Deep and far sea platform balance control method and system based on SCADA system

Abstract

The invention relates to the technical field of control data processing, and provides a deep and far sea platform balance control method and system based on an SCADA (Supervisory Control and Data Acquisition) system, and the deep and far sea platform balance control method based on the SCADA system comprises the following steps: S1, data distribution; s2, upper-position arrangement is carried out; s3, performing upper processing; s4, merging and sorting; and S5, carrying out lower processing. Based on the mode that the upper computer calculates the gain direction and the lower computer calculates the gain amount and executes control, the calculation amount of cooperative control can be greatly reduced, so that it is ensured that balance control of a system composed of multiple parts can be smoothly completed, and a solid and powerful overall frame is provided for balance control of an extensible deep and far sea platform system.

Description

Technical Field

[0001] The invention relates to a deep-sea platform balance control method and system based on a SCADA system, belonging to the technical field of control data processing. Background Art

[0002] SCADA (Supervisory Control And Data Acquisition) system, namely data acquisition and monitoring control system, is mainly used in data acquisition and monitoring control and process control in the fields of power, petroleum, chemical industry, gas, etc. Since SCADA system is convenient to control, flexible to expand, and easy to integrate data control model for intelligent control, SCADA system is also commonly used to control equipment on deep-sea platforms.

[0003] With the increasing demand for deep-sea exploration and development, deep-sea platforms have become more complex than before. In order to facilitate functional expansion, the current mainstream architecture adopts multiple parts that are independently designed and then spliced ​​into a central platform for unified coordination. For example, a central platform is spliced ​​with a fishing platform, an exploration platform and a mooring platform.

[0004] In the deep sea, since it is impossible to anchor on the ground or the seabed, balance control is an important part of the overall control. When the above-mentioned method of independently developing multiple parts and then splicing them together is adopted, since each part is developed independently, it has different balance requirements (such as fishing platforms have significantly lower balance requirements than mooring platforms) and balance structures. Therefore, for balance control, it is necessary to consider both the independent balance control requirements of each part and the influence of each part on the balance control of the central platform. This makes it difficult to complete the traditional centralized unified control method due to the large amount of calculation. Summary of the invention

[0005] To solve the above technical problems, the present invention provides a deep-sea platform balance control method and system based on the SCADA system. The upper computer calculates the gain direction, the lower computer calculates the gain amount and executes the control, which can greatly reduce the calculation amount of the collaborative control, thereby ensuring that the balance control of the multi-part system can be completed smoothly, and providing a solid and powerful overall framework for the scalable deep-sea platform system balance control.

[0006] The present invention is achieved through the following technical solutions.

[0007] The present invention provides a deep sea platform balance control method based on a SCADA system, comprising the following steps: S1, data distribution: obtain sensor data from the sensor, and combine the sensor data with the current timing control data as feedback data and send it to the upper field host; S2, upper level sorting: after receiving the feedback data, the field host separates the feedback data into sensor data and control data, normalizes the sensor data and places it into the sensor data FIFO cache queue for update, and directly places the control data into the control data FIFO cache queue for update; S3, upper processing: taking out the latest two time series of sensor data and control data from the sensor data FIFO cache queue and the control data FIFO cache queue respectively, comparing and calculating the difference of the sensor data and control data of the two time series item by item, fuzzy quantizing the difference, summarizing the difference fuzzy quantities of the sensor data and control data of multiple controllers and performing fuzzy reasoning to determine the gain direction of the difference fuzzy quantity of each control data relative to the overall situation of the difference fuzzy quantities of all sensor data, and returning the gain direction data of the control data to the corresponding controller; S4, merging and sorting: the controller normalizes the sensor data while waiting for and receiving the gain direction data, and obtains the control data of the current time sequence, and formats the normalized sensor, the gain direction data and the control data of the current time sequence into the data to be processed; S5, lower-level processing: Use the preset control model to calculate the data to be processed, obtain the control data of the next time series, then switch to the next time series and control the actuator according to the control data; when calculating, use the control data of the current time series as the reference, use the value calculated for the normalized sensor data as the control increment, and use the gain direction data as the superposition symbol of the control increment.

[0008] The sensing data are displacement sensors, velocity sensors and acceleration sensors at multiple installation points.

[0009] The normalization processing of the sensor data includes fast Fourier transform, filtering, and scale transformation.

[0010] In step S3, the fuzzy quantization adopts a membership function assigned by multiple intervals.

[0011] The fuzzy rules used in the fuzzy reasoning in step S3 are set according to the equipment structure and the installation positions of the sensors and actuators.

[0012] In step S5, the control model is set according to the balance control design scheme of the equipment part where the controller is located.

[0013] The present invention also provides a deep sea platform balance control system based on a SCADA system, comprising: A field host, used to execute step S2 and step S3 in the deep-sea platform balance control method based on the SCADA system as described above; A controller, used to execute step S1, step S4 and step S5 in the deep sea platform balance control method based on the SCADA system as described above; The device is composed of multiple parts, each part is controlled by a controller, each controller is connected to control multiple actuators and multiple sensors, and multiple controllers are connected and communicated with the on-site host through a control bus.

[0014] The field host is connected to a field database, a visualization module and a field server via a communication bus, wherein: The on-site database is used to store historical data; The visualization module is used to generate visualization charts based on historical data; The on-site server is used to provide user interaction services, including responding to user requests, sending historical data, and sending visual charts.

[0015] The communication bus is also connected with a client interface and a wireless communication module.

[0016] The control bus adopts Modbus protocol.

[0017] The beneficial effect of the present invention is that based on the upper computer calculating the gain direction and the lower computer calculating the gain amount and executing the control, the calculation amount of the collaborative control can be greatly reduced, thereby ensuring that the balance control of the multi-part system can be completed smoothly, and providing a solid and powerful overall framework for the balance control of the scalable deep-sea platform system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a connection diagram of at least one embodiment of the present invention; Figure 2 yes Figure 1 Schematic diagram of the control flow of the on-site host; Figure 3 yes Figure 1 Schematic diagram of the control flow of the controller; Figure 4 It is a schematic diagram of the structural layout of an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is further described below, but the scope of protection claimed is not limited to the description.

[0020] A first embodiment of the present invention relates to Figure 2 , Figure 3 A deep sea platform balance control method based on a SCADA system is shown, comprising the following steps: S1, data distribution: obtain sensor data from the sensor, and combine the sensor data with the current timing control data as feedback data and send it to the upper field host; S2, upper level arrangement: after receiving the feedback data, the field host separates the feedback data into sensor data and control data, normalizes the sensor data and places it into the sensor data FIFO cache queue for update, and directly places the control data into the control data FIFO cache queue for update; the out-of-queue data of the sensor data FIFO cache queue and the control data FIFO cache queue are directly discarded, and only the first-in-first-out feature of the FIFO queue is used to ensure that the data obtained each time the data in the queue is obtained is strictly arranged in the latest time sequence; S3, upper processing: taking out the latest two time series of sensor data and control data from the sensor data FIFO cache queue and the control data FIFO cache queue respectively, comparing and calculating the difference of the sensor data and control data of the two time series item by item, fuzzy quantizing the difference, summarizing the difference fuzzy quantities of the sensor data and control data of multiple controllers and performing fuzzy reasoning to determine the gain direction of the difference fuzzy quantity of each control data relative to the overall situation of the difference fuzzy quantities of all sensor data, and returning the gain direction data of the control data to the corresponding controller; S4, merging and sorting: the controller normalizes the sensor data while waiting for and receiving the gain direction data, and obtains the control data of the current time sequence, and formats the normalized sensor, the gain direction data and the control data of the current time sequence into the data to be processed; S5, lower-level processing: Use the preset control model to calculate the data to be processed, obtain the control data of the next time series, then switch to the next time series and control the actuator according to the control data; when calculating, use the control data of the current time series as the reference, use the value calculated for the normalized sensor data as the control increment, and use the gain direction data as the superposition symbol of the control increment.

[0021] Therefore, the present invention essentially calculates the gain direction and gain amplitude separately. The purpose of calculating the gain direction by the on-site host is mainly to determine the increase or decrease effect of the action mechanism (each action mechanism corresponds to at least one control data) on the overall balance; the purpose of calculating the gain amplitude by the controller is mainly to determine the control amount. Due to the complexity of deep-sea platforms, this method is more convenient for independent development of each part compared to the method of completely using the on-site host for overall control.

[0022] One implementation of the FIFO cache queue in the control system is to use a pointer array or a pointer linked list, and use an independent adding method to implement each new variable, then delete the last variable and move the remaining variables backward. Taking the pointer array as an example, in this solution, the sensor data FIFO cache queue is a pointer array [*x 1 ,*x2 ,……,*x n ], control the data FIFO buffer queue as a pointer array [*y 1 ,*y 2 ,……,*y n ], when adding a new sensor data *x to the sensor data FIFO buffer queue, first press n--use *x item by item n =*x n-1 , until n-1 equals 0, then make *x 1 =*x, add new control data *y to the control data FIFO cache queue in the same way, first press n--use *y item by item n =*y n-1 , until n-1 equals 0, then make *y 1 =*y. This ensures that *x 1 、*x 2 The sensor data of the latest two time series controls the data FIFO cache queue *y 1 、*y 2 It is the control data of the latest two time series.

[0023] It is easy to understand that the calculation principle of the above gain direction is to take out the latest two time series of sensor data in the sensor data FIFO cache queue*x 1 、*x 2 , and the control data of the latest two time series in the control data FIFO cache queue *y 1 、*y 2 After that, calculate the latest two time series sensor data*x 1 、*x 2 The difference between *Δx and the latest two timing control data *y 1 、*y 2The difference *Δy, *Δx and *Δy are all pointers, pointing to an array or structure storing multiple numerical values. Then, the more mature fuzzy control method in the prior art (including fuzzy quantization, fuzzy reasoning, and solving a specific control value in a fuzzy calculation manner) can be used to calculate the gain direction Δz. In essence, a fuzzy algorithm is used to calculate a specific value based on multiple numerical values. The fuzzy control method can refer to the prior art, such as a fuzzy controller design method disclosed in Chinese Patent Application No. CN202010792987.0, a noise reduction parameter determination method and an active noise reduction method and an active noise reduction method disclosed in Chinese Patent Application No. CN202110873136.3, and a fuzzy control method for eccentric vibration of a generator rotor based on a magnetorheological damper disclosed in Chinese Patent Application No. CN202211086550.0. The specific fuzzy algorithm formula used belongs to the code level rather than the architecture level involved in this application. It is not in the same technical scope as this application, so it is not within the scope of this application.

[0024] The preset control model in step S5 is preset in the subsystem according to actual needs. For example, for a typical application, Figure 4As shown, the central platform is a wind power foundation platform, on which wind turbines are installed for power generation. A fishing platform, a living platform, a mooring platform and a photovoltaic platform are respectively docked and assembled on the side of the central platform. The fishing platform, the living platform, the mooring platform and the photovoltaic platform are all called subsystems. The controller that plays an actual control role in each subsystem is called a controller. Each subsystem is developed as a whole by other independent departments (including the development of integrated structure, circuit connection, and control software), or directly adopts third-party products for docking structure transformation. Due to different development teams, the controllers of each subsystem have greatly different actuators and control logics for balance control, that is, the controllers of the subsystems have their own independent preset control models. Therefore, the process of step S5 is essentially the calculation process of the controller, but the output of the controller is truncated and the output items are symbolically processed (that is, the gain direction data is the superimposed symbol of the control increment) and then returned to the execution control module of the controller connection control (this operation requires the subsystem development department to provide an API interface). As for the balance control of the fishing platform, a typical prior art solution is a combined deep-sea fishery farming system disclosed in Chinese patent application number CN202210882705.5, which realizes balance control based on a wave compensator. As for the balance control of the photovoltaic platform, another typical prior art solution is a floating photovoltaic platform system with improved ocean adaptability disclosed in Chinese patent application number CN202410365496.6, which realizes balance control based on adjusting the buoyancy distribution. It can be seen that the prior art has different controls for different functional platforms. This application mainly focuses on data scheduling and control processing at the architectural level, so the control details of various subsystems will not be repeated one by one.

[0025] The second embodiment of the present invention is substantially the same as the first embodiment, mainly in that the sensing data are displacement sensors, velocity sensors and acceleration sensors at multiple installation points.

[0026] Furthermore, the sensor data normalization processing includes fast Fourier transform, filtering, and scale transformation.

[0027] Furthermore, in step S3, the fuzzy quantization adopts a membership function assigned by multiple intervals.

[0028] Furthermore, the fuzzy rules used in the fuzzy reasoning in step S3 are set according to the equipment structure and the installation positions of the sensors and actuators.

[0029] Furthermore, in step S5, the control model is set according to the balance control design scheme of the equipment part where the controller is located.

[0030] A third embodiment of the present invention relates to Figure 1 A deep sea platform balance control system based on a SCADA system is shown, comprising: An on-site host, used to execute step S2 and step S3 in the first embodiment or the second embodiment; A controller, configured to execute step S1, step S4 and step S5 in the first embodiment or the second embodiment; The device is composed of multiple parts, each part is controlled by a controller, each controller is connected to control multiple actuators and multiple sensors, and multiple controllers are connected and communicated with the on-site host through a control bus.

[0031] The fourth embodiment of the present invention is substantially the same as the third embodiment, mainly in that the field host is connected to the field database, the visualization module and the field server via a communication bus, wherein: The on-site database is used to store historical data; The visualization module is used to generate visualization charts based on historical data; The on-site server is used to provide user interaction services, including responding to user requests, sending historical data, and sending visual charts.

[0032] Furthermore, a client interface and a wireless communication module are also connected to the communication bus.

[0033] Furthermore, the control bus adopts the Modbus protocol.

Claims

1. A deep sea platform balance control method based on SCADA system, characterized in that: The following steps are involved: S1, data distribution: obtain sensor data from the sensor, and combine the sensor data with the current timing control data as feedback data and send it to the upper field host; S2, upper level sorting: after receiving the feedback data, the field host separates the feedback data into sensor data and control data, normalizes the sensor data and places it into the sensor data FIFO cache queue for update, and directly places the control data into the control data FIFO cache queue for update; S3, upper processing: taking out the latest two time series of sensor data and control data from the sensor data FIFO cache queue and the control data FIFO cache queue respectively, comparing and calculating the difference of the sensor data and control data of the two time series item by item, fuzzy quantizing the difference, summarizing the difference fuzzy quantities of the sensor data and control data of multiple controllers and performing fuzzy reasoning to determine the gain direction of the difference fuzzy quantity of each control data relative to the overall situation of the difference fuzzy quantities of all sensor data, and returning the gain direction data of the control data to the corresponding controller; S4, merging and sorting: the controller normalizes the sensor data while waiting for and receiving the gain direction data, and obtains the control data of the current time sequence, and formats the normalized sensor, the gain direction data and the control data of the current time sequence into the data to be processed; S5, lower-level processing: using a preset control model to calculate the data to be processed, obtaining the control data of the next time sequence, then switching to the next time sequence and controlling the actuator according to the control data; During calculation, the control data of the current time series is used as a reference, the value calculated for the normalized sensor data is used as a control increment, and the gain direction data is used as a superposition symbol of the control increment.

2. The deep sea platform balance control method based on SCADA system as claimed in claim 1, characterized in that: The sensing data are displacement sensors, velocity sensors and acceleration sensors at multiple installation points.

3. The deep sea platform balance control method based on SCADA system as claimed in claim 1, characterized in that: The normalization processing of the sensor data includes fast Fourier transform, filtering, and scale transformation.

4. The deep sea platform balance control method based on SCADA system as claimed in claim 1, characterized in that: In step S3, the fuzzy quantization adopts a membership function assigned by multiple intervals.

5. The deep sea platform balance control method based on SCADA system as claimed in claim 1, characterized in that: The fuzzy rules used in the fuzzy reasoning in step S3 are set according to the equipment structure and the installation positions of the sensors and actuators.

6. The deep sea platform balance control method based on SCADA system as claimed in claim 1, characterized in that: In step S5, the control model is set according to the balance control design scheme of the equipment part where the controller is located.

7. A deep sea platform balance control system based on SCADA system, characterized in that: include, A field host, used to execute step S2 and step S3 in the deep-sea platform balance control method based on the SCADA system as described in any one of claims 1 to 6; A controller, used to execute step S1, step S4 and step S5 in the deep-sea platform balance control method based on the SCADA system according to any one of claims 1 to 6; The device is composed of multiple parts, each part is controlled by a controller, each controller is connected to control multiple actuators and multiple sensors, and multiple controllers are connected and communicated with the on-site host through a control bus.

8. The deep sea platform balance control system based on SCADA system as claimed in claim 7, characterized in that: The field host is connected to a field database, a visualization module and a field server via a communication bus, wherein: The on-site database is used to store historical data; The visualization module is used to generate visualization charts based on historical data; The on-site server is used to provide user interaction services, including responding to user requests, sending historical data, and sending visual charts.

9. The deep sea platform balance control system based on SCADA system as claimed in claim 8, characterized in that: The communication bus is also connected with a client interface and a wireless communication module.

10. The deep sea platform balance control system based on SCADA system as claimed in claim 7, characterized in that: The control bus adopts Modbus protocol.

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