Plating solution circulation monitoring and adjusting method and system fused with Internet of Things technology

Abstract

The invention discloses a plating solution circulation monitoring and adjusting method and system fused with the Internet of Things technology, and relates to the technical field of Internet of Things. The method comprises the following steps: acquiring a plurality of plating solution circulation partitions of a plurality of process sites; obtaining an Internet of Things cloud platform, and establishing a connection relationship between the plurality of edge devices and the plurality of process sites; performing data monitoring on the plurality of plating solution circulation partitions to obtain a plurality of plating solution partition monitoring data sets; transmitting the plurality of plating solution partition monitoring data sets to a plurality of edge devices, performing plating solution performance failure prediction according to the performance prediction sub-model, and obtaining a plurality of failure adjustment time sequence nodes; and performing plating solution adjustment on the plurality of plating solution circulation partitions according to the plurality of failure adjustment time sequence nodes. The technical problem that in the prior art, plating solution circulation monitoring and adjusting efficiency and accuracy are low is solved, real-time monitoring and predictive adjusting of the plating solution performance are achieved by fusing the Internet of Things technology and edge calculation, and the technical effect of improving the plating solution circulation adjusting efficiency and accuracy is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a plating solution circulation monitoring and regulating method and system integrating the Internet of Things technology. Background Art

[0002] In the electroplating industry, the stability of the performance of the plating solution is directly related to the quality and production efficiency of the electroplated products. However, the traditional monitoring and adjustment methods of the plating solution cycle usually rely on manual operation or simple fixed rules, which have the following problems: First, there is a lack of real-time monitoring and early warning mechanism for the failure of the plating solution performance, resulting in the failure of performance not being discovered in time, thus affecting the process stability; second, the adjustment method is single and cannot be adjusted according to the actual status of different plating solution circulation partitions, which easily leads to waste of resources and reduced efficiency. Summary of the invention

[0003] The present application provides a plating solution circulation monitoring and regulation method and system integrating Internet of Things technology, which solves the technical problem of low efficiency and accuracy of plating solution circulation monitoring and regulation in the prior art.

[0004] In view of the above problems, the present application provides a plating solution circulation monitoring and adjustment method and system integrating Internet of Things technology.

[0005] In a first aspect of the present application, a plating solution circulation monitoring and adjustment method integrating Internet of Things technology is provided, the method comprising: Acquire multiple plating solution circulation partitions of multiple process sites, wherein each process site corresponds to a plating solution circulation partition; acquire an Internet of Things cloud platform, wherein the Internet of Things cloud platform includes multiple edge devices, and establish a connection relationship between the multiple edge devices and the multiple process sites; acquire multiple plating solution partition monitoring data sets by performing data monitoring on the multiple plating solution circulation partitions; transmit the multiple plating solution partition monitoring data sets to the multiple edge devices, perform plating solution performance failure prediction according to the trained performance prediction sub-model stored in each edge device, and acquire multiple failure adjustment timing nodes, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than a preset plating solution performance failure index; and perform plating solution adjustment on the multiple plating solution circulation partitions according to the multiple failure adjustment timing nodes.

[0006] The second aspect of the present application provides a plating solution circulation monitoring and regulation system integrating Internet of Things technology, the system comprising: Partition acquisition module: obtain multiple plating solution circulation partitions of multiple process sites, wherein each process site corresponds to a plating solution circulation partition; connection module: obtain an Internet of Things cloud platform, the Internet of Things cloud platform includes multiple edge devices, and establishes a connection relationship between the multiple edge devices and the multiple process sites; data monitoring module: obtains multiple plating solution partition monitoring data sets by performing data monitoring on the multiple plating solution circulation partitions; prediction module: transmits the multiple plating solution partition monitoring data sets to the multiple edge devices, predicts plating solution performance failure according to the trained performance prediction sub-model stored in each edge device, and obtains multiple failure adjustment timing nodes, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than a preset plating solution performance failure index; plating solution adjustment module: performs plating solution adjustment on the multiple plating solution circulation partitions according to the multiple failure adjustment timing nodes.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, multiple plating solution circulation partitions of multiple process sites are obtained, wherein each process site corresponds to a plating solution circulation partition. Next, an Internet of Things cloud platform is obtained, which includes multiple edge devices, and a connection relationship between multiple edge devices and multiple process sites is established. Then, multiple plating solution partition monitoring data sets are obtained by performing data monitoring on multiple plating solution circulation partitions. Further, multiple plating solution partition monitoring data sets are transmitted to multiple edge devices, and plating solution performance failure prediction is performed according to the trained performance prediction sub-model stored in each edge device, and multiple failure adjustment timing nodes are obtained, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than the preset plating solution performance failure index. Finally, plating solution is adjusted for multiple plating solution circulation partitions according to multiple failure adjustment timing nodes. The technical problem of low efficiency and accuracy of plating solution circulation monitoring and adjustment in the prior art is solved. By integrating Internet of Things technology and edge computing, real-time monitoring and predictive adjustment of plating solution performance are realized, and the technical effect of improving the efficiency and accuracy of plating solution circulation adjustment is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic flow chart of a plating solution circulation monitoring and adjustment method integrating Internet of Things technology provided in an embodiment of the present application; Figure 2Schematic diagram of the structure of the plating solution circulation monitoring and control system integrating the Internet of Things technology provided in the embodiment of the present application.

[0010] Explanation of the reference numerals: partition acquisition module 11 , connection module 12 , data monitoring module 13 , prediction module 14 , plating solution adjustment module 15 . DETAILED DESCRIPTION

[0011] The present application solves the technical problem of low efficiency and accuracy of plating solution circulation monitoring and regulation in the prior art by providing a plating solution circulation monitoring and regulation method and system integrating Internet of Things technology.

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0013] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0014] Embodiment 1, as Figure 1 As shown, the present application provides a plating solution circulation monitoring and adjustment method integrating Internet of Things technology, wherein the method comprises: A plurality of plating solution circulation partitions of a plurality of process sites are obtained, wherein each process site corresponds to a plating solution circulation partition.

[0015] In industrial production, each process site usually performs specific process tasks, such as different plating bath types (such as zinc plating, nickel plating or copper plating) or production steps (such as pretreatment, electroplating or post-treatment), and these sites need to rely on independent plating bath circulation systems to ensure the stability and consistency of plating bath performance. By obtaining multiple plating bath circulation partitions of multiple process sites, the corresponding relationship between each process site and its corresponding plating bath circulation partition can be clarified.

[0016] Furthermore, after obtaining multiple plating solution circulation partitions of multiple process stations, the method further includes: Perform correlation identification on the multiple plating solution circulation partitions to obtain a plating solution circulation partition association group; obtain an edge device association group based on the plating solution circulation partition association group; perform integrated learning on the performance prediction sub-models corresponding to the edge device association group to obtain a performance prediction integrated model; update the model parameters of the performance prediction sub-model in the edge device association group based on the model parameters of the performance prediction integrated model.

[0017] After obtaining multiple plating solution circulation partitions of multiple process sites, the multiple plating solution circulation partitions are further identified for correlation to determine the correlation between these partitions in terms of process flow, plating solution characteristics (such as concentration, temperature, flow rate) or operating status (such as performance change trend), thereby generating plating solution circulation partition association groups, each of which contains multiple plating solution circulation partitions with strong correlation or shared operating parameters. Subsequently, according to the plating solution circulation partition association group, the corresponding edge device association group is obtained, and a group mapping relationship between edge devices and plating solution circulation partitions is established, so that each edge device association group can manage one or more plating solution circulation partition association groups. Next, the performance prediction sub-models in the edge device association group are integrated and learned, and the prediction results and parameters of each sub-model are input into an integrated learning framework (such as an integrated algorithm based on a gradient boosting tree or a deep learning model) to train a performance prediction integrated model for comprehensive analysis of the overall performance change trend and local performance failure points of the plating solution circulation system. Finally, according to the optimized model parameters in the performance prediction integrated model, the model parameters of each performance prediction sub-model in the edge device association group are updated to more accurately adapt to the real-time change requirements of the plating solution circulation partitions in the group.

[0018] Furthermore, after obtaining the plating solution circulation partition association group, the method further includes: Obtain the failure adjustment timing node association group corresponding to the plating solution circulation partition association group; obtain the adjustment synergistic influence relationship of the plating solution circulation partition association group; and perform collaborative optimization adjustment on the adjustment parameters of the failure adjustment timing node association group according to the adjustment synergistic influence relationship.

[0019] Based on the plating solution circulation partition association group, the failure adjustment timing nodes of the plating solution circulation partition in each association group are analyzed. These nodes represent the time point when the plating solution performance is about to fail and are the key indicators for triggering plating solution adjustment; the plating solution circulation partitions with similar failure adjustment timing nodes or those that influence each other are divided into failure adjustment timing node association groups. The adjustment synergistic influence relationship between the plating solution circulation partitions in the plating solution circulation partition association group is analyzed, including the influence of the adjustment of parameters such as plating solution composition, temperature, flow rate, etc. on the performance of other plating solution circulation partitions, such as the chain reaction of plating solution flow rate adjustment, temperature change or additive concentration change on the performance of other partitions; data mining is used to quantify the adjustment synergistic influence relationship between plating solution circulation partitions, so as to construct an adjustment synergistic influence relationship model to quantify the adjustment influence degree and feedback link between partitions. According to the coordinated influence relationship of the adjustment, the plating solution circulation partitions within the failure adjustment timing node association group are coordinated and optimized. During the coordinated optimization process, the adjustment parameters are globally optimized using a multi-objective optimization algorithm (such as a genetic algorithm or a particle swarm optimization algorithm) to ensure that the adjustment strategy of each partition not only meets its own performance recovery requirements, but also avoids negative impacts on other partitions due to the adjustment behavior; for example, by optimizing the plating solution flow rate, temperature adjustment rate or additive concentration range, the dynamic balance of the plating solution between partitions is coordinated, while maximizing the adjustment efficiency and stability. Through the above-mentioned coordinated optimization, the adjustment accuracy and resource utilization efficiency of the entire plating solution circulation system under complex correlation relationships are significantly improved, ensuring the overall smooth and efficient operation of the system.

[0020] An Internet of Things cloud platform is obtained, wherein the Internet of Things cloud platform includes a plurality of edge devices, and a connection relationship between the plurality of edge devices and the plurality of process sites is established.

[0021] By acquiring the IoT cloud platform, an efficient distributed management system is built. The IoT cloud platform consists of multiple edge devices that are responsible for performing data collection, processing, and transmission tasks between process sites and the cloud platform.

[0022] The edge devices in the IoT cloud platform are configured to establish a two-way communication connection with the control system of the process site, ensuring real-time data interaction through specific communication protocols (such as MQTT, HTTP or industrial bus protocols). Secondly, according to the actual layout and functional requirements of the process site, the edge devices are bound to the corresponding process sites, and the management scope of each edge device is clearly assigned so that it can collect data and execute adjustment instructions for the plating solution circulation partition of a specific process site. In addition, in the process of establishing a connection relationship, the redundancy and fault tolerance design of the edge devices must also be considered to cope with network fluctuations or hardware failures that may occur in the edge devices. For example, backup edge devices can be configured for multiple process sites, and dynamic switching can be achieved through the IoT cloud platform to ensure the stable operation of the system. Finally, by establishing a connection relationship between multiple edge devices and process sites, an efficient and reliable basic support is provided for subsequent data collection, performance prediction and intelligent adjustment.

[0023] By performing data monitoring on the multiple plating solution circulation partitions, multiple plating solution partition monitoring data sets are obtained.

[0024] Data acquisition devices, such as sensors (including temperature sensors, liquid level sensors, flow sensors, pH sensors, etc.), are deployed in each plating solution circulation partition to collect the core operating parameters of the plating solution partition, including the concentration, temperature, flow rate, liquid level, chemical composition stability and other indicators related to the plating solution performance. The data monitoring equipment is connected to the IoT cloud platform through the edge device, and the collected plating solution operation data is transmitted to the edge device. The edge device processes this data nearby and stores it in categories as a plating solution partition monitoring data set. Each monitoring data set corresponds to a plating solution circulation partition, which contains the real-time monitoring information and historical data records of the partition.

[0025] The multiple plating liquid partition monitoring data sets are transmitted to the multiple edge devices, and the plating liquid performance failure prediction is performed according to the trained performance prediction sub-model stored in each edge device to obtain multiple failure adjustment timing nodes, wherein the failure adjustment timing node is a timing node whose plating liquid performance failure index is less than a preset plating liquid performance failure index.

[0026] The acquired multiple plating solution partition monitoring data sets (including real-time multi-dimensional data such as temperature, concentration, flow rate, liquid level, chemical composition, etc.) are distributed to the corresponding edge devices according to the pre-established connection relationship; each edge device pre-stores a trained performance prediction sub-model, which compares the calculated plating solution performance index with the preset failure threshold, locates the time node when the performance index is lower than the preset threshold, and marks it as a failure adjustment timing node, while recording the corresponding time, location and failure parameters.

[0027] Furthermore, the plating solution performance failure prediction is performed according to the trained performance prediction sub-model stored in each edge device, and the method for training the performance prediction sub-model of each edge device includes: Obtain a plating solution monitoring sample data set for each edge device; perform feature extraction based on the plating solution monitoring sample data set to obtain relevant feature vectors that affect plating solution performance; divide a step state space that characterizes the failure level of plating solution performance according to the size of the relevant feature vector; construct a state transfer matrix based on the step state space; perform Markov chain training with the state transfer matrix, and output a trained performance prediction sub-model for each edge device.

[0028] Specifically, a plating solution monitoring sample data set within the management scope of each edge device is obtained, which contains the historical monitoring data and operation status information of the plating solution, such as temperature, concentration, flow rate, liquid level, chemical composition and other multi-dimensional data; feature extraction is performed on the plating solution monitoring sample data set, and relevant feature vectors affecting the performance of the plating solution are extracted through data processing methods (such as principal component analysis or feature importance analysis). These feature vectors can characterize the change trend and failure risk of the plating solution performance state; according to the size of the extracted feature vector, the plating solution performance state is graded, and the step state space that characterizes the failure level of the plating solution performance is divided. For example, the plating solution performance state is divided into multiple levels such as normal, warning and failure to form a hierarchical state representation. On this basis, the state transition matrix is ​​constructed using the divided step state space. Each item in the matrix represents the transition probability between different states, reflecting the possibility of the plating solution performance changing from one state to another. Finally, based on the state transfer matrix, the Markov chain training model is used to simulate the state change process of the plating solution performance over time, and finally the trained performance prediction sub-model is output. The performance prediction sub-model can predict the future change trend and failure probability of the plating solution performance, thereby providing accurate performance prediction capabilities for each edge device.

[0029] Furthermore, the elements in the state transfer matrix P are transition probabilities , the transition probability is the probability of state i transferring to state j at time instant; obtain a preset failure threshold, perform Markov chain training with the state transfer matrix P, and output the trained performance prediction sub-model of each edge device according to the preset failure threshold as a constraint condition.

[0030] In the process of training the performance prediction sub-model, the elements in the state transition matrix P It represents the probability of transitioning from the state at time i to the state at time j, that is, it represents the dynamic change law of the plating bath performance between different states. Specifically, states i and j correspond to different levels of plating bath performance (such as normal, warning, failure, etc.). Through statistical analysis of monitoring data, the transition probability between each state is calculated, thereby constructing the state transition matrix P.

[0031] During the training process, the preset failure threshold is first obtained as the criterion for determining the failure of the plating solution performance. For example, the threshold can be set based on performance indicators (such as concentration, temperature or flow rate) to define the critical failure state of the plating solution performance. Then, Markov chain training is performed based on the state transfer matrix P and the preset failure threshold. The training process simulates the time series changes of the plating solution performance state and analyzes the probability and time series characteristics of reaching the failure state from the current state. Specifically, according to the state transfer matrix P, the evolution path and transition probability of the plating solution performance from the normal state to the failure state are predicted, and the preset failure threshold is used as a constraint condition to screen out the prediction results that meet the actual process requirements. Finally, an optimized performance prediction sub-model is output, which can not only accurately predict the state distribution of the plating solution performance at future moments, but also determine the time node and probability distribution of reaching the failure state, providing accurate and efficient prediction capabilities for edge devices.

[0032] Plating solution is adjusted for the plurality of plating solution circulation partitions according to the plurality of failure adjustment timing nodes.

[0033] According to the plurality of failure adjustment timing nodes, the plating solution is adjusted for the corresponding plating solution circulation partitions, for example, the plating solution composition, temperature, pH value, etc. are adjusted.

[0034] Furthermore, the method for performing plating solution adjustment on the plurality of plating solution circulation partitions according to the plurality of failure adjustment timing nodes includes: Connect multiple circulation control modules corresponding to the multiple plating solution circulation partitions; obtain multiple real-time circulation parameters corresponding to the multiple circulation control modules; input the multiple failure adjustment timing nodes and the multiple real-time circulation parameters into the multiple circulation control modules, optimize the multiple real-time circulation parameters with the preset plating solution performance failure index, and output multiple optimized circulation parameters; adjust the plating solution for the multiple plating solution circulation partitions with the multiple optimized circulation parameters according to the multiple failure adjustment timing nodes.

[0035] Multiple circulation control modules corresponding to multiple plating solution circulation partitions are connected through the Internet of Things cloud platform, and each circulation control module is responsible for managing its associated plating solution partition. Then, multiple real-time circulation parameters are obtained from each circulation control module. These parameters may include key operating indicators such as flow rate, temperature and reagent addition amount, reflecting the actual state of the current plating solution circulation partition. Subsequently, multiple failure adjustment timing nodes and real-time circulation parameters are input into the corresponding circulation control module together. Based on the preset plating solution performance failure indicators (such as the lower limit of performance concentration or the upper limit of temperature), the optimization algorithm embedded in the module is used to optimize the multiple real-time circulation parameters and generate multiple optimized circulation parameters. Finally, according to the circulation parameters obtained by the optimization calculation and combined with the priority information of the failure adjustment timing node, accurate plating solution adjustment is performed on each plating solution circulation partition. Specific adjustment actions may include adjusting the flow rate of the circulation pump, controlling the temperature of the heating equipment, adding plating solution components or adjusting the liquid level, so as to ensure that the plating solution performance is restored to the normal range.

[0036] Furthermore, the method further comprises: performing plating solution adjustment on the plurality of plating solution circulation partitions according to the plurality of failure adjustment timing nodes; Wherein, the multiple plating solution circulation partitions are connected to multiple filtering devices; the multiple real-time circulation parameters are optimized based on the preset plating solution performance failure index, and if the multiple optimized circulation parameters are less than the preset plating solution performance failure index, a first activation instruction is obtained; according to the first activation instruction, the multiple filtering devices corresponding to the multiple plating solution circulation partitions are activated, and the plating solution is adjusted for the multiple plating solution circulation partitions according to the multiple filtering devices.

[0037] Multiple plating solution circulation partitions are connected to multiple filtering devices, and each filtering device is used to process impurities or substandard plating solution in the corresponding plating solution partition. When optimizing multiple real-time circulation parameters with a preset plating solution performance failure index, if the multiple optimized circulation parameters obtained by the optimization calculation are less than the preset plating solution performance failure index, a first activation instruction is generated to start the relevant filtering device; according to the first activation instruction, the filtering devices corresponding to the failed plating solution circulation partition are activated, and these filtering devices repair or optimize the plating solution performance by removing impurities or adjusting the chemical composition, concentration and other key indicators of the plating solution; the performance adjustment of the plating solution is completed through the filtering device, so that the plating solution performance is restored to the normal range, ensuring the stable operation of the plating solution circulation system.

[0038] In summary, the embodiments of the present application have at least the following technical effects: First, multiple plating solution circulation partitions of multiple process sites are obtained, wherein each process site corresponds to a plating solution circulation partition. Next, an Internet of Things cloud platform is obtained, which includes multiple edge devices, and a connection relationship between multiple edge devices and multiple process sites is established. Then, multiple plating solution partition monitoring data sets are obtained by performing data monitoring on multiple plating solution circulation partitions. Further, multiple plating solution partition monitoring data sets are transmitted to multiple edge devices, and plating solution performance failure prediction is performed according to the trained performance prediction sub-model stored in each edge device, and multiple failure adjustment timing nodes are obtained, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than the preset plating solution performance failure index. Finally, plating solution is adjusted for multiple plating solution circulation partitions according to multiple failure adjustment timing nodes. The technical problem of low efficiency and accuracy of plating solution circulation monitoring and adjustment in the prior art is solved. By integrating Internet of Things technology and edge computing, real-time monitoring and predictive adjustment of plating solution performance are realized, and the technical effect of improving the efficiency and accuracy of plating solution circulation adjustment is achieved.

[0039] Embodiment 2 is based on the same inventive concept as the plating solution circulation monitoring and adjustment method integrating the Internet of Things technology in the above embodiment. Figure 2 As shown, the present application provides a plating solution circulation monitoring and regulating system integrating Internet of Things technology, wherein the system includes: Partition acquisition module 11: acquire multiple plating solution circulation partitions of multiple process sites, wherein each process site corresponds to a plating solution circulation partition; connection module 12: acquire an Internet of Things cloud platform, wherein the Internet of Things cloud platform includes multiple edge devices, and establishes a connection relationship between the multiple edge devices and the multiple process sites; data monitoring module 13: acquire multiple plating solution partition monitoring data sets by performing data monitoring on the multiple plating solution circulation partitions; prediction module 14: transmit the multiple plating solution partition monitoring data sets to the multiple edge devices, perform plating solution performance failure prediction according to the trained performance prediction sub-model stored in each edge device, and acquire multiple failure adjustment timing nodes, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than a preset plating solution performance failure index; plating solution adjustment module 15: perform plating solution adjustment on the multiple plating solution circulation partitions according to the multiple failure adjustment timing nodes.

[0040] Furthermore, the plating solution regulating module 15 is used to perform the following method: Connect multiple circulation control modules corresponding to the multiple plating solution circulation partitions; obtain multiple real-time circulation parameters corresponding to the multiple circulation control modules; input the multiple failure adjustment timing nodes and the multiple real-time circulation parameters into the multiple circulation control modules, optimize the multiple real-time circulation parameters with the preset plating solution performance failure index, and output multiple optimized circulation parameters; adjust the plating solution for the multiple plating solution circulation partitions with the multiple optimized circulation parameters according to the multiple failure adjustment timing nodes.

[0041] Furthermore, the plating solution regulating module 15 is used to perform the following method: Wherein, the multiple plating solution circulation partitions are connected to multiple filtering devices; the multiple real-time circulation parameters are optimized based on the preset plating solution performance failure index, and if the multiple optimized circulation parameters are less than the preset plating solution performance failure index, a first activation instruction is obtained; according to the first activation instruction, the multiple filtering devices corresponding to the multiple plating solution circulation partitions are activated, and the plating solution is adjusted for the multiple plating solution circulation partitions according to the multiple filtering devices.

[0042] Furthermore, the prediction module 14 is used to perform the following method: Obtain a plating solution monitoring sample data set for each edge device; perform feature extraction based on the plating solution monitoring sample data set to obtain relevant feature vectors that affect plating solution performance; divide a step state space that characterizes the failure level of plating solution performance according to the size of the relevant feature vector; construct a state transfer matrix based on the step state space; perform Markov chain training with the state transfer matrix, and output a trained performance prediction sub-model for each edge device.

[0043] Furthermore, the prediction module 14 is used to perform the following method: The elements in the state transfer matrix P are transition probabilities , the transition probability is the probability of state i transferring to state j at time instant; obtain a preset failure threshold, perform Markov chain training with the state transfer matrix P, and output the trained performance prediction sub-model of each edge device according to the preset failure threshold as a constraint condition.

[0044] Furthermore, the partition acquisition module 11 is used to execute the following method: Perform correlation identification on the multiple plating solution circulation partitions to obtain a plating solution circulation partition association group; obtain an edge device association group based on the plating solution circulation partition association group; perform integrated learning on the performance prediction sub-models corresponding to the edge device association group to obtain a performance prediction integrated model; update the model parameters of the performance prediction sub-model in the edge device association group based on the model parameters of the performance prediction integrated model.

[0045] Furthermore, the partition acquisition module 11 is used to execute the following method: Obtain the failure adjustment timing node association group corresponding to the plating solution circulation partition association group; obtain the adjustment synergistic influence relationship of the plating solution circulation partition association group; and perform collaborative optimization adjustment on the adjustment parameters of the failure adjustment timing node association group according to the adjustment synergistic influence relationship.

[0046] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0047] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0048] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A plating solution circulation monitoring and adjustment method integrating Internet of Things technology, characterized in that: The method comprises: Acquire multiple plating solution circulation partitions of multiple process sites, wherein each process site corresponds to a plating solution circulation partition; Acquire an Internet of Things cloud platform, wherein the Internet of Things cloud platform includes a plurality of edge devices, and establish a connection relationship between the plurality of edge devices and the plurality of process sites; Acquire multiple plating solution partition monitoring data sets by performing data monitoring on the multiple plating solution circulation partitions; The plurality of plating solution partition monitoring data sets are transmitted to the plurality of edge devices, and plating solution performance failure prediction is performed according to the trained performance prediction sub-model stored in each edge device to obtain a plurality of failure adjustment timing nodes, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than a preset plating solution performance failure index; Plating solution is adjusted for the plurality of plating solution circulation partitions according to the plurality of failure adjustment timing nodes.

2. The plating solution circulation monitoring and adjustment method integrating Internet of Things technology as claimed in claim 1 is characterized in that: The method includes: performing plating solution adjustment on the plurality of plating solution circulation partitions according to the plurality of failure adjustment timing nodes; Connecting multiple circulation control modules corresponding to the multiple plating solution circulation partitions; Acquire multiple real-time cycle parameters corresponding to the multiple cycle control modules; Input the multiple failure adjustment timing nodes and the multiple real-time cycle parameters into the multiple cycle control modules, optimize the multiple real-time cycle parameters according to the preset plating solution performance failure index, and output multiple optimized cycle parameters; Plating solution is adjusted on the plurality of plating solution circulation partitions according to the plurality of failure adjustment timing nodes using the plurality of optimized circulation parameters.

3. The plating solution circulation monitoring and adjustment method integrating Internet of Things technology as claimed in claim 2 is characterized in that: The method further comprises: performing plating liquid adjustment on the plurality of plating liquid circulation partitions according to the plurality of failure adjustment timing nodes; include: Wherein, the multiple plating solution circulation partitions are connected to multiple filtering devices; Optimizing the plurality of real-time cycle parameters according to the preset plating solution performance failure index, and obtaining a first activation instruction if the plurality of optimized cycle parameters are less than the preset plating solution performance failure index; The plurality of filter devices corresponding to the plurality of plating solution circulation partitions are activated according to the first activation instruction, and the plating solution is adjusted for the plurality of plating solution circulation partitions according to the plurality of filter devices.

4. The plating solution circulation monitoring and adjustment method integrating Internet of Things technology as claimed in claim 1 is characterized in that: The plating solution performance failure prediction is performed according to the trained performance prediction sub-model stored in each edge device. The method for training the performance prediction sub-model of each edge device includes: Obtain a sample data set of plating solution monitoring for each edge device; Perform feature extraction based on the plating solution monitoring sample data set to obtain relevant feature vectors that affect plating solution performance; According to the size of the relevant characteristic vector, a step state space representing the failure level of the plating solution performance is divided; According to the step state space, construct a state transfer matrix; The state transfer matrix is ​​used to perform Markov chain training, and the trained performance prediction sub-model of each edge device is output.

5. The plating solution circulation monitoring and adjustment method integrating Internet of Things technology as claimed in claim 4 is characterized in that: The elements in the state transfer matrix P are transition probabilities , the transition probability is the probability of transition from state i to state j at time instant; Obtain a preset failure threshold, perform Markov chain training with the state transfer matrix P, and output the trained performance prediction sub-model of each edge device according to the preset failure threshold as a constraint condition.

6. The plating solution circulation monitoring and adjustment method integrating Internet of Things technology as claimed in claim 1 is characterized in that: After obtaining a plurality of plating solution circulation partitions for a plurality of process stations, the method further comprises: Performing correlation identification on the plurality of plating solution circulation partitions to obtain a plating solution circulation partition correlation group; According to the plating solution circulation partition association group, obtaining an edge device association group; Performing integrated learning on the performance prediction sub-models corresponding to the edge device association group to obtain a performance prediction integrated model; The model parameters of the performance prediction sub-model in the edge device association group are updated according to the model parameters of the performance prediction integrated model.

7. The plating solution circulation monitoring and adjustment method integrating Internet of Things technology as claimed in claim 6 is characterized in that: After obtaining the plating solution circulation partition association group, the method further includes: Obtaining a failure adjustment timing node association group corresponding to the plating solution circulation partition association group; Obtaining the adjustment synergistic influence relationship of the plating solution circulation partition association group; The adjustment parameters of the failure adjustment timing node association group are collaboratively optimized and adjusted according to the adjustment collaborative influence relationship.

8. The plating solution circulation monitoring and regulation system integrating Internet of Things technology is characterized by: The plating solution circulation monitoring and adjustment method integrating the Internet of Things technology according to any one of claims 1 to 7 is used, and the system comprises: Partition acquisition module: acquire multiple plating solution circulation partitions of multiple process sites, wherein each process site corresponds to a plating solution circulation partition; Connection module: obtaining an Internet of Things cloud platform, the Internet of Things cloud platform including a plurality of edge devices, and establishing a connection relationship between the plurality of edge devices and the plurality of process sites; Data monitoring module: acquiring a plurality of plating solution partition monitoring data sets by performing data monitoring on the plurality of plating solution circulation partitions; Prediction module: transmit the multiple plating solution partition monitoring data sets to the multiple edge devices, perform plating solution performance failure prediction according to the trained performance prediction sub-model stored in each edge device, and obtain multiple failure adjustment timing nodes, wherein the failure adjustment timing node is a timing node whose plating solution performance failure index is less than a preset plating solution performance failure index; A plating solution regulating module is configured to regulate the plating solution on the plurality of plating solution circulation partitions according to the plurality of failure regulation timing nodes.

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