A multi-bus fusion control system and method based on PLC control

Abstract

The present invention relates to the technical field of multi-bus fusion control, and specifically, to a multi-bus fusion control system and method based on PLC control. It includes a fusion control unit, an operation influencing unit, an influencing factor analysis unit, a parameter optimization unit, a parameter sending unit, and an adaptive monitoring unit; the fusion control unit is used to establish a receiving end and an output end by integrating different communication buses with PLC as the core control end; the present invention can realize real-time prediction of equipment operation data by using a prediction model, rather than being limited to reactions based on historical data, which enables the system to quickly respond to changing working conditions and predict possible future equipment states, thereby improving the real-time and accuracy of operation and maintenance. Through prediction and adaptive detection, the system can promptly discover situations where equipment operation data deviates from adaptive parameter settings. Once the predicted data exceeds the predetermined range, the system immediately adjusts through parameter updates to ensure that the equipment is always in the best operating state.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-bus fusion control, and in particular to a multi-bus fusion control system and method based on PLC control. Background Art

[0002] With the increasingly complex functional requirements of PLC control systems, it is often necessary to expand more different functional boards to realize product functions. In traditional PLC controller design, we usually use a combination of baseboard and functional modular design to achieve different functional combinations to meet different user needs. The data transmission between the functional module and the main control module is realized through the backplane bus technology;

[0003] At present, when the equipment is controlled by PLC for production, each working equipment is generally controlled and monitored separately. When the equipment has problems, the corresponding parameters of the equipment are adjusted. However, most of the working equipment are connected to each other. If the parameters of one device are adjusted, it will affect other devices. If the equipment is adjusted one by one, it is necessary to continuously adjust the equipment. If no comprehensive adjustment is made, it is easy to cause the working efficiency of the overall equipment to deviate from the ideal working efficiency, and there will be shutdown failures due to the incompatibility of working parameters between devices. Therefore, a multi-bus fusion control system and method based on PLC control is proposed. Summary of the invention

[0004] The object of the present invention is to provide a multi-bus fusion control system and method based on PLC control to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, one of the purposes of the present invention is to provide a multi-bus fusion control system based on PLC control, including a fusion control unit, an operation influencing unit, an influencing factor analysis unit, a parameter optimization unit, a parameter sending unit and an adaptation monitoring unit;

[0006] The fusion control unit is used to use the PLC as the core control end and fuse different communication buses to establish a receiving end and an output end;

[0007] The operation influencing unit is used to extract the historical operation data and historical operation parameters fed back by each communication bus at the receiving end, analyze the operation influence of each working device as the device center on other working devices, and obtain the influencing device list of each working device;

[0008] The influencing factor analysis unit is used to extract the parameter adjustment log of each communication bus, combine the parameter adjustment log with the influencing device list to perform parameter influencing factor analysis, and obtain the impact data of different degrees of parameter adjustment on the influencing device list;

[0009] The parameter optimization unit is used to combine the real-time operation data with the historical operation data to predict the operation data, and to adjust and analyze the predicted operation data in combination with the real-time operation parameters. When the predicted operation data contains nodes that exceed the range of the real-time operation parameters, the device is optimized for parameter analysis;

[0010] The parameter sending unit is used to receive the optimization parameters through the output end, and analyze the optimization parameters in combination with the operation influencing unit and the influencing factor analysis unit to perform adaptive parameter analysis on the influencing device, obtain the adaptive parameters of the influencing device, and then send the optimization parameters and the adaptive parameters to the device driver through the communication bus;

[0011] The adaptation monitoring unit is used to perform adaptation monitoring on the working equipment that receives the adaptation parameters. When the operating data of the working equipment that receives the adaptation parameters exceeds the node of the adaptation parameters, the deviation operating data, the adaptation parameters and the correct operating data are updated, thereby outputting new adaptation parameters to the working equipment.

[0012] As a further improvement of the technical solution, the fusion control unit uses PLC as the core control end, and integrates the communication buses of different production equipment with PLC to establish a communication channel, which is responsible for receiving and processing data from different communication buses, thereby dividing the core control end into a receiving end and an output end;

[0013] The receiving end is used to receive the operation data and operation parameters fed back by the communication bus;

[0014] The output terminal is used to send operating parameters to the communication bus.

[0015] As a further improvement of the technical solution, the operation influencing unit includes a data extraction module and an influencing device acquisition module;

[0016] The data extraction module is used to extract the historical operation data and historical operation parameters fed back by each communication bus in the receiving end, and classify the historical operation data and historical operation parameters according to the working equipment managed by each communication bus, and obtain the historical operation data and historical operation parameters of each working equipment;

[0017] The influencing device acquisition module is used to set an impact ratio threshold, and take each working device as the device center for monitoring. When new operating parameters appear in the device, the operating data of other working devices are detected with the impact ratio threshold. When the impact of the operating data of other working devices exceeds the impact ratio threshold, it is determined that the other working devices are affected devices. Conversely, when the impact of the operating data of other working devices does not exceed the impact ratio threshold, the detection is continued, and then the affected devices are summarized to establish an influencing device list for each working device.

[0018] As a further improvement of the technical solution, the working formula of the influencing factor analysis unit is as follows:

[0019]

[0020] in, Is the parameter adjustment affecting the device The degree of influence, Is the impact device The parameter change, Is the impact device The initial or base value of a parameter.

[0021] As a further improvement of the technical solution, the parameter optimization unit includes a data prediction module and an optimization analysis module;

[0022] The data prediction module is used to predict the operation data of the working equipment by combining the real-time operation data and the historical operation data with the real-time operation parameters, obtain the predicted operation data, and set the operation data range corresponding to each operation parameter;

[0023] The optimization analysis module is used to adjust and analyze the predicted operating data and the operating data range. When the predicted operating data contains operating data that exceeds the range corresponding to the real-time operating parameters, the optimization parameter analysis is performed in combination with the real-time operating parameters of the equipment and the predicted operating data to obtain the optimized parameters of the equipment. Conversely, when the predicted operating data does not contain operating data that exceeds the range corresponding to the real-time operating parameters, monitoring is continued.

[0024] As a further improvement of the technical solution, the working formula of the parameter optimization unit is as follows:

[0025]

[0026] in, is the number of predicted runs, is the actual operation data corresponding to the real-time operation parameters. and is the permissible range of operating data;

[0027]

[0028] Among them, A is the optimization parameter, C is the original operating parameter, k is the adjustment coefficient, which is used to control the rate and amplitude of adjustment, and ε is the predicted value. With actual value deviation.

[0029] As a further improvement of the technical solution, the working formula of the parameter sending unit is as follows:

[0030]

[0031] Among them, θ new is the ideal operating parameter of the device, which can be the adjusted temperature setting value or other control parameters, and f is a function based on the optimization parameter θ opt and the adaptation parameter θ adapt New equipment operating parameters are calculated.

[0032] As a further improvement of the technical solution, the adaptation monitoring unit includes an adaptation monitoring module and a parameter updating module;

[0033] The adaptation monitoring module is used to predict the adaptation operation data of the working equipment receiving the adaptation parameters, obtain the predicted adaptation operation data of the working equipment receiving the adaptation parameters, and then perform adaptation detection according to the predicted adaptation operation data;

[0034] The parameter updating module is used to monitor the results of the adaptation detection. When the predicted adaptation operation data exceeds the operating range of the adaptation parameter, the deviation data of the predicted adaptation operation data and the operating parameters of the adaptation parameter are combined with the adaptation parameter to update the parameters, and new adaptation parameters are obtained and applied to the working device.

[0035] The second object of the present invention is to provide a multi-bus fusion control method based on PLC control, including any one of the multi-bus fusion control systems based on PLC control described above, including the following steps:

[0036] S1, integrate different communication buses and establish connection with PLC through integration control unit;

[0037] S2. Perform influencing equipment list analysis and influencing data analysis by running the influencing unit and influencing factor analysis unit;

[0038] S3, analyzing the optimization parameters of the working equipment through the parameter optimization unit, and then outputting the adaptation parameters to other working equipment through the parameter sending unit according to the optimization parameters combined with the affected equipment list and the affected data;

[0039] S4. Monitor and update the parameters of the working equipment that receives the adaptation parameters through the adaptation monitoring unit.

[0040] Compared with the prior art, the present invention has the following beneficial effects: by using a prediction model, real-time prediction of equipment operation data can be achieved, rather than being limited to reactions based on historical data, which enables the system to quickly respond to changing working conditions and predict possible future equipment states, thereby improving the real-time and accuracy of operation and maintenance. Through prediction and adaptive detection, the system can promptly discover situations where equipment operation data deviates from the adaptive parameter settings. Once the predicted data exceeds the predetermined range, the system immediately adjusts through parameter updates to ensure that the equipment is always in the best operating state. This optimization helps to extend the life of the equipment and reduce maintenance and replacement costs. By continuously optimizing the adaptive parameters, the system can help the equipment maintain stable high production efficiency under different working conditions. This continuous optimization process helps to reduce downtime and improve equipment utilization, thereby enhancing overall production efficiency and the stability of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is the overall structural principle diagram of the present invention.

[0042] The meaning of each number in the figure is:

[0043] 10. Fusion control unit; 20. Operation influencing unit; 30. Influencing factor analysis unit; 40. Parameter optimization unit; 50. Parameter sending unit; 60. Adaptation monitoring unit. DETAILED DESCRIPTION

[0044] 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 only 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.

[0045] like Figure 1 As shown, one of the purposes of the present invention is to provide a multi-bus fusion control system based on PLC control, including a fusion control unit 10, an operation influencing unit 20, an influencing factor analysis unit 30, a parameter optimization unit 40, a parameter sending unit 50 and an adaptation monitoring unit 60;

[0046] The fusion control unit 10 is used to establish a receiving end and an output end by fusion of different communication buses with PLC as the core control end;

[0047] The fusion control unit 10 uses PLC as the core control end, and integrates the communication buses of different production equipment to establish a communication channel with PLC, and is responsible for receiving and processing data from different communication buses, thereby dividing the core control end into a receiving end and an output end;

[0048] The receiving end is used to receive the operation data and operation parameters fed back by the communication bus;

[0049] The output terminal is used to send operating parameters to the communication bus. The working steps are as follows:

[0050] Choose the right PLC and communication module: First, choose the Ethernet port that is suitable for connecting with different types of devices and communication buses.

[0051] Configure communication modules and protocols: Configure PLC communication modules to ensure compatibility with various communication bus protocols. For example, configure Modbus communication protocol modules to communicate with ModbusRTU / TCP devices; configure CAN bus modules to communicate with CAN bus devices, etc.

[0052] Receiving end implementation: Write a PLC program to enable it to receive data from various communication buses;

[0053] Data processing: In the PLC program, write logic to process the received data. This includes data parsing, storage, calculation or execution of other control logic. PLCs usually have built-in math and logic function blocks for data processing and control algorithms.

[0054] Output end implementation: Configure the PLC program so that it can send data to different communication buses as needed. These data include control instructions, adjustment parameters, etc.

[0055] The operation influencing unit 20 is used to extract the historical operation data and historical operation parameters fed back by each communication bus at the receiving end, analyze the operation influence of each working device as the device center on other working devices, and obtain the influencing device list of each working device;

[0056] The operation influencing unit 20 includes a data extraction module and an influencing device acquisition module;

[0057] The data extraction module is used to extract the historical operation data and historical operation parameters fed back by each communication bus in the receiving end, and classify the historical operation data and historical operation parameters according to the working equipment managed by each communication bus, and obtain the historical operation data and historical operation parameters of each working equipment. The working steps are as follows:

[0058] Set up data reception: Configure the PLC communication module according to the protocol and communication mode of each communication bus. For Modbus communication, set the correct address and function code; for CAN bus, configure the correct data frame format and identifier;

[0059] Data parsing and classification: In the PLC program, parse the received data frame, extract the required historical operation data and parameters, and use conditional statements or data mapping to determine which device's historical data the data should be stored in;

[0060] Data storage: Store data in the corresponding historical data record according to the device identification, using arrays, structures or database tables.

[0061] The affected device acquisition module is used to set the impact ratio threshold, and each working device is used as the device center for monitoring. When the device has new operating parameters, the operating data of other working devices are detected with the impact ratio threshold. When the impact of the operating data of other working devices exceeds the impact ratio threshold, the other working devices are determined to be affected devices. On the contrary, when the impact of the operating data of other working devices does not exceed the impact ratio threshold, the detection is continued, and then the affected devices are summarized to establish an affecting device list for each working device. The working steps are as follows:

[0062] Set impact ratio threshold: Define a threshold to determine whether the operating data of other devices is affected by the central device. This threshold can be a percentage or an absolute value, indicating the sensitivity threshold of data changes of other devices;

[0063] Detection of new operating parameters of central equipment: When new operating parameters of central equipment A are updated, the changes of these parameters are recorded;

[0064] Impact detection: For each other working device B, compare the change between the new operating parameters of device A and the current operating parameters of device B. If the change exceeds the set impact ratio threshold, it is determined that device B is affected by device A.

[0065] Establishment of the affected equipment list: record all equipment B affected by equipment A, and establish the affected equipment list for each working equipment; the formula is as follows:

[0066]

[0067] in, To affect the ratio threshold, is the change in the operating parameters of device A, is the current value of the corresponding operating parameter of device B;

[0068] is the change in a parameter of device A, such as temperature, pressure, etc. This can be the absolute change value of the parameter within a specific time period, that is, , is the latest parameter value, is the previous parameter value;

[0069] It is the current value of the corresponding parameter of device B, which can be obtained from the communication bus of device B at any time;

[0070] This is a ratio that measures Relative to If the size is larger, indicating that the change of device A has a greater impact on device B; conversely, if Smaller, the change is relatively small.

[0071]

[0072] when The absolute value of Multiply , it is considered that device B is affected by device A.

[0073] The influencing factor analysis unit 30 is used to extract the parameter adjustment log of each communication bus, combine the parameter adjustment log with the influencing device list to perform parameter influencing factor analysis, and obtain the impact data of different degrees of parameter adjustment on the influencing device list;

[0074] Parameter adjustment log extraction: Extract parameter adjustment logs from each communication bus system. These logs contain records of changes in device or system parameters at different time points.

[0075] Parameter influencing factor analysis: Combine the parameter adjustment log with the affected device list to perform influencing factor analysis. This analysis aims to determine the impact of different degrees of parameter adjustment on the affected device list.

[0076] Obtain impact data: Based on the analysis results, obtain the impact data of different degrees of parameter adjustment on each affected device. These data can be numerical impact amounts, such as the percentage or absolute value of the impact. The formula is as follows:

[0077]

[0078] in, Is the parameter adjustment affecting the device The degree of influence, Is the impact device The parameter change, Is the impact device Initial or baseline values ​​of parameters;

[0079] The parameter change is calculated in the formula Relative to the initial value of the parameter The ratio tells the percentage or multiple of the parameter change to the initial parameter value. It is a unitless value indicating the effect of parameter adjustment on the device. If Large, indicating that the parameter adjustment has an impact on the device On the contrary, if The smaller the value, the smaller the impact.

[0080] The parameter optimization unit 40 is used to predict the operation data by combining the real-time operation data with the historical operation data, and to adjust and analyze the predicted operation data in combination with the real-time operation parameters. When the predicted operation data contains nodes that exceed the range of the real-time operation parameters, the optimization parameter analysis is performed on the device.

[0081] The parameter optimization unit 40 includes a data prediction module and an optimization analysis module;

[0082] The data prediction module is used to predict the operation data of the working equipment by combining the real-time operation data and the historical operation data with the real-time operation parameters, obtain the predicted operation data, and set the operation data range corresponding to each operation parameter;

[0083] The optimization analysis module is used to adjust and analyze the predicted operation data and the operation data range. When the predicted operation data contains operation data that exceeds the range corresponding to the real-time operation parameters, the optimization parameter analysis is performed in combination with the real-time operation parameters of the equipment and the predicted operation data to obtain the optimized parameters of the equipment. Conversely, when the predicted operation data does not contain operation data that exceeds the range corresponding to the real-time operation parameters, the monitoring is continued. The working formula is as follows:

[0084]

[0085] in, is the number of predicted runs, is the actual operation data corresponding to the real-time operation parameters. and is the permissible range of operating data;

[0086]

[0087] Among them, A is the optimization parameter, C is the original operating parameter, k is the adjustment coefficient, which is used to control the rate and amplitude of adjustment, and ε is the predicted value. With actual value Deviation;

[0088] The function of this formula is to use the predicted operating data The actual operation data The deviation ε is adjusted to adjust the current parameter value so that the predicted operating data can gradually approach the target value within the ideal range.

[0089] The parameter sending unit 50 is used to receive the optimization parameters through the output end, and analyze the optimization parameters in combination with the operation influencing unit 20 and the influencing factor analysis unit 30 to perform adaptive parameter analysis on the influencing device, obtain the adaptive parameters of the influencing device, and then send the optimization parameters and the adaptive parameters to the device driver through the communication bus. The formula is as follows:

[0090]

[0091] Among them, θ new is the ideal operating parameter of the device, which can be the adjusted temperature setting value or other control parameters, and f is a function based on the optimization parameter θ opt and the adaptation parameter θ adapt Calculate new equipment operating parameters;

[0092] θ new The ideal equipment operating parameters are calculated by optimization algorithms, such as machine learning models, PID controllers, etc. θadapt is used to adjust the optimization parameters θ according to the actual condition of the equipment, environmental changes, or other factors that need to be considered. opt To ensure the best operation of the device under different working conditions, the adaptation parameter can be a correction of the calibration value, a compensation factor or any other device-specific adjustment parameter. f is the optimization parameter θ opt and the adaptation parameter θ adapt Combined, a new device operating parameter θ is generated new。

[0093] The adaptation monitoring unit 60 is used to perform adaptation monitoring on the working equipment receiving the adaptation parameters. When the operating data of the working equipment receiving the adaptation parameters exceeds the node of the adaptation parameters, the deviation operating data, the adaptation parameters and the correct operating data are updated, thereby outputting new adaptation parameters to the working equipment.

[0094] The adaptation monitoring unit 60 includes an adaptation monitoring module and a parameter updating module;

[0095] The adaptation monitoring module is used to predict the adaptation operation data of the working equipment receiving the adaptation parameters, obtain the predicted adaptation operation data of the working equipment receiving the adaptation parameters, and then perform adaptation detection according to the predicted adaptation operation data;

[0096] The parameter update module is used to monitor the results of the adaptation detection. When the predicted adaptation operation data exceeds the operating range of the adaptation parameters, the deviation data of the predicted adaptation operation data and the operating parameters of the adaptation parameters are combined with the adaptation parameters to update the parameters and obtain new adaptation parameters for application to the working equipment.

[0097] The second object of the present invention is to provide a multi-bus fusion control method based on PLC control, including any one of the multi-bus fusion control systems based on PLC control described above, comprising the following steps:

[0098] S1, merging different communication buses and establishing connections with PLC through the fusion control unit 10;

[0099] S2, performing influencing device list analysis and influencing data analysis by running the influencing unit 20 and the influencing factor analysis unit 30;

[0100] S3, performing optimization parameter analysis on the working equipment through the parameter optimization unit 40, and then outputting adaptation parameters to other working equipment through the parameter sending unit 50 according to the optimization parameters combined with the affected equipment list and the affected data;

[0101] S4. Monitor and update the parameters of the working equipment that receives the adaptation parameters through the adaptation monitoring unit 60.

[0102] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A multi-bus fusion control system based on PLC control, characterized by: It comprises a fusion control unit (10), an operation influencing unit (20), an influencing factor analysis unit (30), a parameter optimization unit (40), a parameter sending unit (50) and an adaptation monitoring unit (60); The fusion control unit (10) is used to use the PLC as the core control end and fuse different communication buses to establish a receiving end and an output end; The operation influencing unit (20) is used to extract historical operation data and historical operation parameters fed back by each communication bus at the receiving end, analyze the operation influence of each working device as a device center on other working devices, and obtain a list of influencing devices for each working device; The influencing factor analysis unit (30) is used to extract the parameter adjustment log of each communication bus, combine the parameter adjustment log with the influencing device list to perform parameter influencing factor analysis, and obtain the impact data of different degrees of parameter adjustment on the influencing device list; The parameter optimization unit (40) is used to combine the real-time operation data with the historical operation data to perform operation data prediction, and to combine the predicted operation data with the real-time operation parameters to perform adjustment analysis, and when the predicted operation data contains nodes that exceed the range of the real-time operation parameters, perform optimization parameter analysis on the device; The parameter sending unit (50) is used to receive the optimization parameters through the output end, and analyze the optimization parameters in combination with the operation influencing unit (20) and the influencing factor analysis unit (30) to perform adaptive parameter analysis on the influencing device, obtain the adaptive parameters of the influencing device, and then send the optimization parameters and the adaptive parameters to the device driver through the communication bus; The adaptation monitoring unit (60) is used to perform adaptation monitoring on a working device that receives the adaptation parameter, and when the operating data of the working device that receives the adaptation parameter exceeds the node of the adaptation parameter, the deviation operating data, the adaptation parameter and the correct operating data are updated, thereby outputting new adaptation parameters to the working device; The operation influencing unit (20) comprises a data extraction module and an influencing device acquisition module; The data extraction module is used to extract the historical operation data and historical operation parameters fed back by each communication bus in the receiving end, and classify the historical operation data and historical operation parameters according to the working equipment managed by each communication bus, and obtain the historical operation data and historical operation parameters of each working equipment; The influencing device acquisition module is used to set an influencing ratio threshold value, and monitor each working device as a device center. When a new operating parameter appears in the working device, the operating data of other working devices are detected with the influencing ratio threshold value. When the influencing factors of the operating data of other working devices exceed the influencing ratio threshold value, the other working devices are determined to be affected devices. On the contrary, when the influencing factors of the operating data of other working devices do not exceed the influencing ratio threshold value, the detection is continued, and then the affected devices are summarized to establish an influencing device list for each working device. The working formula of the influencing factor analysis unit (30) is as follows: ； in, is the degree of influence of parameter adjustment on device i, is the parameter change that affects device i, It is the initial value or reference value of the parameter affecting device i.

2. The multi-bus fusion control system based on PLC control according to claim 1 is characterized in that: The fusion control unit (10) uses the PLC as the core control end, and integrates the communication buses of different production equipment to establish a communication channel with the PLC, and is responsible for receiving and processing data from different communication buses, thereby dividing the core control end into a receiving end and an output end; The receiving end is used to receive the operation data and operation parameters fed back by the communication bus; The output terminal is used to send operating parameters to the communication bus.

3. The multi-bus fusion control system based on PLC control according to claim 1 is characterized in that: The parameter optimization unit (40) comprises a data prediction module and an optimization analysis module; The data prediction module is used to predict the operation data of the working equipment by combining the real-time operation data and the historical operation data with the real-time operation parameters, obtain the predicted operation data, and set the operation data range corresponding to each operation parameter; The optimization analysis module is used to adjust and analyze the predicted operating data and the operating data range. When the predicted operating data contains operating data that exceeds the range corresponding to the real-time operating parameters, the optimization parameter analysis is performed in combination with the real-time operating parameters of the equipment and the predicted operating data to obtain the optimized parameters of the equipment. Conversely, when the predicted operating data does not contain operating data that exceeds the range corresponding to the real-time operating parameters, monitoring is continued.

4. The multi-bus fusion control system based on PLC control according to claim 1 is characterized in that: The working formula of the parameter optimization unit (40) is as follows: ； in, is the number of predicted runs, is the actual operation data corresponding to the real-time operation parameters. and is the permissible range of operating data; ； Among them, A is the optimization parameter, C is the original operating parameter, k is the adjustment coefficient, which is used to control the rate and amplitude of adjustment, and ε is the predicted value. With actual value deviation.

5. The multi-bus fusion control system based on PLC control according to claim 1 is characterized in that: The working formula of the parameter sending unit (50) is as follows: ； in, is the ideal operating parameter of the equipment, which can be the adjusted temperature setting value or other control parameters, and f is a function based on the optimization parameters and adaptation parameters New equipment operating parameters are calculated.

6. The multi-bus fusion control system based on PLC control according to claim 1 is characterized in that: The adaptation monitoring unit (60) comprises an adaptation monitoring module and a parameter updating module; The adaptation monitoring module is used to predict the adaptation operation data of the working equipment receiving the adaptation parameters, obtain the predicted adaptation operation data of the working equipment receiving the adaptation parameters, and then perform adaptation detection according to the predicted adaptation operation data; The parameter updating module is used to monitor the results of the adaptation detection. When the predicted adaptation operation data exceeds the operating range of the adaptation parameter, the deviation data of the predicted adaptation operation data and the operating parameters of the adaptation parameter are combined with the adaptation parameter to update the parameters, and new adaptation parameters are obtained and applied to the working device.

7. A method for implementing a multi-bus fusion control method based on PLC control, comprising a multi-bus fusion control system based on PLC control as claimed in any one of claims 1 to 6, characterized in that: The steps include: S1, merging different communication buses and establishing a connection with a PLC through a fusion control unit (10); S2, performing an influencing device list analysis and an influencing data analysis by running the influencing unit (20) and the influencing factor analysis unit (30); S3, performing optimization parameter analysis on the working equipment through the parameter optimization unit (40), and then outputting adaptive parameters to other working equipment through the parameter sending unit (50) according to the optimization parameters combined with the affected equipment list and the affected data; S4. Monitoring and updating parameters of the working device receiving the adaptation parameters by the adaptation monitoring unit (60).

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