first sub-temperature field sequence, and fluctuation consistency analysis is performed again until the newly obtained fluctuation consistency index is less than or equal to the preset fluctuation consistency index. The maximum field area of ​​the remaining sub-temperature fields is used as the first temperature rise consistency monitoring area.

[0009] In the implementation, temperature rise data analysis is performed on the air compressor used for laser cutting under various operating loads to generate multiple operating temperature fields. This includes: acquiring the structural composition of the air compressor used for laser cutting and performing network partitioning to generate an air compressor structure network; configuring multiple operating load scenarios for the air compressor used for laser cutting to generate multiple operating load samples; performing temperature rise tests based on the multiple operating load samples to generate multiple temperature rise test data; and mapping the multiple temperature rise test data to the air compressor structure network to generate the multiple operating temperature fields.

[0010] In the implementation method, a temperature control impact sensitivity analysis is performed on the multiple temperature rise consistent monitoring areas to generate multiple temperature control sensitivities. This includes: acquiring multiple reference operating temperatures for the multiple temperature rise consistent monitoring areas; using the multiple reference operating temperatures as centers, historical cooling control data and historical air compressor control impact levels under insufficient and excessive cooling conditions are analyzed according to a preset step size. The historical air compressor control impact level refers to the deviation between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperatures. Based on the historical air compressor control impact level, the multiple temperature control sensitivities are obtained.

[0011] In the implementation, liquid cooling channels are configured based on the multiple temperature control sensitivities to establish multiple liquid cooling systems. Then, temperature control models are constructed for the multiple temperature rise consistent monitoring areas. Establishing multiple temperature control models includes: uniformly distributing liquid cooling channels within the multiple temperature rise consistent monitoring areas to generate multiple initial liquid cooling systems, each initial liquid cooling system including a liquid cooling circulation channel and an electric valve. Multiple cooling test samples are collected within the multiple temperature rise consistent monitoring areas, and temperature control accuracy tests are performed on the multiple initial liquid cooling systems within the same area to generate multiple accuracy indicators. It is determined whether the multiple accuracy indicators meet the multiple temperature control sensitivities. For initial liquid cooling systems that do not meet the requirements, segmented loop optimization of the liquid cooling channels is performed to establish the multiple liquid cooling systems, and temperature control tests are conducted to train the multiple temperature control models.

[0012] This application also provides an adaptive cooling control device for an air compressor used in laser cutting, including: The monitoring module determination module is used to analyze the temperature rise data of the air compressor for laser cutting under various operating loads, establish multiple temperature rise consistent monitoring areas, and determine multiple temperature monitoring modules accordingly.

[0013] The temperature control sensitivity acquisition module is used to perform temperature control influence sensitivity analysis on the multiple temperature rise consistent monitoring areas and generate multiple temperature control sensitivities.

[0014] The temperature control model acquisition module is used to configure liquid cooling channels based on the multiple temperature control sensitivities, establish multiple liquid cooling systems, and then construct temperature control models for the multiple temperature rise consistent monitoring areas to establish multiple temperature control models.

[0015] The cooling control module is used to receive multiple temperature monitoring data through the multiple temperature monitoring modules and input them into the multiple temperature control models to generate cooling control parameters, and then perform cooling control through the multiple liquid cooling systems.

[0016] This application proposes an adaptive cooling control method and device for air compressors used in laser cutting. By analyzing temperature rise data under various operating loads, multiple temperature rise monitoring zones with consistent temperature rise are established, and corresponding temperature monitoring modules are determined. Sensitivity analysis of temperature control effects is performed on these monitoring zones, generating multiple temperature control sensitivities. Based on these sensitivities, liquid cooling channels are configured to establish multiple liquid cooling systems. Temperature control models are then constructed for the monitoring zones with consistent temperature rise, creating multiple temperature control models. Multiple temperature monitoring data are received by the multiple temperature monitoring modules and input into the multiple temperature control models to generate cooling control parameters. Cooling control is then implemented through the multiple liquid cooling systems. This method solves the technical problem in existing laser cutting air compressor cooling methods where adaptive adjustment based on different operating loads is difficult, resulting in poor temperature control accuracy and affecting equipment performance and efficiency. It achieves precise management of air compressor temperature, ensuring equipment operation within the optimal temperature range and improving the performance and efficiency of laser cutting. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the apparatus according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0018] Figure 1 A schematic flowchart of an adaptive cooling control method for an air compressor used for laser cutting, provided in an embodiment of this application. Figure 2 A schematic diagram of the adaptive cooling control device for a laser cutting air compressor provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached diagram: Module 11 for determining the monitoring module, Module 12 for acquiring temperature control sensitivity, Module 13 for acquiring temperature control model, and Module 14 for cooling control. Detailed Implementation

[0020] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or apparatuses. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0023] This application provides an adaptive cooling control method and apparatus for an air compressor used in laser cutting, such as... Figure 1 As shown, the method includes: Temperature rise data of air compressors used for laser cutting under various operating loads were analyzed to establish multiple temperature rise consistent monitoring zones, and corresponding temperature monitoring modules were determined. Sensitivity analysis of temperature control effects was performed on these multiple temperature rise consistent monitoring zones to generate multiple temperature control sensitivities.

[0024] In laser cutting equipment, the air compressor is a crucial auxiliary device, providing the necessary air pressure support for laser cutting. However, air compressors generate a large amount of heat when operating under high loads. If not cooled effectively and promptly, this can lead to decreased equipment performance, shortened lifespan, and even safety hazards. To ensure the equipment operates within its optimal temperature range, temperature rise data of the air compressor for laser cutting is collected under different operating loads. Operating load refers to the air compressor's operating status under various working conditions, such as different pressure settings, operating time, and ambient temperature. By simulating these conditions in the laboratory or actual working conditions, the temperature rise of various parts of the air compressor over time is obtained and analyzed, thereby establishing multiple temperature rise consistent monitoring zones. Temperature monitoring modules are then installed in these zones. Furthermore, a temperature control sensitivity analysis is performed on these multiple temperature rise consistent monitoring zones to generate multiple temperature control sensitivities.

[0025] The method provided in this application embodiment further includes: analyzing temperature rise data of the air compressor for laser cutting under various operating loads to generate multiple operating temperature fields; dividing the multiple operating temperature fields into regional temperature fields according to a preset temperature consistency deviation to generate multiple temperature field segmentation results; and performing temperature fluctuation analysis and fusion on the multiple temperature field segmentation results to generate the multiple temperature rise consistency monitoring areas.

[0026] This paper analyzes the temperature rise data of an air compressor used for laser cutting under various operating loads, establishing multiple temperature rise consistency monitoring areas. This includes acquiring temperature rise data of various parts of the air compressor under different operating loads over time, generating multiple operating temperature fields, each corresponding to a specific operating load. Subsequently, the multiple operating temperature fields are clustered and segmented according to a preset temperature consistency deviation. Based on the preset temperature consistency deviation, region clustering is used to group areas with similar temperatures together, generating multiple temperature field segmentation results. Specifically, during clustering, multiple randomly distributed initial cluster centers are first obtained. Regions within the preset temperature consistency deviation are then identified using these initial cluster centers as a reference, resulting in initial segmented regions. Subsequently, multiple partitioning points are randomly selected from non-initial segmented regions, and regions within the preset temperature consistency deviation are further identified using these partitioning points as a reference, resulting in segmented regions. This process of acquiring partitioning points and regions within the preset temperature consistency deviation continues until all regions are segmented. Finally, the finally obtained region centers are merged according to the preset temperature consistency deviation to obtain the temperature field segmentation results. The preset temperature consistency deviation is a pre-set maximum temperature deviation. When the temperature is less than this preset temperature consistency deviation, the temperature of the corresponding area and the temperature at the base point are considered to be consistent and can be classified as the same area. Conversely, if the temperature is greater than this preset deviation, the temperature is not considered consistent and the two areas do not belong to the same region. Finally, the multiple temperature field segmentation results are analyzed and fused to generate the multiple temperature rise consistency monitoring areas.

[0027] The method provided in this application embodiment further includes: taking an edge position of the air compressor for laser cutting as a base point, extracting multiple first sub-temperature fields starting from the base point from the multiple temperature field segmentation results. Performing fluctuation consistency analysis on the multiple first sub-temperature fields to generate a first fluctuation consistency index. Determining whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index; if so, taking the largest field area among the multiple first sub-temperature fields as a first temperature rise consistency monitoring area and adding it to the multiple temperature rise consistency monitoring areas. Continuing with the first temperature rise consistency monitoring area as the starting point, extracting the next sub-temperature field from the multiple temperature field segmentation results and deleting the overlapping positions with the first temperature rise consistency monitoring area to generate multiple second sub-temperature fields, and adding them to the multiple temperature rise consistency monitoring areas. This process continues until all positions in the multiple temperature field segmentation results are traversed to generate the multiple temperature rise consistency monitoring areas.

[0028] The multiple temperature field segmentation results are analyzed and fused to generate multiple temperature rise consistency monitoring areas. This includes: using an edge position of the air compressor used for laser cutting as a base point, where the base point is a grid near the edge in multiple operating temperature fields, multiple first sub-temperature fields starting from the base point are extracted from the multiple temperature field segmentation results. That is, the regions containing the base point in the multiple temperature field segmentation results are extracted as first sub-temperature fields. Subsequently, fluctuation consistency analysis is performed on the multiple first sub-temperature fields. During the fluctuation consistency analysis, the first sub-temperature field with the largest area is obtained. Using the first sub-temperature field with the largest area as the reference region, multiple overlapping regions where other first sub-temperature fields overlap with the reference region are obtained. The intersection of the overlapping regions is taken to obtain the common region. The difference between the reference region and the common region is obtained in the multiple first sub-temperature fields to obtain the non-common region in each temperature field. The average temperature rise per unit time is calculated for each non-common region, and the average temperature rise per unit time is obtained for all common regions. The difference between the average temperature rise per unit time in each non-common region and the average temperature rise per unit time in the common regions is calculated to generate the first fluctuation consistency index. Then, it is determined whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index. If so, the largest field area among the multiple first sub-temperature fields is taken as the first temperature rise consistency monitoring area and added to the multiple temperature rise consistency monitoring areas. The preset fluctuation consistency index is the maximum value of a preset temperature rise change difference. When it is greater than this value, the temperature rise change of the corresponding area differs significantly from the temperature rise of the original area, and therefore cannot be classified into the same area. Continuing from the first temperature rise consistency monitoring area as the starting point, the next sub-temperature field is extracted from the multiple temperature field segmentation results, and overlapping positions with the first temperature rise consistency monitoring area are deleted to generate multiple second sub-temperature fields, which are added to the multiple temperature rise consistency monitoring areas. This process is repeated until all positions in the multiple temperature field segmentation results are traversed to generate the multiple temperature rise consistency monitoring areas.

[0029] The method provided in this application embodiment further includes: if not, calculating multiple temperature differences between the minimum and maximum temperatures of the plurality of first sub-temperature fields. Based on the multiple temperature differences, arranging the plurality of first sub-temperature fields in descending order of temperature difference to generate a first sub-temperature field sequence. After sequentially deleting the plurality of first sub-temperature fields according to the first sub-temperature field sequence, performing fluctuation consistency analysis again until the newly obtained fluctuation consistency index is less than or equal to the preset fluctuation consistency index, and using the maximum field area of ​​the remaining sub-temperature fields as the first temperature rise consistency monitoring area.

[0030] When the first fluctuation consistency index is greater than the preset fluctuation consistency index, multiple temperature differences between the minimum and maximum temperatures of the plurality of first sub-temperature fields are calculated. Based on the multiple temperature differences, the plurality of first sub-temperature fields are arranged in descending order of temperature difference to generate a first sub-temperature field sequence. Further, the plurality of first sub-temperature fields are sequentially deleted according to the first sub-temperature field sequence, and fluctuation consistency analysis is re-performed. That is, the first sub-temperature field with the highest ranking is deleted according to the sorting, and fluctuation consistency analysis is continued on the remaining first sub-temperature fields after deletion, until the newly obtained fluctuation consistency index is less than or equal to the preset fluctuation consistency index. The maximum field area of ​​the remaining sub-temperature fields is taken as the first temperature rise consistency monitoring area.

[0031] The method provided in this application embodiment further includes: acquiring the structural composition of the air compressor for laser cutting and performing network partitioning to generate an air compressor structure network; configuring multiple operating loads for the air compressor for laser cutting to generate multiple operating load samples; performing temperature rise tests based on the multiple operating load samples to generate multiple temperature rise test data; and mapping the multiple temperature rise test data to the air compressor structure network to generate the multiple operating temperature fields.

[0032] This paper analyzes the temperature rise data of the air compressor used for laser cutting under various operating loads, generating multiple operating temperature fields. The process includes: acquiring the structural components of the air compressor and performing mesh generation; using professional simulation software to mesh the 3D model of the air compressor to generate a structural network; and configuring the air compressor's physical components and their connections, including the casing, motor, compressor head, radiator, piping, and control system. Subsequently, the air compressor is configured with multiple operating load scenarios to obtain its operating parameters under different working conditions, including operating pressure, flow rate, ambient temperature, and continuous operating time, generating multiple operating load samples. Further, temperature rise tests are conducted based on these multiple operating load samples, i.e., operating tests are performed on the multiple operating load samples under simulated or actual conditions to measure the temperature changes of each component of the air compressor during operation, generating multiple temperature rise test data. Finally, these multiple temperature rise test data are mapped to the air compressor structural network to generate the multiple operating temperature fields.

[0033] The method provided in this application embodiment further includes: acquiring multiple reference operating temperatures of the multiple temperature rise consistent monitoring areas. Using the multiple reference operating temperatures as centers, historical cooling control data and historical air compressor control influence levels under insufficient and excessive cooling conditions are analyzed according to a preset step size. The historical air compressor control influence level refers to the deviation between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperatures. Based on the historical air compressor control influence level, a temperature control accuracy with a control influence level less than a preset influence level is determined, and the multiple temperature control sensitivities are generated.

[0034] A temperature control sensitivity analysis is performed on the multiple temperature rise consistent monitoring areas to generate multiple temperature control sensitivities. This includes: acquiring multiple reference operating temperatures for the multiple temperature rise consistent monitoring areas, where the reference operating temperatures are the normal operating temperatures that ensure stable operation under the corresponding environments. Using these multiple reference operating temperatures as the center, historical cooling control data and historical air compressor control influence levels under insufficient and excessive cooling conditions are collected according to a preset step size. The historical cooling control data consists of the specific control parameters of the air compressor under different monitoring area temperatures. Insufficient cooling refers to monitoring area temperatures higher than the reference operating temperature, while excessive cooling refers to monitoring area temperatures lower than the reference operating temperature. The preset step size is a pre-set temperature acquisition amplitude used to collect historical cooling control data and historical air compressor control influence levels under insufficient and excessive cooling conditions within an amplitude greater than or equal to the reference operating temperature. The historical air compressor control influence level is defined as the deviation between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperature. Specifically, it is calculated by subtracting the ratio of the difference between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperature to the air compressor control parameters corresponding to the reference operating temperature. Since the preset step size is fixed, a larger deviation level indicates a higher similarity between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperature, resulting in higher control parameter sensitivity. Conversely, a smaller deviation level indicates a lower similarity between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperature, resulting in lower control parameter sensitivity. There is a one-to-one correspondence between the historical air compressor control influence level and temperature control sensitivity; a higher influence level corresponds to a higher temperature control sensitivity. This correspondence is a parameter preset by technicians. Based on the historical air compressor control influence level, multiple temperature control sensitivities are generated.

[0035] Based on the multiple temperature control sensitivities, liquid cooling channels are configured to establish multiple liquid cooling systems. Then, temperature control models are constructed for the multiple temperature rise monitoring areas, resulting in multiple temperature control models. Multiple temperature monitoring data are received by the multiple temperature monitoring modules and input into the multiple temperature control models to generate cooling control parameters. Finally, cooling control is performed through the multiple liquid cooling systems.

[0036] Based on the multiple temperature control sensitivities, liquid cooling channels are configured to establish multiple liquid cooling systems. The number of these systems is the same as the number of temperature rise consistent monitoring areas. Temperature control models are then constructed for each of these consistent monitoring areas, resulting in multiple temperature control models. Finally, multiple temperature monitoring modules receive multiple temperature monitoring data and input them into the multiple temperature control models. Combined with the target control temperature of the consistent temperature rise monitoring areas, cooling control parameters are generated, and these parameters are then used to control the cooling of the multiple liquid cooling systems.

[0037] The method provided in this application further includes: uniformly distributing liquid cooling channels in the multiple temperature rise consistent monitoring areas to generate multiple initial liquid cooling systems, each initial liquid cooling system including a liquid cooling circulation channel and an electric valve. Multiple cooling test samples are collected in the multiple temperature rise consistent monitoring areas, and temperature control accuracy tests are performed on the multiple initial liquid cooling systems within the same area to generate multiple accuracy indicators. It is determined whether the multiple accuracy indicators meet the multiple temperature control sensitivities; for initial liquid cooling systems that do not meet the requirements, segmented loop optimization of the liquid cooling channels is performed to establish the multiple liquid cooling systems, and temperature control tests are conducted to train the multiple temperature control models.

[0038] Based on the multiple temperature control sensitivities, liquid cooling channels are configured to establish multiple liquid cooling systems. Then, temperature control models are constructed for the multiple temperature rise consistent monitoring areas. These models include: uniformly distributing liquid cooling channels within the multiple temperature rise consistent monitoring areas to generate multiple initial liquid cooling systems. Each initial liquid cooling system includes a liquid cooling circulation channel and an electric valve. Subsequently, multiple cooling test samples are collected within the multiple temperature rise consistent monitoring areas, i.e., obtaining the sample operating temperatures of the multiple temperature rise consistent monitoring areas during historical operation. These multiple cooling test samples include initial temperatures and target control temperatures. Based on the multiple cooling test samples, temperature control accuracy tests are conducted within the same area using the multiple initial liquid cooling systems. During the temperature control accuracy test, the final control temperatures of the multiple initial liquid cooling systems under the multiple cooling test samples are obtained at a preset time. The temperature difference between the final control temperature and the target control temperature is obtained. The ratio of 1 to the temperature difference between the initial temperature and the target control temperature is calculated to generate multiple accuracy indicators. Furthermore, it is determined whether the multiple accuracy indicators meet the requirements (i.e., are greater than or equal to the multiple temperature control sensitivities). For initial liquid cooling systems that do not meet the requirements (i.e., are less than the temperature control sensitivities), segmented loop optimization of the liquid cooling channel is performed, dividing the original single liquid cooling channel into multiple loop segments, such as a dual-loop channel, to establish the multiple liquid cooling systems. After completing the multiple liquid cooling systems, temperature control testing is conducted, testing the control parameters controlled to the target temperature at different initial temperatures, and obtaining training data sets. Each training data set contains the initial control temperature, the target control temperature, and the corresponding liquid cooling control parameters under the liquid cooling system. Based on the training data sets, the neural network model is subjected to supervised training until the accuracy of the liquid cooling control parameters output by the model finally meets the requirements, thus obtaining multiple temperature control models. The number of multiple temperature control models is the same as the number of liquid cooling systems.

[0039] In the above text, refer to Figure 1 An adaptive cooling control method for an air compressor used in laser cutting according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 An adaptive cooling control device for an air compressor for laser cutting according to an embodiment of the present invention is described.

[0040] The adaptive cooling control device for a laser-cutting air compressor according to an embodiment of the present invention solves the technical problem in the prior art where the cooling method for laser-cutting air compressors is difficult to adaptively adjust based on different operating loads, resulting in poor temperature control accuracy and affecting equipment performance and efficiency. It achieves precise management of the air compressor temperature, ensuring the equipment operates within the optimal temperature range, thus improving the performance and efficiency of laser cutting. The adaptive cooling control device for a laser-cutting air compressor includes: a monitoring module determination module 11, a temperature control sensitivity acquisition module 12, a temperature control model acquisition module 13, and a cooling control module 14.

[0041] The monitoring module determination module 11 is used to analyze the temperature rise data of the air compressor for laser cutting under various operating loads, establish multiple temperature rise consistent monitoring areas, and determine multiple temperature monitoring modules accordingly.

[0042] The temperature control sensitivity acquisition module 12 is used to perform temperature control influence sensitivity analysis on the multiple temperature rise consistent monitoring areas and generate multiple temperature control sensitivities.

[0043] The temperature control model acquisition module 13 is used to configure liquid cooling channels based on the multiple temperature control sensitivities, establish multiple liquid cooling systems, and then construct temperature control models for the multiple temperature rise consistent monitoring areas to establish multiple temperature control models.

[0044] The cooling control module 14 is used to receive multiple temperature monitoring data through the multiple temperature monitoring modules and input them into the multiple temperature control models to generate cooling control parameters, and then perform cooling control through the multiple liquid cooling systems.

[0045] The specific configuration of the monitoring module determination module 11 will be described in detail below. The monitoring module determination module 11 may further include: analyzing temperature rise data under various operating loads for the air compressor used for laser cutting, and establishing multiple temperature rise consistent monitoring areas, including: analyzing temperature rise data under various operating loads for the air compressor used for laser cutting, generating multiple operating temperature fields; dividing the multiple operating temperature fields into regional temperature fields according to a preset temperature consistency deviation, generating multiple temperature field segmentation results; and performing temperature fluctuation analysis and fusion on the multiple temperature field segmentation results to generate the multiple temperature rise consistent monitoring areas.

[0046] The specific configuration of the monitoring module determination module 11 will be described in detail below. The monitoring module determination module 11 may further include: performing temperature fluctuation analysis and fusion on the multiple temperature field segmentation results to generate the multiple temperature rise consistent monitoring areas, including: taking an edge position of the laser cutting air compressor as a base point, extracting multiple first sub-temperature fields starting from the base point from the multiple temperature field segmentation results. Performing fluctuation consistency analysis on the multiple first sub-temperature fields to generate a first fluctuation consistency index. Determining whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index; if so, taking the largest field area among the multiple first sub-temperature fields as the first temperature rise consistent monitoring area and adding it to the multiple temperature rise consistent monitoring areas. Continuing with the first temperature rise consistent monitoring area as the starting point, extracting the next sub-temperature field from the multiple temperature field segmentation results and deleting the overlapping positions with the first temperature rise consistent monitoring area to generate multiple second sub-temperature fields and adding them to the multiple temperature rise consistent monitoring areas. This process continues until all positions in the multiple temperature field segmentation results are traversed to generate the multiple temperature rise consistent monitoring areas.

[0047] The specific configuration of the monitoring module determination module 11 will be described in detail below. The monitoring module determination module 11 further includes: determining whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index; and further including: if not, calculating multiple temperature differences between the minimum and maximum temperatures of the multiple first sub-temperature fields. Based on the multiple temperature differences, the multiple first sub-temperature fields are arranged in descending order of temperature difference to generate a first sub-temperature field sequence. The multiple first sub-temperature fields are sequentially deleted according to the first sub-temperature field sequence, and fluctuation consistency analysis is performed again until the newly obtained fluctuation consistency index is less than or equal to the preset fluctuation consistency index. The maximum field area of ​​the remaining sub-temperature fields is used as the first temperature rise consistency monitoring area.

[0048] The specific configuration of the monitoring module determination module 11 will be described in detail below. The monitoring module determination module 11 further includes: analyzing temperature rise data under various operating loads for the air compressor used for laser cutting, generating multiple operating temperature fields, including: acquiring the structural composition of the air compressor used for laser cutting and performing network partitioning to generate an air compressor structure network; configuring multiple operating load scenarios for the air compressor used for laser cutting to generate multiple operating load samples; performing temperature rise tests based on the multiple operating load samples to generate multiple temperature rise test data; and mapping the multiple temperature rise test data to the air compressor structure network to generate the multiple operating temperature fields.

[0049] The specific configuration of the temperature control sensitivity acquisition module 12 will be described in detail below. The temperature control sensitivity acquisition module 12 further includes: performing temperature control influence sensitivity analysis on the multiple temperature rise consistent monitoring areas to generate multiple temperature control sensitivities, including: acquiring multiple reference operating temperatures of the multiple temperature rise consistent monitoring areas. Centered on the multiple reference operating temperatures, historical cooling control data and historical air compressor control influence levels under insufficient and excessive cooling conditions are collected according to a preset step size. The historical air compressor control influence level refers to the deviation between the air compressor control parameters under insufficient and excessive cooling conditions and the air compressor control parameters corresponding to the reference operating temperatures. Based on the historical air compressor control influence level, the multiple temperature control sensitivities are acquired.

[0050] The specific configuration of the temperature control model acquisition module 13 will be described in detail below. The temperature control model acquisition module 13 further includes: configuring liquid cooling channels based on the multiple temperature control sensitivities to establish multiple liquid cooling systems; then constructing temperature control models for the multiple temperature rise consistent monitoring areas; establishing multiple temperature control models includes: uniformly distributing liquid cooling channels in the multiple temperature rise consistent monitoring areas to generate multiple initial liquid cooling systems, each initial liquid cooling system including a liquid cooling circulation channel and an electric valve; collecting multiple cooling test samples in the multiple temperature rise consistent monitoring areas; conducting temperature control accuracy tests within the same area using the multiple initial liquid cooling systems to generate multiple accuracy indicators; determining whether the multiple accuracy indicators meet the multiple temperature control sensitivities; for initial liquid cooling systems that do not meet the requirements, performing segmented loop optimization of the liquid cooling channels; establishing the multiple liquid cooling systems; conducting temperature control tests; and training the multiple temperature control models.

[0051] The adaptive cooling control device for the air compressor used for laser cutting provided in this embodiment of the invention can execute the adaptive cooling control method for the air compressor used for laser cutting provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0052] While this application makes various references to certain modules in the apparatus according to embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved. In addition, the specific names of each functional unit are only for easy distinction and are not intended to limit the scope of protection of this invention.

[0053] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An adaptive cooling control method of an air compressor for laser cutting, characterized by, Comprise: Temperature rise data analysis of air compressors for laser cutting under various work loads, establishment of multiple temperature rise consistent monitoring areas, and corresponding determination of multiple temperature monitoring modules; Temperature control influence sensitivity analysis of the multiple temperature rise consistent monitoring areas, generating multiple temperature control sensitivities; Based on the multiple temperature control sensitivities, configure liquid cooling channels, establish multiple liquid cooling devices, and build temperature control models for the multiple temperature rise consistent monitoring areas, establishing multiple temperature control models; Through the multiple temperature monitoring modules, receive multiple temperature monitoring data and input the multiple temperature control models to generate cooling control parameters, and then through the multiple liquid cooling devices, perform cooling control.

2. The adaptive cooling control method of an air compressor for laser cutting according to claim 1, wherein, Temperature rise data analysis of air compressors for laser cutting under various work loads, establishment of multiple temperature rise consistent monitoring areas, comprising: Temperature rise data analysis of the air compressors for laser cutting under various work loads, generating multiple work temperature fields; According to the preset temperature consistent deviation, divide the multiple work temperature fields into regional temperature fields, generating multiple temperature field segmentation results; Temperature fluctuation analysis and fusion of the multiple temperature field segmentation results, generating the multiple temperature rise consistent monitoring areas.

3. The adaptive cooling control method of an air compressor for laser cutting according to claim 2, wherein Temperature fluctuation analysis and fusion of the multiple temperature field segmentation results, generating the multiple temperature rise consistent monitoring areas, comprising: Taking an edge position of the air compressor for laser cutting as a base point, extracting multiple first sub-temperature fields from the base point in the multiple temperature field segmentation results; Conducting fluctuation consistency analysis on the multiple first sub-temperature fields, generating a first fluctuation consistency index; Determine whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index, if yes, take the largest field area in the multiple first sub-temperature fields as a first temperature rise consistent monitoring area and add it to the multiple temperature rise consistent monitoring areas; Continue to take the first temperature rise consistent monitoring area as the starting point, extract the next sub-temperature field from the multiple temperature field segmentation results and delete the overlapping position with the first temperature rise consistent monitoring area, generate multiple second sub-temperature fields and add them to the multiple temperature rise consistent monitoring areas; In this way, until all positions in the multiple temperature field segmentation results are traversed, the multiple temperature rise consistent monitoring areas are generated.

4. The adaptive cooling control method of an air compressor for laser cutting according to claim 3, wherein Determine whether the first fluctuation consistency index is less than or equal to a preset fluctuation consistency index, also comprising: If not, calculate multiple temperature difference values between the minimum temperature and the maximum temperature of the multiple first sub-temperature fields; Based on the multiple temperature difference values, arrange the multiple first sub-temperature fields in descending order of temperature difference value, generating a first sub-temperature field sequence; According to the first sub-temperature field sequence, delete the multiple first sub-temperature fields in turn and then conduct fluctuation consistency analysis again, until the re-obtained fluctuation consistency index is less than or equal to the preset fluctuation consistency index, take the largest field area of the remaining sub-temperature fields as the first temperature rise consistent monitoring area.

5. The adaptive cooling control method of an air compressor for laser cutting according to claim 2, wherein Temperature rise data analysis of the air compressors for laser cutting under various work loads, generating multiple work temperature fields, comprising: Obtaining the structural composition of the laser cutting air compressor and performing network partitioning to generate an air compressor structure network; Performing multi-scenario job load configuration on the laser cutting air compressor to generate multiple job load samples; Based on the multiple job load samples, performing temperature rise testing to generate multiple temperature rise test data; Mapping the multiple temperature rise test data to the air compressor structure network to generate multiple job temperature fields.

6. The adaptive cooling control method of an air compressor for laser cutting according to claim 1, wherein, Performing temperature control influence sensitivity analysis on the multiple temperature rise consistent monitoring areas to generate multiple temperature control sensitivities, including: Obtaining multiple baseline operating temperatures of the multiple temperature rise consistent monitoring areas; Centering on the multiple baseline operating temperatures, performing historical temperature control data and historical air compressor control influence degree under insufficient cooling and excessive cooling according to a preset step size, wherein the historical air compressor control influence degree is the deviation degree between the air compressor control parameters under insufficient cooling and excessive cooling and the air compressor control parameters corresponding to the baseline operating temperature; Based on the historical air compressor control influence degree, obtaining the multiple temperature control sensitivities.

7. The adaptive cooling control method of an air compressor for laser cutting according to claim 6, wherein Based on the multiple temperature control sensitivities, performing liquid cooling channel configuration to establish multiple liquid cooling devices, and then constructing temperature control models for the multiple temperature rise consistent monitoring areas to establish multiple temperature control models, including: Uniformly distributing liquid cooling channels in the multiple temperature rise consistent monitoring areas to generate multiple initial liquid cooling devices, any initial liquid cooling device including one liquid cooling circulation channel and one electric valve; Collecting multiple cooling test samples in the multiple temperature rise consistent monitoring areas, and performing temperature control precision testing in the same area with the multiple initial liquid cooling devices to generate multiple precision indicators; Determining whether the multiple precision indicators meet the multiple temperature control sensitivities, and for initial liquid cooling devices that do not meet the requirements, performing liquid cooling channel segmentation and circulation optimization to establish the multiple liquid cooling devices and perform temperature control testing to train the multiple temperature control models.

8. An adaptive cooling control device for an air compressor for laser cutting, characterized by, Including: The monitoring module determination module is used for temperature rise data analysis of the laser cutting air compressor under multiple job loads, establishment of multiple temperature rise consistent monitoring areas, and corresponding determination of multiple temperature monitoring modules; The temperature control sensitivity acquisition module is used for temperature control influence sensitivity analysis of the multiple temperature rise consistent monitoring areas to generate multiple temperature control sensitivities; The temperature control model acquisition module is used for liquid cooling channel configuration based on the multiple temperature control sensitivities to establish multiple liquid cooling devices, and then constructing temperature control models for the multiple temperature rise consistent monitoring areas to establish multiple temperature control models; The cooling control module is used for receiving multiple temperature monitoring data through the multiple temperature monitoring modules and inputting the multiple temperature control models to generate cooling control parameters, and then performing cooling control through the multiple liquid cooling devices.

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