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CN-121992471-A - Intelligent control method and system for electroplating soft treatment

CN121992471ACN 121992471 ACN121992471 ACN 121992471ACN-121992471-A

Abstract

The application discloses an intelligent control method and system for electroplating soft processing, the method comprises the steps of obtaining current working condition information and instant monitoring data of a process tank, extracting key characteristic parameters for representing the state of the tank based on the instant monitoring data, obtaining matched initial process parameters based on the current working condition information and the key characteristic parameters through matching of a preset historical working condition database, starting processing according to the initial process parameters, obtaining monitoring data in the process tank at fixed time and updating the key characteristic parameters according to the monitoring data in the processing process, generating optimal process parameters based on the updated key characteristic parameters by taking a preset quality target as a guide through a preset self-adaptive process model, and generating a process parameter adjusting instruction by taking the optimal process parameters as current process parameter set values. The application can improve the consistency and stability of the electroplating soft treatment process by constructing a closed-loop control framework integrating real-time sensing and dynamic optimization.

Inventors

  • LUO HAO

Assignees

  • 杭州云会五金电镀有限公司

Dates

Publication Date
20260508
Application Date
20260410

Claims (10)

  1. 1. An intelligent control method for electroplating soft treatment is characterized by comprising the following steps: Acquiring current working condition information and immediate monitoring data of a process tank, wherein the monitoring data comprise the pH value, conductivity, temperature and oxidation-reduction potential ORP of the liquid in the process tank; Based on the instant monitoring data, extracting key characteristic parameters for representing the state of the tank liquid; based on the current working condition information and the key characteristic parameters, matching is carried out through a preset historical working condition database, and matched initial technological parameters are obtained; The initial technological parameters are used as the set values of the current technological parameters, processing is started according to the preset technological process, monitoring data in a technological groove are obtained at fixed time in the processing process, and key characteristic parameters are updated according to the monitoring data; Based on the updated key characteristic parameters, guiding by taking a preset quality target, and generating optimal process parameters through a preset self-adaptive process model; And generating a process parameter adjusting instruction by taking the optimal process parameter as a current process parameter set value.
  2. 2. The intelligent control method for electroplating soft processing according to claim 1, wherein the extracting key characteristic parameters for representing the state of the bath based on the instant monitoring data comprises: Preprocessing the instant monitoring data, and aligning and fusing the preprocessed instant monitoring data in a time dimension to form a unified tank state time sequence data set; based on the state time sequence data set, key characteristic parameters are obtained through a preset calculation method.
  3. 3. The intelligent control method for electroplating soft processing according to claim 1, wherein the matching is performed through a preset history working condition database based on the current working condition information and the key characteristic parameters, and the obtaining of the matched initial process parameters comprises the following steps: coding the current working condition information and the key characteristic parameters to generate a working condition characteristic vector; based on the working condition feature vector, performing similarity matching through a preset historical working condition database, and acquiring a historical working condition record with the highest similarity and the corresponding similarity; If the similarity is higher than a preset first similarity threshold, recording corresponding historical process parameters of the historical working condition with the highest similarity as matched initial process parameters; If the similarity is lower than a preset first similarity threshold and higher than a preset second similarity threshold, generating an effective fusion set for all history working condition records with the similarity higher than the preset second similarity threshold; Based on the effective fusion set, weighting and fusing the historical process parameters corresponding to each historical working condition record by taking the similarity corresponding to each historical working condition record as a weight to generate initial process parameters; if the similarity is lower than a preset second similarity threshold, adopting a preset general safety process parameter as an initial process parameter.
  4. 4. The intelligent control method for electroplating soft processing according to claim 1, wherein the generating optimal process parameters based on the updated key feature parameters and guided by a preset quality target through a preset adaptive process model comprises: Generating a working state vector based on the current working condition information and the updated key characteristic parameters, wherein the working state vector is used for representing the real-time comprehensive state of the current process tank; based on the working state vector and the current technological parameter set value, generating a quality predicted value of the current processing result through a preset self-adaptive technological model; Calculating a quality deviation by presetting a quality target based on the quality predicted value; judging whether the quality deviation is lower than a preset threshold value or not; If yes, taking the current technological parameter set value as an optimal technological parameter; If not, generating optimal technological parameters through a preset optimization algorithm according to the quality deviation.
  5. 5. The intelligent control method for electroplating soft processing according to claim 4, wherein the generating optimal process parameters according to the quality deviation through a preset optimization algorithm comprises: generating a candidate process parameter set based on the current process parameter set value and the quality deviation; Traversing the candidate process parameter set, outputting a corresponding quality prediction result through a preset self-adaptive process model for each candidate process parameter, and acquiring a cost item through a preset process cost calculation method; based on the quality prediction result and the cost item, generating a comprehensive evaluation score through a preset weight coefficient; and after the traversal is finished, marking the candidate process parameter with the minimum comprehensive evaluation score as the optimal process parameter.
  6. 6. The intelligent control method for electroplating soft treatment according to claim 1, wherein the process tank comprises a plurality of treatment tanks connected in series in sequence, two adjacent treatment tanks are respectively marked as a pre-treatment tank and a post-treatment tank according to a preset procedure, and in the treatment process, before starting treatment, any post-treatment tank further comprises: acquiring process parameters finally adopted by a preamble processing tank and key characteristic parameters of tank liquor when the processing is completed, and recording the process parameters and the key characteristic parameters as feedforward process information; The feedforward process information is added into the current working condition information to be used as updated current working condition information; and adjusting the initial process parameters corresponding to the subsequent processing tank based on the updated current working condition information to generate adjusted process parameters.
  7. 7. The intelligent control method for electroplating soft processing according to claim 6, wherein the adjusting the initial process parameters corresponding to the subsequent processing tank based on the updated current operating condition information to generate adjusted process parameters comprises: Comparing the updated current working condition information with the initial working condition information before starting processing to obtain a state characteristic increment; Based on the state characteristic increment, acquiring a corresponding standardized adjustment scheme through a preset increment-parameter correction mapping table; based on a standard adjustment scheme, the initial process parameters corresponding to the subsequent processing tank are adjusted to generate adjusted process parameters.
  8. 8. The intelligent control method for electroplating soft processing according to claim 1, wherein the process of periodically acquiring the monitoring data in the process tank and updating the key characteristic parameters according to the monitoring data further comprises: calculating process health indexes based on key characteristic parameters, wherein the process health indexes comprise component stability indexes and Ha-pollute accumulation rate; Based on the current working condition information, generating a corresponding dynamic safety threshold value for the process health index through a preset dynamic threshold model; And comparing the process health index with a corresponding dynamic safety threshold, and outputting abnormal prompt information if any index exceeds the corresponding dynamic safety threshold.
  9. 9. An intelligent control system for electroplating soft processing, comprising: The data acquisition module (101) is used for acquiring current working condition information and immediate monitoring data of the process tank, wherein the monitoring data comprise the pH value, the conductivity, the temperature and the oxidation-reduction potential ORP of the tank liquid in the process tank; the initial parameter matching module (102) is used for extracting key characteristic parameters for representing the state of the tank liquid based on the instant monitoring data, and matching the key characteristic parameters through a preset history working condition database based on the current working condition information and the key characteristic parameters to obtain matched initial process parameters; The data dynamic monitoring module (103) is used for starting processing according to a preset process flow by taking an initial process parameter as a current process parameter set value, acquiring monitoring data in a process tank at regular time in the processing process, and updating key characteristic parameters according to the monitoring data; The parameter dynamic correction module (104) is used for generating optimal process parameters by taking a preset quality target as a guide and a preset self-adaptive process model based on the updated key characteristic parameters; And the parameter adjustment execution module (105) is used for generating a process parameter adjustment instruction by taking the optimal process parameter as a current process parameter set value.
  10. 10. A computer readable storage medium storing a computer program capable of being loaded by a processor and executing an intelligent control method for plating soft processing according to any one of claims 1 to 8.

Description

Intelligent control method and system for electroplating soft treatment Technical Field The application relates to the technical field of electroplating soft treatment, in particular to an intelligent control method and system for electroplating soft treatment. Background The electroplating soft treatment link refers to the general term of all chemical or physical chemical treatment steps which do not change the surface state of a workpiece through electrodeposition (i.e. no power supply) in the main electroplating process, and mainly comprises key procedures such as oil removal, acid washing, passivation and the like. The core process parameters such as the temperature, concentration, treatment time and the like of the conventional electroplating soft treatment are usually set by operators according to experience, and cannot be dynamically adjusted according to working conditions (such as the number of workpieces, pollution degree, bath state and the like) which change in real time, so that the fluctuation of the product quality is large, and the consistency is poor. Disclosure of Invention The application aims to provide an intelligent control method and system for electroplating soft treatment, so as to realize a full-automatic intelligent control scheme for real-time sensing and intelligent decision making, thereby replacing manual experience and ensuring that the soft treatment process is always in an optimal state. In a first aspect, the present application provides an intelligent control method for electroplating soft processing, including: Acquiring current working condition information and immediate monitoring data of a process tank, wherein the monitoring data comprise the pH value, conductivity, temperature and oxidation-reduction potential ORP of the liquid in the process tank; Based on the instant monitoring data, extracting key characteristic parameters for representing the state of the tank liquid; based on the current working condition information and the key characteristic parameters, matching is carried out through a preset historical working condition database, and matched initial technological parameters are obtained; The initial technological parameters are used as the set values of the current technological parameters, processing is started according to the preset technological process, monitoring data in a technological groove are obtained at fixed time in the processing process, and key characteristic parameters are updated according to the monitoring data; Based on the updated key characteristic parameters, guiding by taking a preset quality target, and generating optimal process parameters through a preset self-adaptive process model; And generating a process parameter adjusting instruction by taking the optimal process parameter as a current process parameter set value. According to the technical scheme, through timely obtaining the tank liquor monitoring data and extracting the key characteristic parameters, accurate cognition of the tank liquor state is achieved, further, the personalized initial process parameters are obtained through intelligent matching of the historical data, an optimal starting point is provided for the workpiece to be processed, the process parameters are continuously monitored and dynamically optimized in the processing process, a control closed loop for sensing the dynamic optimization in real time is formed, the process parameters are ensured to be self-adaptive to the real-time working conditions all the time, and accordingly consistency and stability of the electroplating soft processing process are improved. Optionally, the extracting key feature parameters for characterizing the state of the tank based on the instant monitoring data includes: Preprocessing the instant monitoring data, and aligning and fusing the preprocessed instant monitoring data in a time dimension to form a unified tank state time sequence data set; based on the state time sequence data set, key characteristic parameters are obtained through a preset calculation method. Optionally, the matching is performed through a preset historical working condition database based on the current working condition information and the key characteristic parameters, and the obtaining of the matched initial technological parameters includes: coding the current working condition information and the key characteristic parameters to generate a working condition characteristic vector; based on the working condition feature vector, performing similarity matching through a preset historical working condition database, and acquiring a historical working condition record with the highest similarity and the corresponding similarity; If the similarity is higher than a preset first similarity threshold, recording corresponding historical process parameters of the historical working condition with the highest similarity as matched initial process parameters; If the similarity is lower than a preset first sim