Intelligent assembly loading control system of geotextile laying ship

Abstract

The invention discloses an intelligent assembly loading control system of a geotextile laying ship, and belongs to the technical field of ship intelligent control. According to the invention, through the intelligent stowage planning module, based on standardized scheme matching and an adaptive optimization algorithm, objectives of balanced material distribution, shortest conveying path and ship stress rationalization are realized, stowage precision is improved, and sailing stability is optimized; the operation scheduling and arranging module dynamically generates an efficient operation time sequence graph through real-time cabin state recognition, process decomposition, operation time sequence optimization and remote cooperative control, precise scheduling is achieved, manual intervention is reduced, the automatic operation execution module is combined with real-time monitoring, abnormal early warning and intelligent feedback, the safety and adaptability of the operation process are ensured, and the working efficiency is improved. According to the method, loading deviation overrun and ballast abnormity are avoided, the decision-making capacity of the system is continuously optimized, manual operation errors are effectively reduced, the safety and economical efficiency of ship operation are improved, and green, energy-saving and efficient operation is helped to be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of ship intelligent control, and in particular to an intelligent assembly loading control system for a laying ship. Background Art

[0002] In the field of modern marine engineering and shipping, laying vessels are widely used in underwater pipeline laying, submarine cable laying, marine resource development and other operations. However, the loading and operation scheduling of traditional laying vessels mainly rely on manual experience, and there are the following problems: The optimization capability of loading plan is limited. Manually formulated loading plans often fail to take into account balanced distribution of materials, shortest conveying path and hull stability control, which may easily lead to problems such as ship pitch, heel and uneven force, affecting operation safety. The operation scheduling efficiency is low. The current operation scheduling mainly relies on manual command, which is difficult to dynamically adjust according to the real-time status of the cabin and changes in the external environment, resulting in low efficiency of loading and unloading operations and affecting the overall construction progress; The automated control and intelligent monitoring capabilities are insufficient. The existing system lacks automated execution and real-time monitoring methods, and is unable to effectively identify abnormal operating conditions and take countermeasures, posing a high operational risk. Summary of the invention

[0003] The object of the present invention is to provide an intelligent assembly loading control system for a laying vessel to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: an intelligent assembly loading control system for a laying ship, comprising: Intelligent load planning module for: Receive external input of intelligent loading instructions containing loading constraints, evaluate the real-time working conditions of the laying tank and balance water tank of the laying ship, and generate a set of candidate loading solutions that meet the optimization objectives, with balanced distribution of laying materials, shortest laying material transportation path, optimization of navigation stability parameters and rationalization of hull force as optimization goals; Implementation plan selection module, used to: Establish data interaction with the intelligent loading planning module, perform multi-criteria evaluation on the candidate loading scheme set according to the preset optimization index priority system and in combination with real-time navigation parameters, and select the final execution scheme, wherein the real-time navigation parameters include meteorological and hydrological conditions and operation task characteristics; Job scheduling module, used for: It works in conjunction with the execution plan selection module to obtain and compare the current actual loading status of the laying ship based on the expected loading form of the final execution plan, and generates a scheduling instruction set including the cabin operation sequence, equipment operation parameters and process time nodes in combination with the loading constraints; Automated job execution module for: It works in coordination with the operation scheduling module, analyzes the scheduling instruction set and converts it into control signals, drives the material distribution conveyor, ballast adjustment unit and actuator, realizes precise material loading and unloading operations and balance water regulation, and finally achieves the predetermined loading state; Loading knowledge repository for: Establish a data channel with the intelligent loading planning module, preset standardized loading rules and corresponding typical solution library, and store historical optimization parameters and constraint condition data sets.

[0005] Furthermore, the intelligent loading planning module includes: Solution matching unit, used to: Receive intelligent loading instructions and parse loading constraints contained in the intelligent loading instructions, wherein the loading constraints include cabin availability, loading balance requirements, and ballast water control requirements; Retrieve the standardized loading scheme that matches the loading constraint conditions in the loading knowledge repository, and compare the applicable scope, tank capacity matching degree and historical execution effect of the scheme; if there is a standardized loading scheme that meets the requirements, output the standardized loading scheme as a preliminary scheme and enter the stability verification unit for scheme verification; if there is no matching scheme, send a dynamic optimization instruction to the dynamic optimization unit; Dynamic optimization unit for: After connecting with the solution matching component and triggering the dynamic optimization command, it generates the loading scheme by using the adaptive optimization algorithm based on the material tank tolerance, compartment load distribution and hull deformation restriction conditions, with multiple objectives such as simplified transportation path, balanced compartment load and minimum ballast control. Stability verification unit, used for: Receive the loading scheme from the scheme matching unit and the dynamic optimization unit, and calculate the key stability parameters of the trim angle, heel angle, hull shear force and bending moment under the loading scheme; The calculation results are compared with the preset safety thresholds. If all parameters are within the safety range, the final execution plan is submitted to the execution plan selection module; if there are out-of-limit parameters, correction instructions are fed back to the dynamic optimization unit and the optimization calculation is re-executed.

[0006] Furthermore, the solution matching unit includes: The data retrieval subunit is used to obtain the full-process execution parameters of each assembly load of the laying ship within a preset historical time period, and divide the full-process execution parameters into nodes based on the execution items of the assembly load of the laying ship; A data processing subunit, for: Based on the node division results, the execution details of each execution project and the execution results corresponding to the execution details are obtained, and the execution details are analyzed by parameters to obtain the material distribution and state characteristics of each execution project in the loading phase and the material position and storage change characteristics in the unloading phase; At the same time, the execution results of each execution rule are traversed to obtain the execution qualification of each execution project under the execution rule. When the execution qualification is less than the preset threshold, the full-process execution parameters of the assembly corresponding to the current execution project are eliminated, and the key focus of the execution project is determined based on the elimination results; Otherwise, the configuration parameters of the laying ship corresponding to the full process execution parameters of each assembly loading are obtained based on the management terminal; Associate the material distribution and state characteristics of each execution project in the loading phase, the material position and storage change characteristics in the unloading phase, and the key points of the execution project with the configuration parameters of the laying ship; The stowage knowledge repository builds subunits for: Building a distributed cache interval based on the association result, and caching the association result in the distributed cache interval; Generate a header tag based on the cached results and the configuration parameters of the laying ship. Generate a structure tag based on the material distribution and state characteristics of each execution project in the loading phase, the material position and storage change characteristics in the unloading phase, and the key concerns of the execution project. Generate a guide table of the stowage knowledge repository based on the association between the header tag and the structure tag. The guide table is added in the distributed cache interval to obtain the final loading knowledge repository.

[0007] Furthermore, the execution scheme selection module includes an interactive unit for visually presenting the technical parameters and three-dimensional simulation effects of the candidate loading scheme set, and supports manual modification of the technical parameters of the candidate loading scheme set or direct selection of the final execution scheme.

[0008] Furthermore, the job scheduling module includes: Space screening unit for: Identify the real-time loading rate and loading status of the cabin of the laying ship, the cabin loading status includes the loading rate of the laying tank, the material type and the water level information of the ballast tank, analyze the expected loading form in the final execution plan, determine the loading demand of the target cabin and extract the loading constraint conditions, compare the current loading state with the target loading form, select the cabin that meets the loading constraint conditions, take the cabin that meets the conditions as the operation target cabin, filter the cabin that does not meet the conditions, and output the data of the operation target cabin; Process decomposition unit, used for: Based on the data of the target cabin, calculate the loading and unloading changes of the laying tank and ballast tank, and determine the material flow direction and ballast adjustment requirements of the cabin. According to the preset deviation threshold, divide the overall operation process into multiple operation stage levels. For each operation stage level, determine the operating parameter range of the key execution equipment, which includes the target flow of the conveying equipment and the water adjustment rate of the ballast system, and output the decomposed process data; Timing generation unit, used to: Receive the output data of the process decomposition unit, build an operation timing optimization model based on the loading constraints, and use a heuristic algorithm to calculate the space operation priority, generate an operation timing map including the space operation priority, loading and unloading volume, transportation parameters, transportation rate and time window, and output the operation timing map; Remote collaboration unit for: The job timing map is pushed to the console through the Internet of Things system, and supports real-time data interaction, analyzes the manual correction instructions entered by the user, and dynamically adjusts the job timing map. After the adjustment is completed, the final scheduling instructions are sent to the automated job execution module.

[0009] Furthermore, the automated operation execution module includes a collaborative control unit for receiving an operation timing diagram, parsing the operation timing diagram and generating device drive instructions, and synchronously coordinating the linkage operation of the material distribution conveyor, the ballast pump group and the auxiliary actuators.

[0010] Furthermore, the automated operation execution module also includes a working condition feedback unit, which is used to collect hull posture, cabin load and equipment operation data through distributed sensors, and trigger an early warning mechanism and start a dynamic compensation program when an over-limit deviation is detected.

[0011] Furthermore, an intelligent assembly loading control system for a laying vessel also includes an operation timing database for storing standard operation timing diagram templates, wherein the operation timing diagram templates are used to accelerate the efficiency of generating a scheduling plan.

[0012] Furthermore, an intelligent loading control system for a laying vessel also includes a data analysis module for dynamically optimizing the loading knowledge repository and iteratively upgrading the system decision-making capabilities by mining pattern features in historical operation data.

[0013] Furthermore, an intelligent assembly loading control system of a laying ship, an automated operation execution module, also includes: The parameter reading unit is used to read the navigation parameters before driving the material conveying device, the ballast regulating unit and the actuator, determine the density of the water in the waters where the laying ship is located and the length of the laying ship, and monitor the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the waters; The first calculation unit is used to calculate the wave interference force of the laying ship on the horizontal axis and the wave interference force of the laying ship on the vertical axis according to the density of water in the water area where the laying ship is located, the length of the laying ship, and the angle formed by the horizontal plane when the hull meets the waves in the water area; ; in, F 1 represents the wave disturbance force on the horizontal axis of the laying ship; r Indicates the density of water in the waters where the current laying ship is located; L Indicates the length of the laying ship; s Indicates the average amplitude of the waves; f It indicates the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the water area; i Indicates the frequency sequence of regular waves in water waves; n Represents the total number of regular waves of different frequencies; m 1 represents the wave drift coefficient of the water area wave on the horizontal axis; m 2 represents the wave drift coefficient of the water area waves on the ordinate axis; l Indicates the wavelength of waves in a body of water; s i Indicated in i The average amplitude of a regular wave of frequency; F 2 represents the wave disturbance force of the laying ship on the ordinate axis; cos (∙) represents the cosine function; The second computing unit is configured to: Collect the target angle of the wave disturbance force of the laying ship on the horizontal axis and the wave disturbance force of the laying ship on the vertical axis i ; According to the wave disturbance force of the laying ship on the horizontal axis, the wave disturbance force of the laying ship on the vertical axis and the target angle i , construct the water area wave disturbance force model; ; in, F 干扰 Represents the water area wave disturbance force model; A determination unit, for: Calculate the wave disturbance force of the target water area of ​​the laying ship in real time according to the water area wave disturbance force model; Obtaining a preset wave disturbance force threshold, and comparing the wave disturbance force of the target waters of the laying ship with the preset wave disturbance force threshold, to determine whether the current laying ship meets the working conditions; When the wave disturbance force in the target waters of the laying ship is less than the preset wave disturbance force threshold, it is determined that the current laying ship meets the working conditions. At the same time, the material conveying device, ballast adjustment unit and actuator are driven to achieve precise material loading and unloading operations and balance water regulation; Otherwise, it is determined that the current laying ship meets the working conditions, and a stop work instruction is generated to control the laying ship to stop working.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention effectively improves the intelligent loading level of the laying ship through the intelligent loading planning module, combined with standardized scheme matching and dynamic optimization calculation. In the loading process, it comprehensively evaluates the cabin availability, load balancing requirements, and ballast water control requirements, automatically matches the historical optimal loading plan, and dynamically generates a loading plan based on a multi-objective adaptive optimization algorithm when there is no matching plan. It fully considers core factors such as cabin capacity utilization, shortest material transportation path, optimization of navigation stability parameters, and rationalization of hull force, so that material loading is more balanced, reduces the problems of ship tilting and uneven load distribution, significantly reduces loading errors, improves loading accuracy, and reduces the stability risk of ships during navigation and operation, thereby improving the safety and economic benefits of ship operation.

[0015] 2. The job scheduling and choreography module of the present invention combines real-time cabin status identification, process decomposition, job timing optimization and remote collaborative control to greatly improve the automated operation capability of the laying ship, monitor the cabin loading rate, material type, ballast water status and other key parameters in real time, and calculate the loading and unloading changes, material flow direction and ballast adjustment requirements of each cabin according to the final loading plan, dynamically generate cabin operation sequence, conveying rate, equipment operating parameters and time window, form an efficient job timing map, and interact with the control console through the remote collaborative unit to realize remote push and dynamic adjustment of scheduling instructions, ensure the flexibility and controllability of the operation process, effectively reduce manual intervention, improve the executability and accuracy of the operation plan, reduce operation delays, and optimize ship operation efficiency.

[0016] 3. The automated operation execution module of the present invention is equipped with a collaborative control unit and a working condition feedback unit to realize intelligent monitoring, abnormal warning and dynamic compensation functions of the operation process. During the operation execution process, core data such as hull posture, cabin load, equipment operating status, etc. are collected in real time, and an operation condition model is constructed based on a distributed sensor network. Through the operation time series database and data analysis module, it is possible to mine the pattern characteristics of historical operation data, optimize the loading knowledge repository, and continuously iterate and upgrade the system decision-making ability, so that ship operations can adapt to different working conditions, improve the safety and economy of long-term operation, realize accurate real-time monitoring and intelligent feedback, and significantly improve the safety, reliability and adaptability of laying ship operations.

[0017] 4. The present invention obtains the full-process execution parameters of each assembly load of the laying ship within a preset historical time period, and processes and analyzes the full-process execution parameters of each assembly load, so as to effectively determine the material distribution and state characteristics of each execution project in the loading stage, the material position and storage change characteristics in the unloading stage, and the key focus points of the execution project under different conditions, thereby providing reliable data support for the construction of a loading knowledge repository. Secondly, the above-mentioned information is associated with the configuration parameters of the laying ship, and the associated results are cached in the constructed distributed cache interval. At the same time, a corresponding guidance table is generated for each reference item according to the cached results, and is bound to the distributed cache interval, thereby finally realizing the accurate and effective construction of the loading knowledge repository, which provides convenience and guarantee for the intelligent assembly load control of the laying ship.

[0018] 5. By determining the density of water in the water area where the laying ship is located, the length of the laying ship, and the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the water area, the wave interference force of the laying ship on the horizontal axis and the wave interference force of the laying ship on the vertical axis can be effectively calculated, so as to accurately construct a water area wave interference force model, which is conducive to effectively calculating the target water area wave interference force of the current laying ship through the water area wave interference force model, and then effectively judging whether the current laying ship meets the working conditions through the preset wave interference force threshold. When the working conditions are not met, the laying ship is controlled to stop working, which ensures the safety and effectiveness of the laying ship's work and provides safety guarantee for the laying ship to carry out assembly and loading. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the intelligent loading control system module of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] See also Figure 1 , the present invention provides the following technical solutions: An intelligent assembly loading control system for a laying ship, comprising: Intelligent load planning module for: Receive external input of intelligent loading instructions containing loading constraints, evaluate the real-time working conditions of the laying tank and balance water tank of the laying ship, and generate a set of candidate loading solutions that meet the optimization objectives, with balanced distribution of laying materials, shortest laying material transportation path, optimization of navigation stability parameters and rationalization of hull force as optimization goals; Implementation plan selection module, used to: Establish data interaction with the intelligent loading planning module, perform multi-criteria evaluation on the candidate loading scheme set according to the preset optimization index priority system and in combination with real-time navigation parameters, and select the final execution scheme, wherein the real-time navigation parameters include meteorological and hydrological conditions and operation task characteristics; Job scheduling module, used for: It works in conjunction with the execution plan selection module to obtain and compare the current actual loading status of the laying ship based on the expected loading form of the final execution plan, and generates a scheduling instruction set including the cabin operation sequence, equipment operation parameters and process time nodes in combination with the loading constraints; Automated job execution module for: It works in coordination with the operation scheduling module, analyzes the scheduling instruction set and converts it into control signals, drives the material distribution conveyor, ballast adjustment unit and actuator, realizes precise material loading and unloading operations and balance water regulation, and finally achieves the predetermined loading state; Loading knowledge repository for: Establish a data channel with the intelligent loading planning module, preset standardized loading rules and corresponding typical solution library, and store historical optimization parameters and constraint condition data sets; Job timing database, used for: Storing a standard job timing diagram template, wherein the job timing diagram template is used to accelerate the efficiency of generating a scheduling plan; Data analysis module for: By mining the pattern features in historical operation data, the loading knowledge repository is dynamically optimized and the system decision-making capabilities are iteratively upgraded.

[0022] In the above embodiment, through the intelligent loading planning module, the system can comprehensively evaluate the cabin status, navigation stability and material transportation path, and automatically generate a set of candidate loading schemes that meet the optimization objectives, so as to achieve accurate and efficient loading planning. By adopting a dynamic optimization algorithm, when the standard scheme cannot meet the constraints, it can adaptively generate an optimization scheme to improve the flexibility and adaptability of the system. In combination with meteorological and hydrological conditions, the real-time operating conditions of the ship and other factors, the execution scheme selection module can perform multi-criteria evaluation on multiple candidate schemes to ensure the safety, economy and operational feasibility of the final scheme. It supports manual intervention through a visual interface to improve the controllability and user-friendliness of the system.

[0023] In the above embodiment, through the job scheduling and choreography module, the system can carry out fine-grained choreography of the cabin operations of the laying ship, including cabin screening, process decomposition, timing optimization, etc., to achieve efficient loading operation management, and use heuristic algorithms to optimize the operation sequence, reduce operation conflicts, and improve overall operation efficiency. The automated operation execution module can accurately drive equipment such as the cloth conveying device and the ballast adjustment unit to ensure the accurate execution of loading and ballast adjustment and reduce manual operation errors. Through the working condition feedback unit, the system can monitor the hull posture and cabin load conditions in real time, and trigger early warning and dynamic compensation mechanisms when exceeding the limit, thereby improving operation safety.

[0024] In the above embodiment, through the data analysis module, the system can mine the pattern features in the historical operation data, continuously optimize the loading knowledge repository, and improve the accuracy of future loading decisions. The operation timing database stores standardized operation timing graph templates, which can accelerate the generation of scheduling plans and improve operation response speed.

[0025] In the above embodiment, by installing sensors, actuators and control units, the hull status and operating parameters are monitored in real time, and accurate scheduling and management of ship loading and unloading operations are achieved, the ship operation route and loading and unloading strategies are optimized, energy consumption is reduced, and transportation efficiency is improved. Combined with the Internet of Things technology, remote monitoring and management of crew members are achieved, and the safety performance of ships is improved. This effectively reduces manual operation errors, improves the safety and economy of ship operations, and helps shipping companies achieve green, energy-saving, and efficient operation goals.

[0026] Intelligent load planning module, including: Solution matching unit, used to: Receive intelligent loading instructions and parse loading constraints contained in the intelligent loading instructions, wherein the loading constraints include cabin availability, loading balance requirements, and ballast water control requirements; Retrieve the standardized loading scheme that matches the loading constraint conditions in the loading knowledge repository, and compare the applicable scope, tank capacity matching degree and historical execution effect of the scheme; if there is a standardized loading scheme that meets the requirements, output the standardized loading scheme as a preliminary scheme and enter the stability verification unit for scheme verification; if there is no matching scheme, send a dynamic optimization instruction to the dynamic optimization unit; Dynamic optimization unit for: After connecting with the solution matching component and triggering the dynamic optimization command, it generates the loading scheme by using the adaptive optimization algorithm based on the material tank tolerance, compartment load distribution and hull deformation restriction conditions, with multiple objectives such as simplified transportation path, balanced compartment load and minimum ballast control. Stability verification unit, used for: Receive the loading scheme from the scheme matching unit and the dynamic optimization unit, and calculate the key stability parameters of the trim angle, heel angle, hull shear force and bending moment under the loading scheme; The calculation results are compared with the preset safety thresholds. If all parameters are within the safety range, the final execution plan is submitted to the execution plan selection module; if there are out-of-limit parameters, correction instructions are fed back to the dynamic optimization unit and the optimization calculation is re-executed.

[0027] In the above embodiment, through the scheme matching unit, the system can quickly retrieve the standard scheme that meets the current loading constraints in the loading knowledge repository, reduce the amount of calculation, and improve the efficiency of loading planning. When the standard scheme cannot meet the current operational needs, the dynamic optimization unit can combine factors such as tank capacity restrictions, load distribution and hull deformation, and use an adaptive optimization algorithm to generate an incremental loading scheme to improve the adaptability of the scheme. Through the stability verification unit, the system can perform longitudinal inclination, heel angle, shear force and bending moment analysis on the loading scheme to ensure the navigation stability of the ship after loading and avoid the risk of excessive eccentric loading or structural damage.

[0028] The execution scheme selection module includes an interactive unit, which is used to visualize the technical parameters and three-dimensional simulation effects of the candidate loading scheme set, and supports manual modification of the technical parameters of the candidate loading scheme set or direct selection of the final execution scheme.

[0029] In the above embodiment, combined with real-time navigation parameters (such as meteorological and hydrological conditions, operational task characteristics, etc.), the system can comprehensively evaluate candidate solutions to ensure the optimal balance of safety, economy and operational efficiency in the final solution. The interactive unit can present the loading status of the candidate solution in a three-dimensional model. The user can intuitively understand the loading effect and adjust the parameters to improve the controllability of the solution. The system has a built-in optimization indicator priority system, which can automatically select the optimal solution according to actual working conditions, reduce human intervention, and improve decision-making efficiency.

[0030] Job scheduling module, including: Space screening unit for: Identify the real-time loading rate and loading status of the cabin of the laying ship, the cabin loading status includes the loading rate of the laying tank, the material type and the water level information of the ballast tank, analyze the expected loading form in the final execution plan, determine the loading demand of the target cabin and extract the loading constraint conditions, compare the current loading state with the target loading form, select the cabin that meets the loading constraint conditions, take the cabin that meets the conditions as the operation target cabin, filter the cabin that does not meet the conditions, and output the data of the operation target cabin; Process decomposition unit, used for: Based on the data of the target cabin, calculate the loading and unloading changes of the laying tank and ballast tank, and determine the material flow direction and ballast adjustment requirements of the cabin. According to the preset deviation threshold, divide the overall operation process into multiple operation stage levels. For each operation stage level, determine the operating parameter range of the key execution equipment, which includes the target flow of the conveying equipment and the water adjustment rate of the ballast system, and output the decomposed process data; Timing generation unit, used to: Receive the output data of the process decomposition unit, build an operation timing optimization model based on the loading constraints, and use a heuristic algorithm to calculate the space operation priority, generate an operation timing map including the space operation priority, loading and unloading volume, transportation parameters, transportation rate and time window, and output the operation timing map; Remote collaboration unit for: The job timing map is pushed to the console through the Internet of Things system, and supports real-time data interaction, analyzes the manual correction instructions entered by the user, and dynamically adjusts the job timing map. After the adjustment is completed, the final scheduling instructions are sent to the automated job execution module.

[0031] In the above embodiment, the job scheduling and choreography module is responsible for generating a detailed job plan to ensure that the order of material loading and ballast adjustment is reasonable. Through the cabin screening unit, the system can identify the real-time loading status of the cabin and screen the target cabin that meets the loading constraints to ensure the accuracy of the operation. The process decomposition unit can calculate the change in cabin loading and unloading, and divide the operation stages according to the preset deviation threshold to make the loading process more orderly. The heuristic algorithm is used to optimize the operation sequence and generate an operation sequence map including cabin operation priority, transportation parameters and time windows to reduce operation conflicts and improve overall operation efficiency. The remote collaboration unit can push the operation plan through the Internet of Things system and support manual correction to enhance the adaptability and flexibility of the system.

[0032] Automated job execution module, including: A collaborative control unit is used to receive the operation timing map, analyze the operation timing map and generate equipment drive instructions, and synchronously coordinate the linkage operation of the material distribution conveyor, ballast pump group and auxiliary actuators; The working condition feedback unit is used to collect the hull attitude, cabin load and equipment operation data through distributed sensors, trigger the early warning mechanism and start the dynamic compensation program when an excessive deviation is detected.

[0033] In the above embodiment, through the collaborative control unit, the system can automatically analyze the operation timing diagram and generate equipment drive instructions, accurately control the linkage operation of the material distribution conveyor, ballast pump group and auxiliary actuators, improve the operation accuracy, and the working condition feedback unit can collect the hull posture, cabin load and equipment operation data, and trigger the early warning mechanism when an over-limit deviation is detected, start the dynamic compensation program, and ensure the safety of the operation.

[0034] This embodiment provides an intelligent assembly loading control system for a laying ship, a scheme matching unit, including: The data retrieval subunit is used to obtain the full-process execution parameters of each assembly load of the laying ship within a preset historical time period, and divide the full-process execution parameters into nodes based on the execution items of the assembly load of the laying ship; A data processing subunit, for: Based on the node division results, the execution details of each execution project and the execution results corresponding to the execution details are obtained, and the execution details are analyzed by parameters to obtain the material distribution and state characteristics of each execution project in the loading phase and the material position and storage change characteristics in the unloading phase; At the same time, the execution results of each execution rule are traversed to obtain the execution qualification of each execution project under the execution rule. When the execution qualification is less than the preset threshold, the full-process execution parameters of the assembly corresponding to the current execution project are eliminated, and the key focus of the execution project is determined based on the elimination results; Otherwise, the configuration parameters of the laying ship corresponding to the full process execution parameters of each assembly loading are obtained based on the management terminal; Associate the material distribution and state characteristics of each execution project in the loading phase, the material position and storage change characteristics in the unloading phase, and the key points of the execution project with the configuration parameters of the laying ship; The stowage knowledge repository builds subunits for: Building a distributed cache interval based on the association result, and caching the association result in the distributed cache interval; Generate a header tag based on the cached results and the configuration parameters of the laying ship. Generate a structure tag based on the material distribution and state characteristics of each execution project in the loading phase, the material position and storage change characteristics in the unloading phase, and the key concerns of the execution project. Generate a guide table of the stowage knowledge repository based on the association between the header tag and the structure tag. The guide table is added in the distributed cache interval to obtain the final loading knowledge repository.

[0035] In this embodiment, the preset historical time period is set in advance, for example, it may be one month or two months.

[0036] In this embodiment, the full-process execution parameters of the assembly and loading refer to the data corresponding to the entire process from loading to unloading and completion of the layout of the materials each time the task is executed.

[0037] In this embodiment, the execution project refers to the business type involved in the assembly and loading of the laying ship, for example, it may be the material location, material storage weight, and material storage form.

[0038] In this embodiment, node division refers to dividing the full-process execution parameters of the assembly loading into specific data information corresponding to each execution project, so as to facilitate the determination of the standards that different execution projects need to meet when assembling the loading.

[0039] In this embodiment, the execution details refer to data information that can characterize the specific execution status of each execution project after the execution parameters of the entire process are divided into nodes.

[0040] In this embodiment, the material distribution and state characteristics refer to the stacking position, stacking posture, and stacking weight of different materials on the laying ship.

[0041] In this embodiment, the material position and storage change characteristics refer to the change in the position and weight of the current material on the laying ship in order to ensure the balance of the laying ship when the material is unloaded.

[0042] In this embodiment, the execution qualification is used to characterize the implementation of each execution item under the execution rules. The larger the value, the more reliable the execution rules.

[0043] In this embodiment, the preset threshold is set in advance and is the minimum standard used to measure whether the execution qualification meets the requirements.

[0044] In this embodiment, the key focus points refer to the parameters that are determined to be focused on in the current execution project when the execution qualification is unqualified.

[0045] In this embodiment, the configuration parameters refer to the carrying capacity and space size of the laying vessel.

[0046] In this embodiment, the header tag refers to the parameter information generated according to the configuration parameters of the laying ship, and is the parameter information that needs to be retrieved and compared first when retrieving the assembly loading plan.

[0047] In this embodiment, the structure tag refers to the assembly loading scheme parameters that are determined according to the header tag and match the header tag.

[0048] In this embodiment, the guide table is a data recording table used to provide guidance or assistance to the user when selecting an assembly loading plan.

[0049] The working principle and beneficial effects of the above technical solution are: by obtaining the full-process execution parameters of each assembly loading of the laying ship within a preset historical time period, and processing and analyzing the full-process execution parameters of each assembly loading, it is possible to effectively determine the material distribution and state characteristics of each execution item in the loading stage, the material position and storage change characteristics in the unloading stage, and the key focus points of the execution project under different conditions, thereby providing reliable data support for the construction of a loading knowledge repository. Secondly, the above information obtained is associated with the configuration parameters of the laying ship, and the associated results are cached in the constructed distributed cache interval. At the same time, a corresponding guidance table is generated for each reference item according to the cached results, and is bound to the distributed cache interval, thereby finally realizing the accurate and effective construction of the loading knowledge repository, which provides convenience and guarantee for the intelligent assembly loading control of the laying ship.

[0050] This embodiment provides an intelligent assembly loading control system for a laying ship, an automated operation execution module, and further includes: The parameter reading unit is used to read the navigation parameters before driving the material conveying device, the ballast regulating unit and the actuator, determine the density of the water in the waters where the laying ship is located and the length of the laying ship, and monitor the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the waters; The first calculation unit is used to calculate the wave interference force of the laying ship on the horizontal axis and the wave interference force of the laying ship on the vertical axis according to the density of water in the water area where the laying ship is located, the length of the laying ship, and the angle formed by the horizontal plane when the hull meets the waves in the water area; ; in, F 1 represents the wave disturbance force on the horizontal axis of the laying ship; r Indicates the density of water in the waters where the current laying ship is located; L Indicates the length of the laying ship; s Indicates the average amplitude of the waves; f It indicates the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the water area; i Indicates the frequency sequence of regular waves in water waves; n Represents the total number of regular waves of different frequencies; m 1 represents the wave drift coefficient of the water area wave on the horizontal axis; m 2 represents the wave drift coefficient of the water area waves on the ordinate axis; l Indicates the wavelength of waves in a body of water; s i Indicated in i The average amplitude of a regular wave of frequency; F 2 represents the wave disturbance force of the laying ship on the ordinate axis; cos(∙) represents the cosine function; The second computing unit is configured to: Collect the target angle of the wave disturbance force of the laying ship on the horizontal axis and the wave disturbance force of the laying ship on the vertical axis i ; According to the wave disturbance force of the laying ship on the horizontal axis, the wave disturbance force of the laying ship on the vertical axis and the target angle i , construct the water area wave disturbance force model; ; in, F 干扰 Represents the water area wave disturbance force model; A determination unit, for: Calculate the wave disturbance force of the target water area of ​​the laying ship in real time according to the water area wave disturbance force model; Obtaining a preset wave disturbance force threshold, and comparing the wave disturbance force of the target waters of the laying ship with the preset wave disturbance force threshold, to determine whether the current laying ship meets the working conditions; When the wave disturbance force in the target waters of the laying ship is less than the preset wave disturbance force threshold, it is determined that the current laying ship meets the working conditions. At the same time, the material conveying device, ballast adjustment unit and actuator are driven to achieve precise material loading and unloading operations and balance water regulation; Otherwise, it is determined that the current laying ship meets the working conditions, and a stop work instruction is generated to control the laying ship to stop working.

[0051] In this embodiment, the preset wave disturbance force threshold is set in advance and is used as a criterion for judging whether the current laying vessel meets the working conditions.

[0052] The working principle and beneficial effects of the above technical solution are: by determining the density value of water in the water area where the laying ship is located, the length value of the laying ship, and the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the water area, the wave interference force of the laying ship on the horizontal axis and the wave interference force of the laying ship on the vertical axis are effectively calculated, so as to accurately construct a water area wave interference force model, which is conducive to effectively calculating the target water area wave interference force of the current laying ship through the water area wave interference force model, and then effectively judging whether the current laying ship meets the working conditions through the preset wave interference force threshold, so that when the working conditions are not met, the laying ship is controlled to stop working, thereby ensuring the safety and effectiveness of the laying ship's work and providing safety protection for the laying ship to carry out assembly and loading.

[0053] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent assembly loading control system for a laying ship, characterized in that: include: Intelligent load planning module for: Receive external input of intelligent loading instructions containing loading constraints, evaluate the real-time working conditions of the laying tank and balance water tank of the laying ship, and generate a set of candidate loading solutions that meet the optimization objectives, with balanced distribution of laying materials, shortest laying material transportation path, optimization of navigation stability parameters and rationalization of hull force as optimization goals; Implementation plan selection module, used to: Establish data interaction with the intelligent loading planning module, perform multi-criteria evaluation on the candidate loading scheme set according to the preset optimization index priority system and in combination with real-time navigation parameters, and select the final execution scheme, wherein the real-time navigation parameters include meteorological and hydrological conditions and operation task characteristics; Job scheduling module, used for: It works in conjunction with the execution plan selection module to obtain and compare the current actual loading status of the laying ship based on the expected loading form of the final execution plan, and generates a scheduling instruction set including the cabin operation sequence, equipment operation parameters and process time nodes in combination with the loading constraints; Automated job execution module for: It works in coordination with the operation scheduling module, analyzes the scheduling instruction set and converts it into control signals, drives the material distribution conveyor, ballast adjustment unit and actuator, realizes precise material loading and unloading operations and balance water regulation, and finally achieves the predetermined loading state; Loading knowledge repository for: Establish a data channel with the intelligent loading planning module, preset standardized loading rules and corresponding typical solution library, and store historical optimization parameters and constraint condition data sets.

2. The intelligent assembly loading control system of a laying ship according to claim 1, characterized in that: The intelligent loading planning module includes: Solution matching unit, used to: Receive intelligent loading instructions and parse loading constraints contained in the intelligent loading instructions, wherein the loading constraints include cabin availability, loading balance requirements, and ballast water control requirements; Retrieve the standardized loading scheme that matches the loading constraint conditions in the loading knowledge repository, and compare the applicable scope, tank capacity matching degree and historical execution effect of the scheme; if there is a standardized loading scheme that meets the requirements, output the standardized loading scheme as a preliminary scheme and enter the stability verification unit for scheme verification; if there is no matching scheme, send a dynamic optimization instruction to the dynamic optimization unit; Dynamic optimization unit for: After connecting with the solution matching component and triggering the dynamic optimization command, it generates the loading scheme by using the adaptive optimization algorithm based on the material tank tolerance, compartment load distribution and hull deformation restriction conditions, with multiple objectives such as simplified transportation path, balanced compartment load and minimum ballast control. Stability verification unit, used for: Receive the loading scheme from the scheme matching unit and the dynamic optimization unit, and calculate the key stability parameters of the trim angle, heel angle, hull shear force and bending moment under the loading scheme; The calculation results are compared with the preset safety thresholds. If all parameters are within the safety range, the final execution plan is submitted to the execution plan selection module; if there are out-of-limit parameters, correction instructions are fed back to the dynamic optimization unit and the optimization calculation is re-executed.

3. The intelligent assembly loading control system of a laying ship according to claim 2 is characterized by: Solution matching unit, including: The data retrieval subunit is used to obtain the full-process execution parameters of each assembly load of the laying ship within a preset historical time period, and divide the full-process execution parameters into nodes based on the execution items of the assembly load of the laying ship; A data processing subunit, for: Based on the node division results, the execution details of each execution project and the execution results corresponding to the execution details are obtained, and the execution details are analyzed by parameters to obtain the material distribution and state characteristics of each execution project in the loading phase and the material position and storage change characteristics in the unloading phase; At the same time, the execution results of each execution rule are traversed to obtain the execution qualification of each execution project under the execution rule. When the execution qualification is less than the preset threshold, the full-process execution parameters of the assembly corresponding to the current execution project are eliminated, and the key focus of the execution project is determined based on the elimination results; Otherwise, the configuration parameters of the laying ship corresponding to the full process execution parameters of each assembly loading are obtained based on the management terminal; Associate the material distribution and state characteristics of each execution project in the loading phase, the material position and storage change characteristics in the unloading phase, and the key points of the execution project with the configuration parameters of the laying ship; The stowage knowledge repository builds subunits for: Building a distributed cache interval based on the association result, and caching the association result in the distributed cache interval; Generate a header tag based on the cached results and the configuration parameters of the laying ship. Generate a structure tag based on the material distribution and state characteristics of each execution project in the loading phase, the material position and storage change characteristics in the unloading phase, and the key concerns of the execution project. Generate a guide table of the stowage knowledge repository based on the association between the header tag and the structure tag. The guide table is added in the distributed cache interval to obtain the final loading knowledge repository.

4. The intelligent assembly loading control system of a laying ship as claimed in claim 1, characterized in that: The execution scheme selection module includes an interactive unit for visually presenting the technical parameters and three-dimensional simulation effects of the candidate loading scheme set, and supports manual modification of the technical parameters of the candidate loading scheme set or direct selection of the final execution scheme.

5. The intelligent assembly loading control system of a laying ship as claimed in claim 1, characterized in that: The job scheduling module includes: Space screening unit for: Identify the real-time loading rate and loading status of the cabin of the laying ship, the cabin loading status includes the loading rate of the laying tank, the material type and the water level information of the ballast tank, analyze the expected loading form in the final execution plan, determine the loading demand of the target cabin and extract the loading constraint conditions, compare the current loading state with the target loading form, select the cabin that meets the loading constraint conditions, take the cabin that meets the conditions as the operation target cabin, filter the cabin that does not meet the conditions, and output the data of the operation target cabin; Process decomposition unit, used for: Based on the data of the target cabin, calculate the loading and unloading changes of the laying tank and ballast tank, and determine the material flow direction and ballast adjustment requirements of the cabin. According to the preset deviation threshold, divide the overall operation process into multiple operation stage levels. For each operation stage level, determine the operating parameter range of the key execution equipment, which includes the target flow of the conveying equipment and the water adjustment rate of the ballast system, and output the decomposed process data; Timing generation unit, used to: Receive the output data of the process decomposition unit, build an operation timing optimization model based on the loading constraints, and use a heuristic algorithm to calculate the space operation priority, generate an operation timing map including the space operation priority, loading and unloading volume, transportation parameters, transportation rate and time window, and output the operation timing map; Remote collaboration unit for: The job timing map is pushed to the console through the Internet of Things system, and supports real-time data interaction, analyzes the manual correction instructions entered by the user, and dynamically adjusts the job timing map. After the adjustment is completed, the final scheduling instructions are sent to the automated job execution module.

6. The intelligent assembly loading control system of a laying ship as claimed in claim 1, characterized in that: The automated operation execution module includes a collaborative control unit for receiving an operation timing diagram, parsing the operation timing diagram and generating device drive instructions, and synchronously coordinating the linkage operation of the material distribution conveyor, the ballast pump group and the auxiliary actuators.

7. The intelligent assembly loading control system of a laying ship as claimed in claim 6, characterized in that: The automated operation execution module also includes a working condition feedback unit, which is used to collect hull posture, cabin load and equipment operation data through distributed sensors, and trigger an early warning mechanism and start a dynamic compensation program when an over-limit deviation is detected.

8. The intelligent assembly loading control system of a laying ship as claimed in claim 1, characterized in that: It also includes a job timing database for storing standard job timing graph templates, and the job timing graph templates are used to accelerate the generation efficiency of the scheduling plan.

9. The intelligent assembly loading control system of a laying ship according to claim 1, characterized in that: It also includes a data analysis module, which is used to dynamically optimize the loading knowledge repository and iteratively upgrade the system decision-making capabilities by mining pattern features in historical operation data.

10. The intelligent assembly loading control system of a laying ship according to claim 1, characterized in that: The automated job execution module also includes: The parameter reading unit is used to read the navigation parameters before driving the material conveying device, the ballast regulating unit and the actuator, determine the density of the water in the waters where the laying ship is located and the length of the laying ship, and monitor the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the waters; The first calculation unit is used to calculate the wave interference force of the laying ship on the horizontal axis and the wave interference force of the laying ship on the vertical axis according to the density of water in the water area where the laying ship is located, the length of the laying ship, and the angle formed by the horizontal plane when the hull meets the waves in the water area; ； in, F 1 represents the wave disturbance force on the horizontal axis of the laying ship; ρ Indicates the density of water in the waters where the current laying ship is located; L Indicates the length of the laying ship; σ Indicates the average amplitude of the waves; φ It indicates the angle formed by the horizontal plane when the hull of the laying ship meets the waves in the water area; i Indicates the frequency sequence of regular waves in water waves; n Represents the total number of regular waves of different frequencies; μ 1 represents the wave drift coefficient of the water area wave on the horizontal axis; μ 2 represents the wave drift coefficient of the water area waves on the ordinate axis; λ Indicates the wavelength of waves in a body of water; σ i Indicated in i The average amplitude of a regular wave of frequency; F 2 represents the wave disturbance force of the laying ship on the ordinate axis; cos (∙) represents the cosine function; The second computing unit is configured to: Collect the target angle of the wave disturbance force of the laying ship on the horizontal axis and the wave disturbance force of the laying ship on the vertical axis θ ; According to the wave disturbance force of the laying ship on the horizontal axis, the wave disturbance force of the laying ship on the vertical axis and the target angle θ , construct the water area wave disturbance force model; ； in, F 干扰 Represents the water area wave disturbance force model; A determination unit, for: Calculate the wave disturbance force of the target water area of ​​the laying ship in real time according to the water area wave disturbance force model; Obtaining a preset wave disturbance force threshold, and comparing the wave disturbance force of the target waters of the laying ship with the preset wave disturbance force threshold, to determine whether the current laying ship meets the working conditions; When the wave disturbance force in the target waters of the laying ship is less than the preset wave disturbance force threshold, it is determined that the current laying ship meets the working conditions. At the same time, the material conveying device, ballast adjustment unit and actuator are driven to achieve precise material loading and unloading operations and balance water regulation; Otherwise, it is determined that the current laying ship meets the working conditions, and a stop work instruction is generated to control the laying ship to stop working.

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