An intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships

Abstract

The present invention discloses an intelligent cargo loading and unloading decision-making support system for liquid cargo ships. By collecting liquid level data from cargo and ballast tanks, as well as draft data from the bow and stern, the system calculates the weight of the loaded cargo and ballast water. The system then verifies the ship's stability based on the ship's buoyancy. The system calculates and verifies the ship's structural strength based on the weight of the cargo loaded in each cargo hold and the weight of the ballast water loaded in each ballast tank. A genetic algorithm is used to search for a complete loading and unloading plan, allowing the crew to load and unload cargo according to the output. The present invention intelligently loads cargo based on the planned cargo load, proposes an intelligent loading and unloading decision-making support plan, formulates a loading and unloading plan based on the intelligent loading and unloading decision-making support, and evaluates the time between each step, eliminating the need for full-process monitoring. This significantly reduces the crew's workload and improves the safety of the ship's loading and unloading process.

Description

Technical Field

[0001] The present invention relates to an intelligent cargo loading and unloading system for a liquid cargo ship, and more particularly to an intelligent cargo loading and unloading auxiliary decision-making system for a liquid cargo ship. Background Art

[0002] With growing international environmental awareness, the shipping industry is also raising its environmental standards. In recent years, the SEEMP, EEDI, EEXI, and EEOI have been implemented to encourage shipowners to reduce energy consumption and emissions, enhance energy efficiency management, and lower greenhouse gas emissions. To improve ship energy efficiency, reduce fuel consumption, and lower carbon dioxide emissions, shipping companies are using sails, air lubrication, and other equipment to reduce energy consumption and enhance operational efficiency.

[0003] A smart ship refers to a ship that uses sensors, communications, the Internet of Things, the Internet and other technical means to automatically sense and obtain information and data on the ship itself, the marine environment, logistics, ports, etc., and based on computer technology, automatic control technology and big data processing and analysis technology, it realizes intelligent operation in ship navigation, management, maintenance, cargo transportation, etc., making ships safer, more environmentally friendly, more economical and reliable.

[0004] Currently, the loading and unloading process of liquid cargo ships mainly relies on the first mate to determine which cargo holds or ballast tanks to load or unload based on the real-time floating state, bending moment, and shear force calculation results of the loading computer, and complete the loading or unloading of cargo while ensuring safety. For large ships such as Afra or VLCC, the entire loading and unloading process lasts for more than 24 hours, and the first mate needs to monitor the cargo control room at all times, which is extremely intensive. Summary of the Invention

[0005] To address the above issues, the present invention provides an intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships. It performs intelligent cargo loading according to the planned cargo loading volume, proposes an intelligent loading auxiliary decision-making plan, and evaluates the time between different steps, thereby reducing the labor intensity of the crew and improving the safety of the ship's loading and unloading process.

[0006] The present invention provides an intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships, comprising the following steps:

[0007] S1 collects data

[0008] Bow Port Starboard Draft T FP-acture and T FS-acture ;

[0009] Aft Port Starboard Draft T AP-acture and T AS-acture ;

[0010] Liquid level height of cargo tank (HC1 ,H C2 ...H Cn );

[0011] Ballast tank liquid level (H B1 ,H B2 ...H Bn );

[0012] S2 is calculated based on the collected data

[0013] a) According to the liquid level height of each cargo tank (H C1 ,H C2 ...H Cn ) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn ) to calculate the loaded cargo weight (W C1 ,W C2 ...W Cn ) and loaded ballast water weight (W B1 ,W B2 ...W Bn );

[0014] b) According to each (C1, C2...C n ) Cargo weight loaded in the cargo hold (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) Calculate the floating state of the ship, including the forward draft T F , tail draft T A , trim Tr and heel, each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) calculated from a) or input according to design requirements during the design phase;

[0015] Among them, the trim of the ship is:

[0016]

[0017] The ship's heel is:

[0018]

[0019] c) Check the stability performance of the ship according to the floating state in b);

[0020] d) According to each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) calculate and check the structural strength of the ship, each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) calculated from a) or input according to design requirements during the design phase;

[0021] S3 searches for a complete loading and unloading solution through an algorithmic process

[0022] 1) Variables

[0023] The variables in the loading and unloading auxiliary decision process are the weight of cargo loaded in each cargo hold and the weight of ballast water loaded in each ballast tank;

[0024] 2) Objective function

[0025] Objective function 1:

[0026]

[0027] Objective function 2:

[0028]

[0029] Objective function 3:

[0030]

[0031] Among them, the mathematical model F=f1+f2+f3, when F is smaller, it is closer to the optimization target, T F =f F (W C1 ,W C2 ...W Cn ,WB1 ,W B2 ...W Bn ) represents the first draft function, T A =f A (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ) represents the tail draft function, Heel=f Heel (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ) represents the heel function;

[0032] 3) Constraints

[0033] Constraint 1:

[0034]

[0035] Among them, W C1-i , W C2-i ,...W Cn-i is the loading weight of each cargo hold in the i-th step loading plan, W C1-0 , W C2-0 ,...W Cn-0 is the loading weight of each cargo hold corresponding to the initial state, W C1-final , W C2-final ,...W Cn-final is the cargo hold loading weight corresponding to the final operational loading;

[0036] Constraint 2:

[0037] f A (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )-f F (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )≤0.015L

[0038] Where, L is the captain;

[0039] Constraint 3:

[0040] arcsin[f Heel (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )]≤2.5°

[0041] Constraint 4:

[0042] The stability of the loading scheme is checked by calling the loading computer to ensure that it meets the requirements of IS CODE 2008 of the Association of Classification Societies.

[0043] Constraint 5:

[0044] By calling the loading computer to check whether the hull longitudinal strength and local strength of the loading scheme meet the requirements of the hull design strength;

[0045] 4) The loading and unloading process is divided into 8 intermediate steps. Each step loads and unloads 1 / 8 of the cargo. A loading plan is obtained for each step. The loading plan for each step is optimized using a genetic algorithm.

[0046] a. Matrix variables (W C1 ,W C2 ...W Cn ) and (W B1 ,W B2 ...W Bn ) realize the encoding of chromosomes;

[0047] b. Let the algorithm population be Pareto(t)=[f1(i),f2(i),f3(i)];

[0048] Where t is the current iteration number, i is the loading plan for step i, and the loading plan stepi of this step is optimized;

[0049] c. Randomly create an initial parent population P0 and use crossover and mutation operations to generate a sub-band population Q0;

[0050] d. Perform non-dominated sorting on the entire population R0 composed of P0 and Q0, and construct all non-dominated solution sets Z1, Z2, Z3~Zn of different levels;

[0051] Among them, n represents the sorting number;

[0052] e. Sort the ranked non-dominated solution set by crowding distance, and obtain the top N solutions according to their fitness, which constitute the parent population P1 of the next iteration;

[0053] f. Repeat steps a to e until the results converge. The final converged result is recorded as the loading plan stepi of step i.

[0054] 5) Perform a multi-objective genetic optimization on each loading plan to obtain the loading plans for the eight intermediate steps. The intelligent loading and unloading auxiliary decision software outputs the loading and unloading auxiliary decision, i.e., the loading plans for the eight steps.

[0055] 6) The cargo loading and unloading rates and ballast water loading and unloading rates of the ship are obtained based on the ship's design drawings. The intelligent loading and unloading decision-making support software evaluates the time required between each step based on the differences in the eight-step loading plan and outputs the results.

[0056] Preferably, the bow is provided with one draft measuring sensor on the port side and one on the starboard side, and the stern is provided with one draft measuring sensor on the port side and one on the starboard side, respectively measuring the bow draft T FP-acture and T FS-acture , tail draft T AP-acture and T AS-acture .

[0057] Preferably, liquid level measurement sensors are installed in all cargo tanks and ballast tanks to collect the liquid level height (H C1 ,H C2 ...H Cn ) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn ).

[0058] Preferably, the heel and pitch of the ship are collectively referred to as the floating state, and the draft is measured by a draft measuring sensor to monitor the floating state of the ship.

[0059] Preferably, in step S2, when the trim value of the ship exceeds 0.015 times the ship length, an alarm will be sounded, and when the heel value of the ship exceeds 2.5 degrees, an alarm will be sounded.

[0060] Preferably, in step S2, when the real-time stability of the ship does not meet the requirements of IS CODE 2008 of the Institute of Classification Societies, an alarm is issued.

[0061] Preferably, in step S2, when the real-time longitudinal strength and local strength of the ship's hull do not meet the requirements of the hull design strength, an alarm will be issued.

[0062] Preferably, the crew performs cargo loading and unloading operations according to the 8-step loading plan output in step S3.

[0063] The present invention performs intelligent cargo stowage according to the planned cargo loading volume, proposes an intelligent stowage auxiliary decision-making scheme, formulates a loading and unloading plan based on the intelligent stowage auxiliary decision-making, and evaluates the time between each step. It does not need to monitor the entire process, greatly reducing the crew's workload and improving the safety of the ship's loading and unloading process. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 Example diagrams of initial loading plan / loading plan / operational loading plan;

[0065] Figure 2 Algorithm flow chart. DETAILED DESCRIPTION

[0066] Example

[0067] An intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships comprises the following steps:

[0068] S1 collects data

[0069] Bow Port Starboard Draft T FP-acture and T FS-acture ;

[0070] Aft Port Starboard Draft T AP-acture and T AS-acture ;

[0071] Liquid level height of cargo tank (H C1 ,H C2 ...H Cn );

[0072] Ballast tank liquid level (H B1 ,H B2 ...H Bn );

[0073] S2 is calculated based on the collected data

[0074] a) According to the liquid level height of each cargo tank (H C1 ,H C2 ...H Cn ) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn ) to calculate the loaded cargo weight (W C1 ,W C2 ...W Cn ) and loaded ballast water weight (W B1 ,W B2 ...W Bn );

[0075] b) According to each (C1, C2...C n) Cargo weight loaded in the cargo hold (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) Calculate the floating state of the ship, including the forward draft T F , tail draft T A , trim Tr and heel, each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) calculated from a) or input according to design requirements during the design phase;

[0076] Among them, the trim of the ship is:

[0077]

[0078] The ship's heel is:

[0079]

[0080] c) Check the stability performance of the ship according to the floating state in b);

[0081] d) According to each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) calculate and check the structural strength of the ship, each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) calculated from a) or input according to design requirements during the design phase;

[0082] S3 searches for a complete loading and unloading solution through an algorithmic process

[0083] 1) Variables

[0084] The variables in the loading and unloading auxiliary decision process are the weight of cargo loaded in each cargo hold and the weight of ballast water loaded in each ballast tank;

[0085] 2) Objective function

[0086] Objective function 1:

[0087]

[0088] Objective function 2:

[0089]

[0090] Objective function 3:

[0091]

[0092] Among them, the mathematical model F=f1+f2+f3, when F is smaller, it is closer to the optimization target, T F =f F (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ) represents the first draft function, T A =f A (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ) represents the tail draft function, Heel=f Heel (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ) represents the heel function;

[0093] 3) Constraints

[0094] Constraint 1:

[0095]

[0096] Among them, W C1-i , W C2-i ,...WCn-i is the loading weight of each cargo hold in the i-th step loading plan, W C1-0 , W C2-0 ,...W Cn-0 is the loading weight of each cargo hold corresponding to the initial state, W C1-final , W C2-final ,...W Cn-final is the cargo hold loading weight corresponding to the final operational loading;

[0097] Constraint 2:

[0098] f A (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )-f F (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )≤0.015L

[0099] Where, L is the captain;

[0100] Constraint 3:

[0101] arcsin[f Heel (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )]≤2.5°

[0102] Constraint 4:

[0103] The stability of the loading scheme is checked by calling the loading computer to ensure that it meets the requirements of IS CODE 2008 of the Association of Classification Societies.

[0104] Constraint 5:

[0105] By calling the loading computer to check whether the hull longitudinal strength and local strength of the loading scheme meet the requirements of the hull design strength;

[0106] 4) The loading and unloading process is divided into 8 intermediate steps. Each step loads and unloads 1 / 8 of the cargo. A loading plan is obtained for each step. The loading plan for each step is optimized using a genetic algorithm.

[0107] a. Matrix variables (WC1 ,W C2 ...W Cn ) and (W B1 ,W B2 ...W Bn ) realize the encoding of chromosomes;

[0108] b. Let the algorithm population be Pareto(t)=[f1(i),f2(i),f3(i)];

[0109] Where t is the current iteration number, i is the loading plan for step i, and the loading plan stepi of this step is optimized;

[0110] c. Randomly create an initial parent population P0 and use crossover and mutation operations to generate a sub-band population Q0;

[0111] d. Perform non-dominated sorting on the entire population R0 composed of P0 and Q0, and construct all non-dominated solution sets Z1, Z2, Z3~Zn of different levels;

[0112] Among them, n represents the sorting number;

[0113] e. Sort the ranked non-dominated solution set by crowding distance, and obtain the top N solutions according to their fitness, which constitute the parent population P1 of the next iteration;

[0114] f. Repeat steps a to e until the results converge. The final converged result is recorded as the loading plan stepi of step i.

[0115] 5) Perform a multi-objective genetic optimization on each loading plan to obtain the loading plans for the eight intermediate steps. The intelligent loading and unloading auxiliary decision software outputs the loading and unloading auxiliary decision, i.e., the loading plans for the eight steps.

[0116] 6) The cargo loading and unloading rates and ballast water loading and unloading rates of the ship are obtained based on the ship's design drawings. The intelligent loading and unloading decision-making support software evaluates the time required between each step based on the differences in the eight-step loading plan and outputs the results.

[0117] The bow is equipped with one draft measuring sensor on the port and starboard sides, and the stern is equipped with one draft measuring sensor on the port and starboard sides, respectively, to measure the bow draft T FP-acture and T FS-acture , tail draft T AP-acture and T AS-acture .

[0118] Liquid level measurement sensors are installed in all cargo tanks and ballast tanks to collect the liquid level height (H C1 ,H C2 ...H Cn) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn ).

[0119] The ship's heel and pitch are collectively referred to as the floating state. The draft is measured by a draft measurement sensor to monitor the ship's floating state.

[0120] In step S2, when the trim value of the ship exceeds 0.015 times the ship length, an alarm will be triggered; when the heel value of the ship exceeds 2.5 degrees, an alarm will be triggered.

[0121] In step S2, when the real-time stability of the ship does not meet the requirements of IS CODE 2008 of the Institute of Classification Societies, an alarm will be issued.

[0122] In step S2, when the real-time longitudinal strength and local strength of the ship's hull do not meet the requirements of the hull design strength, an alarm will be issued.

[0123] The crew performs cargo loading and unloading operations according to the 8-step loading plan output in step S3.

[0124] The present invention will be further described below with reference to the accompanying drawings.

[0125] 1. The system consists of hardware and software. The hardware includes draft measurement sensors and liquid level measurement sensors. The software includes loading computer software and intelligent loading and unloading auxiliary decision software.

[0126] 1) One draft measuring sensor is arranged on the port and starboard sides of the bow, and one draft measuring sensor is arranged on the port and starboard sides of the stern to measure the bow draft T FP-acture and T FS-acture , tail draft T AP-acture and T AS-acture ;

[0127] The trim of the ship is:

[0128]

[0129] The ship's heel is:

[0130]

[0131] The heel and pitch of a ship are collectively referred to as its floating state. Draught measurement sensors are used to measure the draft and thus monitor the ship's floating state.

[0132] 2) Liquid level measurement sensors are installed in all cargo tanks and ballast tanks to collect the liquid level height (H C1 ,H C2 ...H Cn) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn );

[0133] 3) Cargo loading and unloading: The process of loading and unloading cargo and ballast water transforms the ship's initial loading plan into the operational loading plan. The process of increasing the ship's cargo weight is called loading, and the process of reducing it is called unloading. The intelligent loading and unloading decision-making support software targets the operational loading plan and provides eight intermediate stowage plans, ensuring stability and structural strength meet requirements. These eight intermediate stowage plans are called loading and unloading decision support.

[0134] ①The initial loading plan refers to the final loading plan of each cargo hold (C1, C2...C n ) and ballast tanks (B1, B2...B n ) their respective loading weights. The operational loading plan for a vessel on a voyage is as follows: Figure 1 As shown in the first column initial, the C1 cargo hold is loaded with 0 tons of cargo, the C2 cargo hold is loaded with 0 tons of cargo, the C3 cargo hold is loaded with 0 tons of cargo, etc.; the B1 ballast tank is loaded with 0 tons of ballast water, the B2 ballast tank is loaded with 0 tons of ballast water, and the B3 ballast tank is loaded with 4,000 tons of ballast water, etc.;

[0135] ② Operational loading plan refers to the shipping company's plan for the final cargo holds (C1, C2...C n ) and ballast tanks (B1, B2...B n ) their respective loading weights. The operational loading plan for a vessel on a voyage is as follows: Figure 1 As shown in the last column of final, the C1 cargo hold is loaded with 0 tons of cargo, the C2 cargo hold is loaded with 0 tons of cargo, the C3 cargo hold is loaded with 5,000 tons of cargo...; the B1 ballast tank is loaded with 200 tons of ballast water, the B2 ballast tank is loaded with 200 tons of ballast water, the B3 ballast tank is loaded with 0 tons of ballast water...;

[0136] ③ Loading plan refers to the loading process of each cargo hold (C1, C2...C n ) and ballast tanks (B1, B2...B n ) respective loading weights, such as Figure 1 As shown in step 1 to step 8 in the loading plan, step 2 of the loading plan means that the C1 cargo hold is loaded with 0 tons of cargo, the C2 cargo hold is loaded with 0 tons of cargo, the C3 cargo hold is loaded with 2,000 tons of cargo, etc.; the B1 ballast tank is loaded with 200 tons of ballast water, the B2 ballast tank is loaded with 200 tons of ballast water, and the B3 ballast tank is loaded with 3,500 tons of ballast water, etc.

[0137] 4) The loading computer software adopts mature products currently on the market (such as NAPA's loading computer software). The software functions of the loading computer include:

[0138] a) According to the liquid level height of each cargo tank (H C1 ,H C2 ...H Cn ) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn ) to calculate the loaded cargo weight (W C1 ,W C2 ...W Cn ) and loaded ballast water weight (W B1 ,W B2 ...W Bn ):

[0139] b) According to each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) Calculate the floating state of the ship, including the forward draft T F , tail draft T A , longitudinal inclination Tr and transverse inclination Heel. Among them, each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) is calculated from a) and can also be obtained by direct input;

[0140] c) Check the stability performance of the ship according to the floating state in c);

[0141] d) According to each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,WB2 ...W Bn ) calculates and verifies the structural strength of the ship. Among them, each cargo hold (C1, C2...C n ) Loaded cargo weight (W C1 ,W C2 ...W Cn ) and each ballast tank (B1, B2...B n ) Ballast water weight loaded (W B1 ,W B2 ...W Bn ) is calculated from a) and obtained by direct input;

[0142] 2. Based on the operational loading plan, calculate the ship's forward draft T by loading computer software. F-final , tail draft T A-final , pitch Tr final and Heel final , where Tr final =T A-final -T F-final There are three optimization objectives. The process from the initial loading plan to the operational loading plan is a multi-objective optimization process. A multi-objective genetic algorithm is used to analyze and solve multi-objective optimization problems. Its core goal is to coordinate the relationships between the various objective functions and find the optimal solution set that maximizes (or minimizes) the value of each objective function. The NAGA-II algorithm is the most influential and widely used multi-objective genetic algorithm. Its basic principles are described in the paper "NSGA-II Algorithm and Its Improvements."

[0143] 3. The optimization process of intelligent loading and unloading auxiliary decision software for loading and unloading auxiliary decision is compiled in C++ software using the NAGA-II algorithm.

[0144] 1) Variables

[0145] The variables in the loading and unloading auxiliary decision process are the weight of cargo loaded in each cargo hold (W C1 ,W C2 ...W Cn ) and the weight of ballast water loaded in each ballast tank (W B1 ,W B2 ...W Bn )

[0146] 2) Objective function

[0147] Assume that the weight of cargo loaded in each cargo hold in a loading scheme m (W C1-m ,W C2-m ...W Cn-m ) and the weight of ballast water loaded in each ballast tank (WB1-m ,W B2-m ...W Bn-m ), calculate the first draft T corresponding to the loading scheme m through the loading computer software F-m , tail draft T A-m and Heel final-m Therefore, the first draft T F , tail draft T A , and heel Heel are all expressed by functions T F =f F (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ), tail draft T A =f A (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn ), and Heel = f Heel (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )

[0148] There are three optimization objective functions in this optimization process:

[0149] Objective function 1:

[0150]

[0151] Objective function 2:

[0152]

[0153] Objective function 3:

[0154]

[0155] The mathematical model of this project is F=f1+f2+f3. The smaller F is, the closer it is to the optimization goal.

[0156] 3) Constraints

[0157] Constraint 1:

[0158]

[0159] Among them, WC1-i , W C2-i ,...W Cn-i is the loading weight of each cargo hold in the i-th step loading plan;

[0160] W C1-0 , W C2-0 ,...W Cn-0 is the loading weight of each cargo hold corresponding to the initial state;

[0161] W C1-final , W C2-final ,...W Cn-final is the cargo hold loading weight corresponding to the final operational loading;

[0162] Constraint 2:

[0163] f A (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )-f F (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )≤0.015L

[0164] Where: L is the captain;

[0165] Constraint 3:

[0166] arcsin[f Heel (W C1 ,W C2 ...W Cn ,W B1 ,W B2 ...W Bn )]≤2.5°

[0167] Constraint 4:

[0168] The stability of this loading scheme meets the requirements of IS CODE 2008 (checked by calling the loading computer)

[0169] Constraint 5:

[0170] The overall longitudinal strength and local strength of the hull of this loading scheme meet the requirements of the hull design strength (checked by calling the loading computer)

[0171] 4) The loading and unloading process is divided into 8 intermediate steps. Each step loads and unloads 1 / 8 of the cargo. A loading plan is obtained for each step. The loading plan for each step is optimized using a genetic algorithm. The algorithm flow is as follows: Figure 2 As shown:

[0172] a. Matrix variables (W C1 ,W C2 ...W Cn ) and (W B1 ,W B2 ...W Bn ) realize the encoding of chromosomes;

[0173] b. Let the algorithm population be Pareto(t)=[f1(i),f2(i),f3(i)]. Where t is the current iteration number, i is the loading plan for step i, and the loading plan for this step is optimized.

[0174] c. Randomly create an initial parent population P0 and use crossover and mutation operations to generate a sub-band population Q0;

[0175] d. Perform non-dominated sorting on the entire population R0 composed of P0 and Q0, and construct all non-dominated solution sets Z1, Z2, Z3...

[0176] e. Sort the non-dominated solution sets by crowding distance, and get the top N solutions according to their fitness, which constitute the parent population P1 for the next iteration.

[0177] f. Repeat steps a to e until the results converge. The final converged result is recorded as the loading plan for step i.

[0178] g. Perform a multi-objective genetic optimization on each loading plan to obtain the loading plan for the 8 intermediate steps. The intelligent loading and unloading auxiliary decision software outputs the loading and unloading auxiliary decision, i.e. the loading plan for the 8 steps, such as Figure 1 As shown in step 1 to step 8;

[0179] 5) The cargo loading and unloading rates and ballast water loading and unloading rates of the ship are obtained based on the ship's design drawings. The intelligent loading and unloading decision-making support software evaluates the time required for each step based on the differences in the eight-step stowage plan and outputs the results;

[0180] 4. The crew performs loading and unloading operations according to the 8-step loading auxiliary decision-making plan output in step 3;

[0181] 5. During loading and unloading, the draft measurement sensor will collect the first draft T in real time. FP 、T FS and tail draft T AP 、TAS :

[0182] 1) Trim of the ship:

[0183]

[0184] According to the requirements of IS CODE 2008, the trim value of a ship should not exceed 0.015 times the ship length. r If the requirements of IS CODE 2008 are not met, the decision support system software will issue an alarm.

[0185] 2) List of the ship:

[0186]

[0187] When the heel exceeds 2.5 degrees, the decision support system software will issue an alarm.

[0188] 6. During the loading and unloading process, the liquid level measurement sensor will collect the liquid level height (H C1 ,H C2 ...H Cn ) and the liquid level of the ballast tank (H B1 ,H B2 ...H Bn ) is input into the loading computer software for stability and structural strength verification:

[0189] 1) When the ship's real-time stability does not meet the requirements of the Association of Classification Societies' IS CODE 2008, the decision-making support system software will issue an alarm;

[0190] 2) When the real-time longitudinal strength and local strength of the ship's hull do not meet the requirements of the hull design strength, the auxiliary decision-making system software will alarm.

[0191] The present invention performs intelligent cargo stowage according to the planned cargo loading volume, proposes an intelligent stowage auxiliary decision-making scheme, formulates a loading and unloading plan based on the intelligent stowage auxiliary decision-making, and evaluates the time between each step. It does not need to monitor the entire process, greatly reducing the crew's workload and improving the safety of the ship's loading and unloading process.

[0192] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. An intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships, characterized in that: The steps include: S1 collects data Bow Port Starboard Draft and ; Aft Port Starboard Draft and ; Liquid level in cargo tanks ; Ballast tank liquid level ; S2 is calculated based on the collected data a) According to the liquid level height of each cargo tank and the liquid level of the ballast tanks Calculate the weight of loaded cargo and loaded ballast water weight ; b) According to each Weight of cargo loaded in the cargo hold and various ballast tanks Weight of ballast water loaded Calculate the ship's floating state, including the forward draft , tail draft , pitch and heel , each cargo hold Loaded cargo weight and various ballast tanks Weight of ballast water loaded Obtained by calculation in a) or input according to design requirements during the design stage; Among them, the trim of the ship is: The ship's heel is: c) Check the stability performance of the ship according to the floating state in b); d) According to each cargo hold Loaded cargo weight and various ballast tanks Weight of ballast water loaded Calculate and verify the structural strength of the ship, each cargo hold Loaded cargo weight and various ballast tanks Weight of ballast water loaded Obtained by a) calculation or determined according to the design during the design stage; S3 searches for a complete loading and unloading solution through an algorithmic process, including: 1) Variables The variables in the loading and unloading auxiliary decision process are the weight of cargo loaded in each cargo hold and the weight of ballast water loaded in each ballast tank; 2) Objective function Objective function 1: Objective function 2: Objective function 3: Among them, the mathematical model , when F is smaller, it is closer to the optimization goal, represents the first draft function, represents the tail draft function, represents the heel function; 3) Constraints Constraint 1: in, is the loading weight of each cargo hold in the i-th step loading plan, is the loading weight of each cargo hold corresponding to the initial state, is the loading weight of each cargo hold corresponding to the final operational loading; Constraint 2: Where, L is the captain; Constraint 3: Constraint 4: The stability of the loading plan must meet the requirements of IS CODE 2008; Constraint 5: Check that the hull's longitudinal strength and local strength of the loading scheme meet the hull's design strength requirements; 4) The loading and unloading process is divided into 8 intermediate steps. Each step loads and unloads 1 / 8 of the cargo. A loading plan is obtained for each step. The loading plan for each step is optimized using a genetic algorithm. a. Matrix variables and Implement chromosome encoding; b. Let the algorithm population be ; Where t is the current iteration number, i is the loading plan for step i, and the loading plan stepi of this step is optimized; c. Randomly create an initial parent population P0 and use crossover and mutation operations to generate a child population Q0; d. Perform non-dominated sorting on the entire population R0 composed of P0 and Q0, and construct all non-dominated solution sets Z1, Z2, Z3~Zn of different levels; where n represents the sorting number; e. Sort the ranked non-dominated solution set by crowding distance, and obtain the top N solutions according to their fitness, which constitute the parent population P1 of the next iteration; f. Repeat steps a to e until the results converge. The final converged result is recorded as the loading plan stepi of step i. 5) Perform a multi-objective genetic optimization on each loading plan to obtain the loading plans for the eight intermediate steps. The intelligent loading and unloading auxiliary decision software outputs the loading and unloading auxiliary decision, i.e., the loading plans for the eight steps. 6) Obtain the cargo loading and unloading rate and ballast water loading and unloading rate of the ship based on the design drawings of the ship, as well as the differences in the loading schemes of the eight intermediate steps, evaluate the time required between each step, and output the optimal loading.

2. The intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships according to claim 1, characterized in that: The bow is provided with one draft measuring sensor on the port and starboard sides, and the stern is provided with one draft measuring sensor on the port and starboard sides, respectively, to measure the bow draft. and tail draft and .

3. The intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships according to claim 1 is characterized in that: Liquid level measurement sensors are installed in all cargo tanks and ballast tanks to collect the liquid level height of each cargo tank. and the liquid level of the ballast tanks .

4. The intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships according to claim 1, characterized in that: The draft is measured by the draft measurement sensor to monitor the floating state of the ship.

5. The intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships according to claim 1, characterized in that: In step S2, when the trim value of the ship exceeds 0.015 times the ship length, an alarm will be triggered; when the heel value of the ship exceeds 2.5 degrees, an alarm will be triggered.

6. The intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships according to claim 1, characterized in that: In step S2, when the real-time stability of the ship does not meet the requirements of IS CODE 2008 of the Institute of Classification Societies, an alarm will be issued.

7. The intelligent cargo loading and unloading auxiliary decision-making system for liquid cargo ships according to claim 1, characterized in that: In step S2, when the real-time longitudinal strength and local strength of the ship's hull do not meet the requirements of the hull design strength, an alarm will be issued.

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