Control method and system of hybrid ship tail gas desulfurization device

Abstract

The invention relates to a control method and system of a hybrid ship tail gas desulfurization device, and belongs to the technical field of equipment control. The method comprises the following steps: acquiring longitude and latitude coordinates of a ship, a longitude and latitude coordinate range of a drainage prohibited sea area, seawater alkalinity data, seawater depth data, closed-loop desulfurization device parameters and open-loop desulfurization device parameters; according to the ship longitude and latitude coordinates, the drainage forbidding sea area longitude and latitude coordinate range, the seawater alkalinity data and the seawater depth data, a judgment result is obtained through calculation of a judgment model; performing identification according to a judgment result, and performing corresponding operation according to an identification result; performing preprocessing and prediction according to the closed-loop desulfurization device parameters and the open-loop desulfurization device parameters to obtain a closed-loop desulfurization efficiency prediction result and an open-loop desulfurization efficiency prediction result; and determining an execution strategy according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result. Reasonable scheduling of the hybrid ship tail gas desulfurization device is realized, and the tail gas desulfurization efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of equipment control, and in particular relates to a control method and system for a hybrid ship exhaust gas desulfurization device. Background Art

[0002] With the enhancement of global environmental awareness and the rapid development of the shipping industry, the issue of ship exhaust emissions has received increasing attention. In particular, pollutants such as sulfur dioxide emitted by ships pose a serious threat to the marine environment and air quality. To this end, governments have introduced strict emission regulations, requiring ships to take effective desulfurization measures. As an efficient and flexible desulfurization technology, hybrid ship exhaust gas desulfurization devices are gradually becoming the mainstream choice in the market. This article aims to introduce an innovative control method and system for a hybrid ship exhaust gas desulfurization device. This method comprehensively considers factors such as the ship's location and seawater environment, and intelligently selects the optimal desulfurization method to achieve efficient and environmentally friendly ship exhaust gas treatment.

[0003] Traditional ship exhaust gas desulfurization devices are mainly divided into two types: open-loop and closed-loop. Open-loop desulfurization devices use seawater to directly absorb sulfur dioxide in exhaust gas, but are limited by environmental factors such as seawater alkalinity and depth, and may cause secondary pollution to the environment. Closed-loop desulfurization devices use chemical absorbents for desulfurization. Although they are not limited by seawater conditions, their operating costs are relatively high. Therefore, how to intelligently select desulfurization methods based on ship navigation conditions and environmental factors has become a hot topic in current research. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a control method and system for a hybrid ship exhaust gas desulfurization device. The purpose of the present invention can be achieved through the following technical solutions: S1: Obtain the longitude and latitude coordinates of the ship through the ship's AIS unit, obtain the longitude and latitude coordinate range of the prohibited discharge sea area, obtain the seawater alkalinity data and seawater depth data through the ship bottom sensor, and obtain the closed-loop desulfurization device parameters and open-loop desulfurization device parameters through the device's built-in sensors; S2: Obtaining a determination result through calculation using a determination model according to the longitude and latitude coordinates of the ship, the longitude and latitude coordinate range of the prohibited discharge sea area, the seawater alkalinity data, and the seawater depth data; the determination result includes closed-loop operation and continued calculation; S3 performs identification according to the determination result. If the determination result is the closed-loop operation, the intelligent terminal executes the first control strategy; if the determination result is the continued calculation, steps S4-S5 are executed; S4: according to the closed-loop desulfurization device parameters, the closed-loop pretreatment data are calculated by the pretreatment model, according to the open-loop desulfurization device parameters, the open-loop pretreatment data are calculated by the pretreatment model, according to the closed-loop pretreatment data, the closed-loop desulfurization efficiency prediction result is calculated by the closed-loop GRNN model, and according to the seawater alkalinity data and the open-loop pretreatment data, the open-loop desulfurization efficiency prediction result is calculated by the open-loop GRNN model; S5: obtaining an evaluation result through calculation of an evaluation model according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, and the intelligent terminal determines an execution strategy according to the evaluation result.

[0005] Specifically, the judgment model includes judging whether the longitude and latitude coordinates of the ship are within the longitude and latitude coordinate range of the prohibited discharge sea area through a coordinate matching algorithm. If yes, the judgment result is output as the closed-loop operation; if not, the seawater alkalinity threshold is obtained, and a judgment is made based on the seawater alkalinity data and the seawater alkalinity threshold. If the seawater alkalinity data is less than the seawater alkalinity threshold, the judgment result is output as the closed-loop operation; if the seawater alkalinity data is greater than the seawater alkalinity threshold, the seawater depth threshold is obtained, and a judgment is made based on the seawater depth threshold and the seawater depth data. If the seawater depth data is less than the seawater depth threshold, the judgment result is output as the closed-loop operation; if the seawater depth data is greater than the seawater depth threshold, the judgment result is output as the continued calculation.

[0006] Specifically, the pretreatment model obtains noise reduction data through filtering according to the closed-loop desulfurization device parameters, obtains correction data through zero-point correction according to the noise reduction data, and obtains the closed-loop pretreatment data through normalization according to the correction data.

[0007] Specifically, the evaluation model makes a judgment based on the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result. If the closed-loop desulfurization efficiency prediction result is greater than the open-loop desulfurization efficiency prediction result, the output evaluation result is the closed-loop operation; if the closed-loop desulfurization efficiency prediction result is less than the open-loop desulfurization efficiency prediction result, the output evaluation result is the open-loop operation.

[0008] Specifically, the closed-loop GRNN model consists of an input layer, a pattern layer, a summation layer, and an output layer. The specific calculation steps are: S201: transmitting the closed-loop preprocessing data to the model layer through the input layer; S202: The mode layer calculates the closed-loop pre-processed data through a Gaussian function to obtain Gaussian processed data; S203: the summing layer performs a summing operation on the Gaussian processed data to obtain a summing result; S204: the output layer calculates according to the summation result to obtain prediction data, and obtains the closed-loop desulfurization efficiency prediction result by reverse normalization according to the prediction data.

[0009] Specifically, the parameters of the closed-loop desulfurization device include the inlet flue gas volume of the closed-loop desulfurization device, the ammonia concentration of the closed-loop desulfurization device, the absorption liquid concentration of the closed-loop desulfurization device, the liquid-to-gas ratio of the closed-loop desulfurization device, the inlet temperature of the closed-loop desulfurization device, the ammonia consumption of the closed-loop desulfurization device, and the pH value of the slurry in the spray tower of the closed-loop desulfurization device; the parameters of the open-loop desulfurization device include the inlet flue gas volume of the open-loop desulfurization device, the ammonia concentration of the open-loop desulfurization device, the liquid-to-gas ratio of the open-loop desulfurization device, the inlet temperature of the open-loop desulfurization device, the ammonia consumption of the open-loop desulfurization device, and the pH value of the slurry in the spray tower of the open-loop desulfurization device.

[0010] Specifically, the execution strategy includes the first control strategy and the second control strategy. The first control strategy is to operate the closed-loop desulfurization device and shut down the open-loop desulfurization device; the second control strategy is to shut down the closed-loop desulfurization device and operate the open-loop desulfurization device.

[0011] A control system for a hybrid ship exhaust gas desulfurization device, comprising: a data acquisition module, a determination module, an identification module, a prediction module, and a control module; The data acquisition module is used to obtain the longitude and latitude coordinates of the ship through the AIS unit of the ship, obtain the longitude and latitude coordinate range of the prohibited discharge sea area, obtain the seawater alkalinity data and seawater depth data through the bottom sensor of the ship, and obtain the closed-loop desulfurization device parameters and the open-loop desulfurization device parameters through the built-in sensor of the device; The determination module is used to calculate the determination result through the determination model according to the longitude and latitude coordinates of the ship, the longitude and latitude coordinate range of the prohibited discharge sea area, the seawater alkalinity data, and the seawater depth data; the determination result includes closed-loop operation and continued calculation; The identification module is used to identify according to the determination result. If the determination result is the closed-loop operation, the intelligent terminal executes the first control strategy; if the determination result is the continued calculation, steps S4-S5 are executed; The prediction module is used to calculate the closed-loop pretreatment data through the pretreatment model according to the closed-loop desulfurization device parameters, calculate the open-loop pretreatment data through the pretreatment model according to the open-loop desulfurization device parameters, calculate the closed-loop desulfurization efficiency prediction result through the closed-loop GRNN model according to the closed-loop pretreatment data, and calculate the open-loop desulfurization efficiency prediction result through the open-loop GRNN model according to the seawater alkalinity data and the open-loop pretreatment data; The control module is used to calculate an evaluation result through an evaluation model according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, and the intelligent terminal determines an execution strategy according to the evaluation result.

[0012] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the control method of the hybrid ship exhaust gas desulfurization device as described above when executing the program.

[0013] A storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a control method for a hybrid ship exhaust gas desulfurization device as described above when executed by a computer processor.

[0014] The beneficial effects of the present invention are: (1) The method first makes a comprehensive judgment based on the longitude and latitude coordinates of the ship, the longitude and latitude coordinates of the prohibited discharge area, the seawater alkalinity data and the seawater depth data. This step ensures that the desulfurization operation complies with environmental protection regulations and makes full use of natural environmental conditions. When the ship enters the prohibited discharge area or the seawater conditions do not meet the requirements, the system automatically switches to the closed-loop desulfurization device to ensure that environmental protection requirements can be met under any circumstances.

[0015] (2) By setting up the GRNN model, when the ship is not in the prohibited discharge area and the seawater conditions meet the requirements, the system obtains real-time data and uses the generalized regression neural network (GRNN) model to predict the desulfurization efficiency of the closed-loop desulfurization device and the open-loop desulfurization device respectively. The GRNN model, with its powerful nonlinear mapping and generalization capabilities, can accurately predict the desulfurization efficiency under different working conditions, providing a scientific basis for the selection of the optimal desulfurization method.

[0016] (3) Based on the prediction results of the GRNN model, the system intelligently determines the desulfurization efficiency of the closed-loop desulfurization device and the open-loop desulfurization device, and selects the more efficient desulfurization mode for operation. This dynamic selection mechanism not only ensures the desulfurization effect, but also reduces the operating cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0018] Figure 1 The present invention is a flow chart of a control method of a hybrid ship exhaust gas desulfurization device. DETAILED DESCRIPTION

[0019] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments; See also Figure 1 , a control method for a hybrid ship exhaust gas desulfurization device, specifically comprising: S1: Obtain the longitude and latitude coordinates of the ship through the ship's AIS unit, obtain the longitude and latitude coordinate range of the prohibited discharge sea area, obtain the seawater alkalinity data and seawater depth data through the ship bottom sensor, and obtain the closed-loop desulfurization device parameters and open-loop desulfurization device parameters through the device's built-in sensors; S2: Obtaining a determination result through calculation using a determination model according to the longitude and latitude coordinates of the ship, the longitude and latitude coordinate range of the prohibited discharge sea area, the seawater alkalinity data, and the seawater depth data; the determination result includes closed-loop operation and continued calculation; S3 performs identification according to the determination result. If the determination result is the closed-loop operation, the intelligent terminal executes the first control strategy; if the determination result is the continued calculation, steps S4-S5 are executed; S4: according to the closed-loop desulfurization device parameters, the closed-loop pretreatment data are calculated by the pretreatment model, according to the open-loop desulfurization device parameters, the open-loop pretreatment data are calculated by the pretreatment model, according to the closed-loop pretreatment data, the closed-loop desulfurization efficiency prediction result is calculated by the closed-loop GRNN model, and according to the seawater alkalinity data and the open-loop pretreatment data, the open-loop desulfurization efficiency prediction result is calculated by the open-loop GRNN model; S5: obtaining an evaluation result through calculation of an evaluation model according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, and the intelligent terminal determines an execution strategy according to the evaluation result.

[0020] In this embodiment, the hybrid ship exhaust gas desulfurization device includes a closed-loop desulfurization device and an open-loop desulfurization device. Gas valves are respectively provided at the two desulfurization devices and the ship exhaust gas inlet channel. When one device is in operation, the intelligent terminal controls the valve and power supply of the other device through a PWM modulation signal; the AIS unit is composed of shore-based, satellite-based receiving equipment and ship-borne equipment, and its main functions include ship identification and positioning, navigation safety enhancement, data exchange and electronic chart display module integration.

[0021] It should be noted that the closed-loop GRNN model and the open-loop GRNN model are both GRNN models, and the closed-loop GRNN model and the open-loop GRNN model have the same structure, calculation process, and training process.

[0022] Specifically, the parameters of the closed-loop desulfurization device include the inlet flue gas volume of the closed-loop desulfurization device, the ammonia concentration of the closed-loop desulfurization device, the absorption liquid concentration of the closed-loop desulfurization device, the liquid-to-gas ratio of the closed-loop desulfurization device, the inlet temperature of the closed-loop desulfurization device, the ammonia consumption of the closed-loop desulfurization device, and the pH value of the slurry in the spray tower of the closed-loop desulfurization device; the parameters of the open-loop desulfurization device include the inlet flue gas volume of the open-loop desulfurization device, the ammonia concentration of the open-loop desulfurization device, the liquid-to-gas ratio of the open-loop desulfurization device, the inlet temperature of the open-loop desulfurization device, the ammonia consumption of the open-loop desulfurization device, and the pH value of the slurry in the spray tower of the open-loop desulfurization device.

[0023] Specifically, the execution strategy includes the first control strategy and the second control strategy. The first control strategy is to operate the closed-loop desulfurization device and shut down the open-loop desulfurization device; the second control strategy is to shut down the closed-loop desulfurization device and operate the open-loop desulfurization device.

[0024] Specifically, the judgment model includes judging whether the longitude and latitude coordinates of the ship are within the longitude and latitude coordinate range of the prohibited discharge sea area through a coordinate matching algorithm. If yes, the judgment result is output as the closed-loop operation; if not, the seawater alkalinity threshold is obtained, and a judgment is made based on the seawater alkalinity data and the seawater alkalinity threshold. If the seawater alkalinity data is less than the seawater alkalinity threshold, the judgment result is output as the closed-loop operation; if the seawater alkalinity data is greater than the seawater alkalinity threshold, the seawater depth threshold is obtained, and a judgment is made based on the seawater depth threshold and the seawater depth data. If the seawater depth data is less than the seawater depth threshold, the judgment result is output as the closed-loop operation; if the seawater depth data is greater than the seawater depth threshold, the judgment result is output as the continued calculation.

[0025] In this embodiment, the coordinate matching algorithm adopts the Hungarian algorithm.

[0026] Specifically, the pretreatment model obtains noise reduction data through filtering according to the closed-loop desulfurization device parameters, obtains correction data through zero-point correction according to the noise reduction data, and obtains the closed-loop pretreatment data through normalization according to the correction data.

[0027] It should be noted that the process of obtaining the open-loop pretreatment data by calculating the pretreatment model according to the open-loop desulfurization device parameters is consistent with the process of obtaining the closed-loop pretreatment data by calculating the pretreatment model according to the closed-loop desulfurization device parameters.

[0028] Specifically, the evaluation model makes a judgment based on the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result. If the closed-loop desulfurization efficiency prediction result is greater than the open-loop desulfurization efficiency prediction result, the output evaluation result is the closed-loop operation; if the closed-loop desulfurization efficiency prediction result is less than the open-loop desulfurization efficiency prediction result, the output evaluation result is the open-loop operation.

[0029] Specifically, the closed-loop GRNN model consists of an input layer, a pattern layer, a summation layer, and an output layer. The specific calculation steps are: S201: transmitting the closed-loop preprocessing data to the model layer through the input layer; S202: The mode layer calculates the closed-loop pre-processed data through a Gaussian function to obtain Gaussian processed data; The Gaussian function expression is: , in, P i is the output of the ith neuron, X Preprocessing data for the closed loop, X i is the i-th training sample, δ is the smoothing factor, exp is the exponential function, and T is the transpose calculation; It should be noted that the size of variable i is the number of training samples; S203: the summing layer performs a summing operation on the Gaussian processed data to obtain a summing result; The summation operation includes arithmetic sum calculation and weighted sum calculation, and the arithmetic sum calculation formula is: , in, S D is the arithmetic sum, i is a variable parameter, n is the total number of training samples, P i is the output result of the i-th neuron; The weighted sum calculation formula is: , Among them, S is the weighted sum, i is a variable parameter, n is the total number of training samples, P i is the output of the ith neuron, Y i is the connection weight between the i-th neuron in the pattern layer and the neurons in the summation layer; S204: the output layer calculates according to the summation result to obtain prediction data, and obtains the closed-loop desulfurization efficiency prediction result by reverse normalization according to the prediction data; The prediction data calculation formula is: , in, Y is the predicted data, S is the weighted sum, S D is the arithmetic sum.

[0030] Specifically, the intelligent terminal determines the execution strategy according to the evaluation result, which specifically includes making a judgment according to the evaluation result. If the evaluation result is a closed-loop operation, the execution strategy is the first control strategy; if the evaluation result is an open-loop operation, the execution strategy is the second control strategy.

[0031] In this embodiment, when the evaluation model judges the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, a parameter is set to save the judgment result. If the parameter value is 1, it means that the closed-loop desulfurization efficiency prediction result is greater than the open-loop desulfurization efficiency prediction result; if the parameter value is 0, it means that the closed-loop desulfurization efficiency prediction result is less than the open-loop desulfurization efficiency prediction result. The intelligent terminal confirms the execution strategy by judging the parameter value.

[0032] A control system for a hybrid ship exhaust gas desulfurization device, comprising: a data acquisition module, a determination module, an identification module, a prediction module, and a control module; The data acquisition module is used to obtain the longitude and latitude coordinates of the ship through the AIS unit of the ship, obtain the longitude and latitude coordinate range of the prohibited discharge sea area, obtain the seawater alkalinity data and seawater depth data through the bottom sensor of the ship, and obtain the closed-loop desulfurization device parameters and the open-loop desulfurization device parameters through the built-in sensor of the device; The determination module is used to calculate the determination result through the determination model according to the longitude and latitude coordinates of the ship, the longitude and latitude coordinate range of the prohibited discharge sea area, the seawater alkalinity data, and the seawater depth data; the determination result includes closed-loop operation and continued calculation; The identification module is used to identify according to the determination result. If the determination result is the closed-loop operation, the intelligent terminal executes the first control strategy; if the determination result is the continued calculation, steps S4-S5 are executed; The prediction module is used to calculate the closed-loop pretreatment data through the pretreatment model according to the closed-loop desulfurization device parameters, calculate the open-loop pretreatment data through the pretreatment model according to the open-loop desulfurization device parameters, calculate the closed-loop desulfurization efficiency prediction result through the closed-loop GRNN model according to the closed-loop pretreatment data, and calculate the open-loop desulfurization efficiency prediction result through the open-loop GRNN model according to the seawater alkalinity data and the open-loop pretreatment data; The control module is used to calculate an evaluation result through an evaluation model according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, and the intelligent terminal determines an execution strategy according to the evaluation result.

[0033] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the control method of the hybrid ship exhaust gas desulfurization device as described above when executing the program.

[0034] A storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a control method for a hybrid ship exhaust gas desulfurization device as described above when executed by a computer processor.

[0035] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0036] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0037] The program code contained on the computer-readable medium can be transmitted with any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or a combination thereof, and the programming language includes an object-oriented programming language-such as Java, Smalltalk, C++, and also includes a conventional procedural programming language-such as "C" language or similar programming language. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0038] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A control method for a hybrid ship exhaust gas desulfurization device, characterized in that: include: S1: Obtain the longitude and latitude coordinates of the ship through the ship's AIS unit, obtain the longitude and latitude coordinate range of the prohibited discharge sea area, obtain the seawater alkalinity data and seawater depth data through the ship's bottom sensor, and obtain the closed-loop desulfurization device parameters and open-loop desulfurization device parameters through the device's built-in sensors; S2: Obtaining a determination result through calculation by a determination model according to the longitude and latitude coordinates of the ship, the longitude and latitude coordinate range of the prohibited discharge sea area, the seawater alkalinity data, and the seawater depth data; the determination result includes closed-loop operation and continued calculation; S3 performs identification according to the determination result, and if the determination result is the closed-loop operation, the intelligent terminal executes the first control strategy; If the determination result is to continue calculating, then execute steps S4-S5; S4: according to the closed-loop desulfurization device parameters, the closed-loop pretreatment data are calculated by the pretreatment model, according to the open-loop desulfurization device parameters, the open-loop pretreatment data are calculated by the pretreatment model, according to the closed-loop pretreatment data, the closed-loop desulfurization efficiency prediction result is calculated by the closed-loop GRNN model, and according to the seawater alkalinity data and the open-loop pretreatment data, the open-loop desulfurization efficiency prediction result is calculated by the open-loop GRNN model; S5: obtaining an evaluation result through calculation of an evaluation model according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, and the intelligent terminal determines an execution strategy according to the evaluation result.

2. The control method of the hybrid ship exhaust gas desulfurization device according to claim 1, characterized in that: The judgment model includes judging whether the longitude and latitude coordinates of the ship are within the longitude and latitude coordinate range of the prohibited discharge sea area through a coordinate matching algorithm. If yes, the judgment result is output as the closed-loop operation; if not, the seawater alkalinity threshold is obtained, and a judgment is made based on the seawater alkalinity data and the seawater alkalinity threshold. If the seawater alkalinity data is less than the seawater alkalinity threshold, the judgment result is output as the closed-loop operation; if the seawater alkalinity data is greater than the seawater alkalinity threshold, the seawater depth threshold is obtained, and a judgment is made based on the seawater depth threshold and the seawater depth data. If the seawater depth data is less than the seawater depth threshold, the judgment result is output as the closed-loop operation; if the seawater depth data is greater than the seawater depth threshold, the judgment result is output as the continued calculation.

3. The control method of the hybrid ship exhaust gas desulfurization device according to claim 1, characterized in that: The pretreatment model obtains noise reduction data by filtering according to the closed-loop desulfurization device parameters, obtains correction data by zero-point correction according to the noise reduction data, and obtains the closed-loop pretreatment data by normalization according to the correction data.

4. The control method of the hybrid ship exhaust gas desulfurization device according to claim 1, characterized in that: The evaluation model includes making a judgment based on the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result. If the closed-loop desulfurization efficiency prediction result is greater than the open-loop desulfurization efficiency prediction result, the output evaluation result is the closed-loop operation; if the closed-loop desulfurization efficiency prediction result is less than the open-loop desulfurization efficiency prediction result, the output evaluation result is the open-loop operation.

5. The control method of the hybrid ship exhaust gas desulfurization device according to claim 1, characterized in that: The closed-loop GRNN model consists of an input layer, a pattern layer, a summation layer, and an output layer. The specific calculation steps are: S201: transmitting the closed-loop preprocessing data to the model layer through the input layer; S202: The mode layer calculates the closed-loop pre-processed data through a Gaussian function to obtain Gaussian processed data; S203: the summing layer performs a summing operation on the Gaussian processed data to obtain a summing result; S204: the output layer calculates according to the summation result to obtain prediction data, and obtains the closed-loop desulfurization efficiency prediction result by reverse normalization according to the prediction data.

6. The control method of the hybrid ship exhaust gas desulfurization device according to claim 1, characterized in that: The parameters of the closed-loop desulfurization device include the inlet flue gas volume of the closed-loop desulfurization device, the ammonia concentration of the closed-loop desulfurization device, the absorption liquid concentration of the closed-loop desulfurization device, the liquid-to-gas ratio of the closed-loop desulfurization device, the inlet temperature of the closed-loop desulfurization device, the ammonia consumption of the closed-loop desulfurization device, and the pH value of the slurry in the spray tower of the closed-loop desulfurization device; the parameters of the open-loop desulfurization device include the inlet flue gas volume of the open-loop desulfurization device, the ammonia concentration of the open-loop desulfurization device, the liquid-to-gas ratio of the open-loop desulfurization device, the inlet temperature of the open-loop desulfurization device, the ammonia consumption of the open-loop desulfurization device, and the pH value of the slurry in the spray tower of the open-loop desulfurization device.

7. The control method of the hybrid ship exhaust gas desulfurization device according to claim 1, characterized in that: The execution strategy includes the first control strategy and the second control strategy. The first control strategy is to operate the closed-loop desulfurization device and shut down the open-loop desulfurization device; the second control strategy is to shut down the closed-loop desulfurization device and operate the open-loop desulfurization device.

8. A control system for a hybrid ship exhaust gas desulfurization device, characterized in that: include: Data acquisition module, determination module, identification module, prediction module, control module; The data acquisition module is used to obtain the longitude and latitude coordinates of the ship through the AIS unit of the ship, obtain the longitude and latitude coordinate range of the prohibited discharge sea area, obtain the seawater alkalinity data and seawater depth data through the bottom sensor of the ship, and obtain the closed-loop desulfurization device parameters and the open-loop desulfurization device parameters through the built-in sensor of the device; The determination module is used to calculate the determination result through the determination model according to the longitude and latitude coordinates of the ship, the longitude and latitude coordinate range of the prohibited discharge sea area, the seawater alkalinity data, and the seawater depth data; the determination result includes closed-loop operation and continued calculation; The identification module is used to identify according to the determination result, and if the determination result is the closed-loop operation, the intelligent terminal executes the first control strategy; If the determination result is to continue calculating, then execute steps S4-S5; The prediction module is used to calculate the closed-loop pretreatment data through the pretreatment model according to the closed-loop desulfurization device parameters, calculate the open-loop pretreatment data through the pretreatment model according to the open-loop desulfurization device parameters, calculate the closed-loop desulfurization efficiency prediction result through the closed-loop GRNN model according to the closed-loop pretreatment data, and calculate the open-loop desulfurization efficiency prediction result through the open-loop GRNN model according to the seawater alkalinity data and the open-loop pretreatment data; The control module is used to calculate an evaluation result through an evaluation model according to the closed-loop desulfurization efficiency prediction result and the open-loop desulfurization efficiency prediction result, and the intelligent terminal determines an execution strategy according to the evaluation result.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the control method of the hybrid ship exhaust gas desulfurization device as described in any one of claims 1-7 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the control method of the hybrid ship exhaust gas desulfurization device as described in any one of claims 1 to 7 when executed by a computer processor.

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