Automatic constant pressure method, device, equipment and storage medium

Abstract

The present application discloses an automatic constant pressure method, device, equipment and storage medium, wherein the automatic constant pressure method comprises: obtaining a target pressure value through a human-machine interface, and obtaining an actual pressure value through a pressure sensor; based on the actual pressure value, adaptively learning the PID algorithm parameters, and obtaining a first analog voltage for controlling the frequency of the frequency converter; according to the first analog voltage, controlling the speed of the water pump so that the water pump reaches the first pressure value; if the first pressure value does not meet the target pressure value, repeating the steps of adaptively learning the PID algorithm parameters based on the actual pressure value, and obtaining the first analog voltage for controlling the frequency of the frequency converter, until the first pressure value meets the target pressure value. This method can quickly and accurately reach the set target pressure value, and the pressure adjustment time is short, reducing the workload of the staff.

Description

Technical Field

[0001] The present invention relates to the field of automatic etching technology, and in particular to an automatic constant pressure method, device, equipment and storage medium. Background Art

[0002] When the developer and etcher are performing wet processing on the circuit board, the automatic constant pressure function of the developer and etcher is used for real-time adjustment, automatic constant and precise control of the spray pressure.

[0003] In the existing automatic constant pressure function, PID (Proportional Integral Differential) control debugging is cumbersome, requiring the operator to set PID parameters based on experience and make multiple adjustments, resulting in a long pressure adjustment time and an inability to quickly and accurately reach the set pressure value, resulting in low adjustment efficiency and reduced production efficiency. Summary of the invention

[0004] The embodiments of the present invention provide an automatic constant pressure method, device, equipment and storage medium to solve the problem that PID control debugging is cumbersome, the operator needs to set PID parameters based on experience, and make multiple adjustments, which results in a long pressure adjustment time, and the set pressure value cannot be reached quickly and accurately, resulting in low adjustment efficiency and reduced production efficiency.

[0005] The present application provides an automatic constant pressure method, the method comprising:

[0006] Obtain the target pressure value through the human-machine interface and obtain the actual pressure value through the pressure sensor;

[0007] Based on the actual pressure value, adaptive learning is performed on the PID algorithm parameters to obtain a first analog voltage for controlling the frequency of the frequency converter;

[0008] According to the first analog voltage, the speed of the water pump is controlled so that the water pump reaches a first pressure value;

[0009] If the first pressure value does not meet the target pressure value, the steps of obtaining the actual pressure value through the pressure sensor, adaptively learning the PID algorithm parameters based on the actual pressure value, and obtaining the first analog voltage for controlling the frequency of the inverter are repeated until the first pressure value meets the target pressure value.

[0010] The present application provides an automatic constant pressure device, the device comprising:

[0011] The actual pressure value acquisition module is used to obtain the target pressure value through the human-machine interface and obtain the actual pressure value through the pressure sensor;

[0012] An adaptive learning module, used for adaptively learning PID algorithm parameters based on actual pressure value, and obtaining a first analog voltage for controlling the frequency of the frequency converter;

[0013] A water pump speed control module, used for controlling the water pump speed according to the first analog voltage so that the actual pressure value reaches the first pressure value;

[0014] The repeated execution module is used to repeatedly execute the steps of obtaining the actual pressure value through the pressure sensor and adaptively learning the PID algorithm parameters based on the actual pressure value to obtain the first analog voltage for controlling the frequency of the inverter if the first pressure value does not meet the target pressure value, until the first pressure value meets the target pressure value.

[0015] In some embodiments, the adaptive learning module is further used to: obtain actual algorithm parameters of the PID algorithm in real time; and adaptively learn the PID algorithm based on the initial algorithm parameters and the actual algorithm parameters to generate a first analog voltage of the inverter frequency.

[0016] In some embodiments, the adaptive learning module is also used to: obtain the deviation and the deviation change rate based on the initial algorithm parameters and the actual algorithm parameters; set the rule base based on the parameter relationship between the deviation, the deviation change rate and the PID algorithm parameters; repeatedly execute the PID algorithm to correct the detection deviation and the deviation change rate so that the detection deviation and the deviation change rate activate the parameter relationship rules in the rule base; and output the first analog voltage based on the parameter relationship rules.

[0017] In some embodiments, the device is further used to: acquire image information of the spraying object in real time; and numerically adjust the spraying parameters of the nozzle based on the image information.

[0018] In some embodiments, the device is further used to: obtain an optimal pressure value and a target parameter in the solution tank; obtain a first pressure value based on the target parameter; and compare and analyze the optimal pressure value and the first pressure value to obtain the optimal target parameter.

[0019] In some embodiments, the device is also used to: use the optimal pressure value, the first pressure value and the target parameter as input parameters of the model, train the deep learning model, and output the optimal target parameter; adjust the target parameter based on the optimal target parameter; and generate an optimal pressure value-optimal target parameter data table based on the optimal pressure value and the optimal target parameter.

[0020] In some embodiments, the device is further used to: detect changes in the first pressure value in real time to determine whether to output abnormal data; if so, obtain an abnormal data report based on the abnormal data and send an alarm signal.

[0021] The present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned automatic constant pressure method when executing the computer program.

[0022] The present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned automatic constant pressure method is implemented.

[0023] The above-mentioned automatic constant pressure method, device, equipment and storage medium obtain the target pressure value and the actual pressure value, and achieve constant pressure when the actual pressure value approaches and satisfies the target pressure value as the first pressure value through adaptive learning of PID algorithm parameters. In this way, the target pressure value is automatically collected and the self-learning algorithm is automatically adjusted, so that the set target pressure value can be reached quickly and accurately, and the pressure adjustment time is short, reducing the workload of the staff. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0025] Figure 1 A first flow chart of an automatic constant pressure method according to an embodiment of the present invention is shown;

[0026] Figure 2 A second flow chart of the automatic constant pressure method according to an embodiment of the present invention is shown;

[0027] Figure 3 A block diagram of a model for adaptive learning of an automatic constant pressure method according to an embodiment of the present invention is shown;

[0028] Figure 4 A schematic diagram of an automatic constant pressure device according to an embodiment of the present invention is shown;

[0029] Figure 5 A schematic diagram of an electronic device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] In one embodiment, if Figure 1 As shown, an automatic constant pressure method is provided, which specifically includes the following steps:

[0032] S10. Obtain a target pressure value through a human-machine interface, and obtain an actual pressure value through a pressure sensor.

[0033] Among them, in this embodiment, the human-machine interface (HMI) can be an interface of an input / output device for establishing contact and exchanging information between a person and a computer. The control center of the method can be a programmable logic controller (PLC), and the human-machine interface and the pressure sensor are electrically connected to the programmable logic controller. The programmable controller includes an analog input module and an analog output module for inputting and outputting data. The human-machine interface can be made by the software GP-PROEX.

[0034] Specifically, when a developing machine or etching machine performs a wet process on a circuit board, the circuit board or the circuit board is immersed in the solution tank of the developing machine, and unnecessary impurities on the circuit board are etched or corroded by applying pressure to the nozzle on the pipeline and spraying the circuit board. Different products have different pressure values. The target pressure value is obtained, and the programmable controller (PLC) collects the actual pressure value from the sensor through the analog input module. The etched products of this method include but are not limited to circuit board products.

[0035] S20. Based on the actual pressure value, adaptively learn the PID algorithm parameters to obtain a first analog voltage for controlling the frequency of the inverter.

[0036] In this embodiment, the PID (Proportion Integral Differential) algorithm can be used to perform calculations according to the functional relationship of proportion, integration and differentiation based on the input deviation value, and the calculation result is used to control the output. The programmable controller is electrically connected to the frequency converter. The first analog voltage is output through the analog output module of the programmable controller.

[0037] Specifically, the PID algorithm is input into the programmable controller, and the PID algorithm parameters are controlled to perform adaptive learning through the actual pressure value to obtain the first analog voltage, which is used to control the frequency of the frequency converter. The output range of the first analog voltage can be 0 to 10 volts, and each volt can correspond to a different frequency of the frequency converter.

[0038] S30. According to the first analog voltage, control the rotation speed of the water pump so that the actual pressure value reaches the first pressure value.

[0039] In this embodiment, the frequency converter is electrically connected to the water pump.

[0040] Specifically, the first analog voltage controls the frequency of the frequency converter to change, and the frequency converter controls the motor speed of the water pump to change the actual pressure value, and the pressure value of the intermediate change is called the first pressure value. The process of this method is mostly a process in which the first pressure value increases continuously.

[0041] S40. If the first pressure value does not meet the target pressure value, repeat the step of adaptively learning the PID algorithm parameters based on the actual pressure value to obtain the first analog voltage for controlling the frequency of the inverter until the first pressure value meets the target pressure value.

[0042] Specifically, in this embodiment, the first pressure value is compared with the target pressure value. If the first pressure value is not equal to the target pressure value, the first pressure value (actual pressure value) is obtained in real time through the pressure sensor and fed back to the programmable controller. The programmable controller performs adaptive learning on the PID algorithm parameters again, obtains the first analog voltage used to control the frequency of the inverter, and repeats the process until the first pressure value is equal to the target pressure value, at which time the pressure is constant. This process does not require the operator to adjust the PID algorithm parameters multiple times, and multiple adjustments take a long time.

[0043] The above-mentioned automatic constant pressure method obtains the target pressure value and the actual pressure value, and achieves constant pressure when the actual pressure value as the first pressure value approaches and meets the target pressure value through adaptive learning of the PID algorithm parameters. In this way, the target pressure value is automatically collected and the self-learning algorithm is automatically adjusted, so that the set target pressure value can be reached quickly and accurately, and the pressure adjustment time is short, reducing the workload of the staff.

[0044] In some embodiments, such as Figure 2 As shown, in step S20, the PID algorithm parameters are adaptively learned to obtain the first analog voltage for controlling the frequency of the inverter, which specifically includes the following steps:

[0045] S201. Obtain actual algorithm parameters of the PID algorithm in real time.

[0046] S202. Based on the initial algorithm parameters and the actual algorithm parameters, adaptively learn the PID algorithm to generate a first analog voltage of the inverter frequency.

[0047] Specifically, the initial PID algorithm parameters are obtained, and the PID algorithm parameters include proportional parameters, integral parameters and differential parameters, which are used to perform closed-loop adjustment on the PID. The actual algorithm parameters of the PID algorithm are collected through a programmable controller, and the PID algorithm is adaptively learned. The programmable controller autonomously gives the optimal proportional parameter, optimal integral parameter and optimal differential parameter at the current moment. Through the optimal proportional parameter, optimal integral parameter and optimal differential parameter, a first analog voltage is output, and the first analog voltage is used to control the frequency of the inverter.

[0048] The role of steps S201 to S202 is to adaptively learn the PID algorithm based on the initial algorithm parameters and the actual algorithm parameters, so that the output results are more accurate and faster, and there is no need to manually adjust the parameters.

[0049] In some embodiments, such as Figure 2 As shown, in step S202, the PID algorithm is adaptively learned based on the initial algorithm parameters and the actual algorithm parameters to generate the first analog voltage of the inverter frequency, which specifically includes the following steps:

[0050] S2021. Based on the initial algorithm parameters and the actual algorithm parameters, obtain the deviation and the deviation change rate.

[0051] S2022. Based on the deviation, deviation change rate and parameter relationship of PID algorithm parameters, set a rule base; repeatedly execute the PID algorithm to correct the detection deviation and deviation change rate so that the detection deviation and deviation change rate activate the parameter relationship rules in the rule base.

[0052] S2023. Based on the parameter relationship rule, output a first analog voltage.

[0053] Specifically, adaptive learning is used to adjust the PID algorithm parameters in the programmable controller. According to the algorithmic relationship between the deviation and the deviation change rate and the three parameters, a rule base is formulated. In the automatic constant pressure operation, the detection deviation and the deviation change rate are corrected, reasoning is performed, the corresponding parameter relationship rules are activated, and then the model is solved and the output control quantity Kp / Ki / Kd is output, which corresponds to the optimal proportional parameter, the optimal integral parameter and the optimal differential parameter respectively. Figure 3 shown.

[0054] In addition, the essence of PID self-learning is to use the characteristics of the controller to correct the characteristics of the object, so that the roots of the characteristic equation of the entire control system all fall within a certain range of the root plane, meeting the requirements of stability, speed and accuracy.

[0055] The purpose of steps S2021 to S2023 is to address the shortcoming that PID parameters are difficult to adjust in automatic constant pressure. This method can make PID algorithm parameters easy to adjust, have good control effect, and have strong versatility and adaptability.

[0056] In some embodiments, such as Figure 2 As shown, an automatic constant pressure method further includes the following steps:

[0057] S50. Acquire image information of the spraying object in real time.

[0058] S60. Based on the image information, numerically adjust the spraying parameters of the nozzle.

[0059] The image information may include the shape of the spray object, the thickness of impurities, color and texture, etc. The spray parameters include the spray pressure, spray amount and the number of nozzles, etc.

[0060] Specifically, during the spraying process of the spray object, the image information of the spray object is obtained through the camera, and the etching degree on the spray object is analyzed. Based on the etching degree, the spray parameters are numerically adjusted. For example, if the etching in a certain area on the spray object has been completed, but the etching in other areas has not been completed, the programmable controller controls to close the corresponding nozzle area where the etching has been completed.

[0061] The purpose of steps S50 to S60 is to obtain image information in real time, so as to save resources and costs.

[0062] In some embodiments, such as Figure 2 As shown, an automatic constant pressure method further includes the following steps:

[0063] S70. Obtain the optimal pressure value and target parameters in the solution tank.

[0064] S80. Based on the target parameter, obtain a first pressure value.

[0065] S90. Compare and analyze the optimal pressure value and the first pressure value to obtain the optimal target parameter.

[0066] The optimal pressure value may be a set target pressure value. The target parameters include the temperature in the solution tank, the concentration of the solution content, and the volume of the solution.

[0067] Specifically, other sensors are used to sense the solution in the surrounding solution box to obtain the temperature, solution content concentration, and solution volume in the solution box. At the same time, the first pressure value can be obtained through the pressure sensor. At this time, the target parameter corresponds to the first pressure value, and the optimal target parameter and the optimal pressure value can also correspond. When the optimal pressure value is obtained, the corresponding optimal target parameter is obtained. The optimal target parameter is stored and updated.

[0068] The purpose of steps S70 to S90 is to reduce the influence of the external environment on the automatic constant function and obtain the optimal target parameters based on the influence.

[0069] In some embodiments, such as Figure 2 As shown, in step S90, the optimal pressure value and the first pressure value are compared and analyzed to obtain the optimal target parameter, which specifically includes the following steps:

[0070] S901. Use the optimal pressure value, the first pressure value and the target parameter as the input parameters of the model, train the deep learning model, and output the optimal target parameter.

[0071] S902. Adjust the target parameters based on the optimal target parameters.

[0072] S903. Generate an optimal pressure value-optimal target parameter data table based on the optimal pressure value and the optimal target parameter.

[0073] Among them, deep learning is to learn the inherent laws and representation levels of sample data. The information obtained in the learning process enables the machine to have analytical learning capabilities like humans, and can recognize and analyze data such as text, images and sounds. Spraying graphic information can provide images and image data information with better spraying effects for spraying robots.

[0074] Specifically, a large number of optimal pressure values, first pressure values, and target parameters are obtained from the database to build a model, the first pressure value and the target parameter are trained, and the intermediate target parameters are iteratively updated to obtain the error loss value between the intermediate target parameter and the corresponding optimal target parameter. When the error loss value converges to a certain extent, that is, when the intermediate target parameter is approximately the same as or the same as the corresponding optimal target parameter, the corresponding optimal target parameter is obtained. According to the target parameters and the optimal target parameters, a target parameter-optimal target parameter data table is generated for subsequent data acquisition and storage. By obtaining the data in the target parameter-optimal spraying parameter data table and subsequently using it to adjust the target parameters, the spraying effect is better and avoids being greatly affected by the external environment.

[0075] The purpose of steps S901 to S903 is to reduce the impact of target parameters on the spraying effect, and to learn through a deep learning model to achieve a better spraying effect, reduce spraying time and save resource costs.

[0076] In some embodiments, such as Figure 2 As shown, an automatic constant pressure method further includes the following steps:

[0077] S91. Detect changes in the first pressure value in real time to determine whether to output abnormal data.

[0078] S92. If yes, based on the abnormal data, obtain an abnormal data report and send an alarm signal.

[0079] Among them, abnormal data include sudden drops, sudden increases, and pressure slopes that are slower or faster than normal.

[0080] Specifically, the method detects the change of the first pressure value in real time, determines the output abnormal data and abnormal data type, and outputs the abnormal data and abnormal data type to the human-machine interface for the abnormal data report. Based on the abnormal data report, the specific error location can be obtained. For example: the spray pressure control at the spraying place is unstable, the water pump structure performance is abnormal, etc. After obtaining the abnormal data report, the work is stopped and an alarm signal is sent for subsequent operations.

[0081] The purpose of steps S91 to S92 is that the method can detect abnormal data in a timely manner and obtain the corresponding abnormal position through the abnormal data report, so as to quickly find the vulnerability.

[0082] The above-mentioned automatic constant pressure method obtains the target pressure value and the actual pressure value, and achieves constant pressure when the actual pressure value as the first pressure value approaches and meets the target pressure value through adaptive learning of the PID algorithm parameters. In this way, the target pressure value is automatically collected and the self-learning algorithm is automatically adjusted, so that the set target pressure value can be reached quickly and accurately, and the pressure adjustment time is short, reducing the workload of the staff.

[0083] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0084] In one embodiment, an automatic constant pressure device is provided, which corresponds one-to-one with the automatic constant pressure method in the above embodiment. Figure 4 As shown, the automatic constant pressure device includes an actual pressure value acquisition module 10, an adaptive learning module 20, a water pump speed control module 30 and a repeated execution module 40. The functional modules are described in detail as follows:

[0085] The actual pressure value acquisition module 10 is used to acquire the target pressure value through the human-machine interface and acquire the actual pressure value through the pressure sensor;

[0086] An adaptive learning module 20, used to adaptively learn PID algorithm parameters based on the actual pressure value, and obtain a first analog voltage for controlling the frequency of the frequency converter;

[0087] A water pump speed control module 30, used to control the water pump speed according to the first analog voltage so that the water pump reaches a first pressure value;

[0088] The module 40 is repeatedly executed, and is used to repeatedly execute the steps of obtaining the actual pressure value through the pressure sensor and adaptively learning the PID algorithm parameters based on the actual pressure value to obtain the first analog voltage for controlling the frequency of the inverter if the first pressure value does not meet the target pressure value, until the first pressure value meets the target pressure value.

[0089] The specific definition of the automatic constant pressure device can be found in the definition of the automatic constant pressure method above, which will not be repeated here. Each module in the above-mentioned automatic constant pressure device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0090] In one embodiment, an electronic device is provided. The electronic device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The electronic device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used for data related to the automatic constant pressure method. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, an automatic constant pressure method is implemented.

[0091] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the automatic constant pressure method of the above embodiment is implemented, for example Figure 1 Alternatively, when the processor executes the computer program, the functions of each module / unit of the automatic constant pressure device in the above embodiment are realized, for example Figure 4The functions of the modules 10 to 40 are shown in Figure 1. To avoid repetition, they will not be described in detail here.

[0092] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the automatic constant pressure method of the above embodiment is implemented, for example Figure 1 Alternatively, when the computer program is executed by the processor, the functions of each module / unit in the automatic constant pressure device in the above device embodiment are realized, for example Figure 4 The functions of the modules 10 to 40 are shown in Figure 1. To avoid repetition, they will not be described in detail here.

[0093] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments of the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0094] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0095] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. An automatic constant pressure method, characterized in that: include: Obtain the target pressure value through the human-machine interface; And obtain the actual pressure value through the pressure sensor; Based on the actual pressure value, adaptive learning is performed on the PID algorithm parameters to obtain a first analog voltage for controlling the frequency of the frequency converter, including: obtaining the actual algorithm parameters of the PID algorithm in real time; obtaining the deviation and the deviation change rate based on the initial algorithm parameters and the actual algorithm parameters; setting a rule base based on the deviation, the deviation change rate and the parameter relationship of the PID algorithm; repeatedly executing the PID algorithm to correct and detect the deviation and the deviation change rate so that the deviation and the deviation change rate activate the parameter relationship rules in the rule base; outputting the first analog voltage based on the parameter relationship rules; the first analog voltage is used to control the frequency of the frequency converter, and the output range of the first analog voltage is 0 to 10 volts, and each volt corresponds to a different frequency of the frequency converter; the frequency converter is electrically connected to the water pump; the frequency converter can control the motor speed on the water pump to change the actual pressure value; According to the first simulated voltage, controlling the speed of the water pump so that the actual pressure value reaches a first pressure value; comparing the first pressure value with a target pressure value; If the first pressure value does not meet the target pressure value, repeating the steps of obtaining the actual pressure value through the pressure sensor to adaptively learning the PID algorithm parameters based on the actual pressure value to obtain the first analog voltage for controlling the frequency of the inverter until the first pressure value is equal to the target pressure value; Acquire image information of the spray object in real time; analyze the degree of etching on the spray object based on the image information; and adjust the spray parameters of the nozzle numerically based on the degree of etching; Obtain an optimal pressure value and a target parameter in a solution tank; based on the target parameter, obtain the first pressure value; use the optimal pressure value, the first pressure value and the target parameter as input parameters of a model, train a deep learning model, and output an optimal target parameter; based on the optimal target parameter, adjust the target parameter; based on the optimal pressure value and the optimal target parameter, generate an optimal pressure value-optimal target parameter data table, which is subsequently used to adjust the target parameter.

2. The automatic constant pressure method according to claim 1, characterized in that: Also includes: detecting changes in the first pressure value in real time to determine whether to output abnormal data; If so, based on the abnormal data, an abnormal data report is obtained and an alarm signal is sent.

3. An automatic constant pressure device, characterized in that: The method for realizing the automatic constant pressure as claimed in claim 1 or 2 comprises: The actual pressure value acquisition module is used to obtain the target pressure value through the human-machine interface and obtain the actual pressure value through the pressure sensor; An adaptive learning module, used for adaptively learning PID algorithm parameters based on the actual pressure value, and obtaining a first analog voltage for controlling the frequency of the frequency converter; the first analog voltage is used to control the frequency of the frequency converter, and the output range of the first analog voltage is 0 to 10 volts, and each volt corresponds to a different frequency of the frequency converter; the frequency converter is electrically connected to the water pump; the frequency converter can control the motor speed on the water pump to change the actual pressure value; a water pump speed control module, used for controlling the water pump speed according to the first analog voltage so that the actual pressure value reaches a first pressure value; and comparing the first pressure value with a target pressure value; A repeated execution module is used to repeatedly execute the steps of obtaining the actual pressure value through the pressure sensor to adaptively learning the PID algorithm parameters based on the actual pressure value to obtain the first analog voltage for controlling the frequency of the inverter if the first pressure value does not meet the target pressure value, until the first pressure value is equal to the target pressure value.

4. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the automatic constant pressure method according to any one of claims 1 to 2 is implemented.

5. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the automatic constant pressure method according to any one of claims 1 to 2 is implemented.

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