343 results about "Quay crane" patented technology

The disclosure provides an intelligent horizontal transportation system for automatic loading or unloading at a container terminal. The system includes a plurality of autonomous transport robots (ATRs) and an ATR control system. The plurality of ATRs are configured to perform horizontal transportation tasks. The ATR control system is in real-time communication with the plurality of ATRs to manage and control the plurality of ATRs; the ATR control system is in real-time communication with a terminal management system, an automated yard crane, and an automated quay crane, so as to coordinate task scheduling between the automated yard cranes, automated quay cranes, and the plurality of ATRs. The ATR control system includes a task scheduling module, a dynamic path planning module, a standardized control interface module, a traffic management module, a lock station management module, a vehicle sequencing module, a charging scheduling module, a parking management module, and a remote driving module.

The invention discloses an intelligent port scheduling and energy efficiency optimization method based on digital twinning. The method comprises the steps that S1, three-dimensional point cloud data and sensor data of a target port are acquired; s2, constructing a port digital twin model comprising a quay crane model, an AGV model and a storage yard model; s3, agents are constructed for a quay crane model, an AGV model and a storage yard model in the port digital twinborn model, and a multi-agent reinforcement learning environment is built; s4, training each agent in a multi-agent reinforcement learning environment through a multi-agent reinforcement learning algorithm; s5, mapping the real-time task data and state data of the port to each trained agent to simulate the scheduling of the target port, and generating a port scheduling strategy; and S6, realizing operation scheduling of the quay crane equipment, the AGV equipment and the storage yard equipment of the target port based on the port scheduling strategy. According to the invention, the operation efficiency and the energy efficiency level of the port can be improved, and powerful technical support is provided for sustainable development of the intelligent port.

The invention relates to the technical field of equipment collaborative operation of the Internet of Things, in particular to a transit hub equipment collaborative operation method and system based on the Internet of Things technology. According to the method, original attitude motion data of a target ship are collected in real time through an attitude sensor network of the Internet of Things, and a real-time attitude drift vector of the target ship relative to a geodetic coordinate system is calculated; constructing a dynamic coordinate transformation matrix according to the real-time attitude drift vector; acquiring an expected operation track control instruction preset by the quay crane control system according to the geodetic coordinate system; performing coordinate transformation operation on the expected operation track control instruction through a dynamic coordinate transformation matrix to obtain a compensated cooperative control instruction; the compensated cooperative control instruction is transmitted to a quay crane control system in real time through an Internet of Things communication link, and a quay crane lifting appliance is driven by the quay crane control system to conduct lifting operation according to the compensated track instruction; and the safety and efficiency of the hoisting operation between the ship and the quay crane can be effectively improved.

The invention discloses a port container transportation full-process simulation and space planning quantification system and method under random event deduction. The system comprises a data acquisition module, a data processing module, a process simulation module, an efficiency quantification index generation module and an efficiency quantification module. The data acquisition module is used for acquiring basic data in port operation; the data processing module is used for processing the basic data; the process simulation module is used for constructing port container transportation process simulation covering the whole process of ship navigation, ship berthing, quay crane loading and unloading, storage yard storage and container truck outward transportation based on the processed basic data, and obtaining a simulation result; the efficiency quantitative index generation module is used for obtaining an efficiency quantitative index according to the container transportation characteristics and the port operation experience; and the efficiency quantification module is used for quantifying the simulation result by utilizing the efficiency quantification index. According to the invention, the current operation efficiency level of the port can be measured comprehensively and objectively.

The invention discloses a seaport logistics-energy optimization scheduling method based on multi-agent reinforcement learning, and the method comprises the steps: constructing a port logistics-energy space-time cooperation model which comprises an AES berth distribution model, a QC distribution model, an AGV scheduling model, and an SPDN optimal power flow model; a logistics-energy space-time coordination model based on optimization is converted into a multi-agent fully observable Markov decision process (MDP), and a general multi-agent reinforcement learning (MARL) large model is constructed and trained to calculate a reward function, observe and act space and automatically generate scheduling strategies of various scenes. According to the method, an optimal scheduling strategy is directly obtained by considering a comprehensive logistics-energy space-time cooperation model of an all-electric ship (AES), a quay crane (QC), an automatic guided vehicle (AGV) and a port power distribution network (SPDN) and inputting system operation parameters through a multi-agent reinforcement learning large model, and the calculation efficiency is greatly improved while the optimality is ensured.

The invention discloses a new energy access lower harbor area transformer insulation performance and service life evaluation method, which comprises the following steps: firstly, establishing a wind and light storage AC / DC hybrid micro-grid equivalent simulation model, and quantifying a composite action mechanism of new energy fluctuation and harmonic characteristics on dynamic loss and hot-spot temperature rise of a transformer; analyzing a harmonic loss mechanism of the transformer in different operation modes; secondly, constructing a quay crane and field crane operation simulation model, and analyzing the harmonic characteristics of bridge crane equipment and the influence of the harmonic characteristics on the harmonic distortion rate of the power distribution network; then, on the basis of the data, a transformer hot-spot temperature dynamic calculation model is established in combination with bidirectional power flow characteristics; and finally, calculating transient temperature distribution of the transformer through a flow field-temperature field coupling method, and constructing a multi-physical field coupled insulation aging rate model to realize evaluation of the residual life of the transformer. The method solves the problem that the traditional method cannot quantify the bidirectional power flow and harmonic wave composite aging effect.

The invention discloses a port shore power direct-current system topological structure with a super capacitor. The port shore power direct-current system topological structure comprises a port power grid, a wind power unit, a photovoltaic power generation unit, a direct-current bus, a super capacitor bank, a ship power storage unit and a shore bridge feedback load. The port power grid, the wind power unit, the photovoltaic power generation unit and the super capacitor bank are respectively connected to the direct current bus through a first bidirectional AC / DC converter, a unidirectional AC / DC converter, a non-isolated DC / DC converter and an isolated DC / DC converter; the DC bus is connected to the ship power storage unit and the shore bridge feedback load through the bidirectional DC / DC converter and the second bidirectional AC / DC converter. The invention further discloses a seaport integrated energy system optimal scheduling method considering the ship demand response under the multi-time scale. According to the method, firstly, an electricity-heat-hydrogen coupling system model is established, and then optimization scheduling is carried out through day-ahead and intra-day optimization scheduling models. The ship docking power utilization efficiency can be effectively improved, the loss is reduced, the on-site absorption of port new energy is promoted, and the stability and reliability of the system are improved.

The invention relates to the technical field of port operation simulation software systems, and particularly discloses a quay crane operation process simulation system and method for port intelligent driving. The quay crane operation process simulation system comprises a data interaction module, a quay crane motion simulation module, a service simulation module, a simulation control module, an operation backtracking module, an analysis and optimization module and a simulation display module. The method has the beneficial effects that a complex port operation process is completely mapped to a digital space through fine dynamic modeling and coding, a port manager can visually observe and analyze the whole operation process in a virtual environment through full-process digitization, and potential problems can be found and solved in time; based on the constructed 3D simulation environment, natural environment data and random events are combined to carry out work process simulation, meanwhile, simulation data are fed back to a simulation system to carry out closed-loop control, simulation errors are reduced, and the work process simulation authenticity is improved.

The invention relates to a quay crane RTK positioning precision evaluation method and system and a storage medium, and the method comprises the steps: L1, when an unmanned container truck carries out the container loading and unloading operation under a quay crane, the quay crane RTK feeds back the positioning value of a vehicle according to a fixed frequency, and obtains the data information of the positioning value of the vehicle within a fixed time; l2, based on the data information of the positioning value of the vehicle within the fixed time, predicting the positioning value of the vehicle by adopting an improved ELMAN dynamic recurrent neural network prediction algorithm optimized based on a particle swarm optimization algorithm to obtain the data information of the predicted positioning value of the vehicle; and L3, based on the predicted data information of the positioning value of the vehicle, optimizing the positioning value of the vehicle by adopting a zebra optimization algorithm of a self-adaptive dynamic learning factor based on global search to obtain the optimized data information of the positioning value of the vehicle. The alignment success rate of the unmanned container truck can be increased, and harbor area operation can be prevented from being affected.

The invention discloses a container logistics ecological chain large model system based on a joint model, and relates to the technical field of container logistics, and the system comprises real equipment, a Tos system, a real-time data concentrator, a virtual port, a database, and an LLM. The real equipment is key operation objects of a port site and comprises quay cranes, wheel cranes, inner container trucks, storage yards, ships and the like, and each object continuously outputs real-time operation state data; and the Tos system is responsible for receiving and processing real-time data from real equipment. According to the container logistics ecological chain large model system based on the joint model, a scheduling strategy with sensing, decision-making and self-adaption capabilities is formed by training an agent in a virtual port environment, and real-time deployment and application are performed in an actual port, so that multi-type equipment and multi-task concurrent scheduling can be supported; efficient, real-time response and dynamic rescheduling capability are realized, and the overall intelligent level, loading and unloading efficiency and handling capacity of port operation are improved.

The invention relates to an equipment collaborative scheduling method in a sea-railway combined transport port mixed mode and electronic equipment, and belongs to the technical field of port engineering. The method comprises the following steps: by taking preset operation sequence connection, safe operation of a rail-mounted gantry crane and waiting time of each device as constraints, unloading a container onto a container truck by the rail-mounted gantry crane, and then transporting the container to a wharf by the container truck to wait for quay crane operation; a scheduling model is established according to the working condition of a transfer mode that the rail-mounted gantry crane stacks the containers needing to be stacked to the designated container positions of the railway storage yard; the scheduling model is solved based on the grey wolf algorithm introducing the chromosome uniform crossover strategy, a final equipment cooperative scheduling scheme is obtained, and the problem that in the prior art, research on the scheduling mode is single in actual work is effectively solved.

The invention relates to an intelligent port cargo scheduling method based on the Internet of Things, and the method comprises the steps: collecting cargo state information, equipment position coordinates, operation progress data and environment parameters in real time through Internet of Things sensor nodes disposed on a quay crane, a container truck, a storage yard sling and a cargo carrier, and fusing a port GIS map and a berth plan based on the real-time collected data, and establishing a multi-objective optimization model with maximization of the quay crane-container truck-storage yard cooperative efficiency as an objective and minimization of equipment conflict avoidance and path overlap as constraint conditions, and dynamically activating or sleeping storage yard operation partitions and adjusting the number of container truck marshalling according to the obtained storage yard congestion prediction index and the parking space vacancy rate.

The invention relates to the field of automatic container wharf operation optimization, in particular to a container wharf automatic remote control quay crane one-control-two operation control system and a quay crane operation control method, and the system comprises a remote console which is used for receiving an operator instruction and displaying real-time operation data; at least two quay crane devices, wherein each quay crane device comprises a crane and a container spreader; the automatic remote control system is used for analyzing the operation instruction and controlling the quay crane to execute automatic loading and unloading operation; the dynamic switching module is in communication connection with the automatic remote control system, so that the control rights of the two quay crane devices are alternately switched under the monitoring of a single operator; and the safety monitoring module is used for monitoring the operation state of the double-shore bridge in real time and ensuring the safety of the system when the control right is switched. According to the one-control-two operation control system for the automatic remote control quay cranes of the container wharf, the operation of managing and switching the two quay cranes at the same time by a single operator through the remote control console, and the problem that manpower resources of the wharf are insufficient is effectively solved.

The invention discloses a quay crane digital twin detection system using an unmanned aerial vehicle, and the system comprises a website management platform which is used for achieving task management, user management, customer management and synchronous data storage and reading; and the hangar is arranged on a wharf and establishes communication with the website management platform, a plurality of unmanned aerial vehicles can be arranged in the hangar in a matched mode, or a plurality of hangars and unmanned aerial vehicles are arranged on the port wharf. The invention further discloses a quay crane digital twinning detection method using the unmanned aerial vehicle. According to the invention, the VT detection efficiency is improved, the safety of quay crane equipment and the use safety and reliability are improved, the image information and the corresponding digital information of important parts of the quay crane can be quickly known in real time, so that a correct decision can be made, and the production efficiency is also improved.

The invention discloses a quay crane operation queue intelligent scheduling data processing method, and belongs to the technical field of intelligent scheduling, and the method comprises the steps: 1, preparing data, processing the data including ship information, equipment information, queue information and rule configuration, and then setting constraint conditions including a preset limiting condition and a target constraint condition; 2, building a CWP algorithm framework; 3, initializing parameters, carrying out data preprocessing, initializing parameters and variables required by an algorithm, and executing scheduling; step 4, constructing a neural network, establishing a neural network model of reinforcement learning, and realizing data progressive extraction from an input layer, a processing layer, a feature fusion layer, a decision layer to an output layer; and 5, training the network and updating parameters. The defects of a traditional scheduling algorithm are overcome, scheduling mode diversification is achieved, global optimization of intelligent scheduling is achieved, and a more flexible, efficient and intelligent job scheduling solution is provided.

The invention discloses an automatic container terminal quay crane operation mode intelligent switching system and method, and the system comprises a mode management unit which is used for defining an automatic mode, a manual intervention mode and a special mode, and configuring mode switching conditions; the dynamic safety detection unit is used for monitoring the lifting appliance height and container operation area parameters in real time, the types of containers comprise tanks, overrun boxes and dangerous goods boxes, and the types of operation areas comprise an on-board area, a bridge bottom IGV operation area and a bridge rear container truck operation area; the task coordination engine unit is used for responding to the mode switching request and executing a corresponding task; and the abnormity recovery unit is used for triggering a task recovery or manual intervention mode based on the container carrying state of the lifting appliance and the ID of the container when the special mode is switched back to the automatic mode. According to the embodiment of the invention, while the cost advantage of a single-trolley automatic system is maintained, the system safety and the operation efficiency are optimal, and a brand new solution is provided for automatic modification of a wharf.

The invention discloses a nonsingular terminal sliding mode control method and system for a marine rotary crane, and the method comprises the steps: obtaining related parameters of a four-degree-of-freedom marine rotary crane, and building a first mathematical model; establishing a first equation and a second equation based on the first mathematical model; an equation is combined with the improved non-singular fast terminal sliding mode curved surface, and a non-singular terminal sliding mode controller is obtained through solving; and a nonsingular terminal sliding mode controller is used for controlling the four-degree-of-freedom marine rotary crane to move. The external disturbance of the crane system can be well inhibited by coupling measurable ship yawing and rolling disturbance and combining self-adaptive control, meanwhile, a good compensation effect is achieved for parameter uncertainty caused by reciprocating transportation in actual operation, and the stability of the system is improved. And finally, efficient trajectory tracking and swing suppression can be realized, so that a control effect is achieved.

The invention relates to the field of deep learning, and provides a container ship loading and unloading operation time prediction method and system for solving the problems that an existing container ship operation time estimation method is rough, and operation data has noise in a real loading and unloading operation scene. On the basis of a deep residual shrinkage network DRSN-CW (Deep Residual Shrinkage Net) model with feature extraction and denoising capabilities under a ResNet-18 architecture, a fixed soft threshold function is changed into a more flexible adaptive threshold function, so that the noise reduction capability is more flexible while the feature learning capability is kept. According to the scheme of the application, the request of real-time prediction of the quay crane operation duration in the berth planning process can be well met with relatively high average detection precision and robustness.

The invention provides a port berth and quay crane distribution method and system based on diffusion evolution generation, and the method comprises the following steps: 1, carrying out the noise addition of an original image, and generating training data; 2, training a diffusion model; and step 3, generating a Gantt chart through the diffusion model, and completing auxiliary optimization work on the Gantt chart by adopting a genetic algorithm. According to the method, the Gantt chart of the BACAP is generated for the pure noise graph by adopting the diffusion model, the generation of the final image is accelerated by adopting the genetic algorithm in the generation process, the image is ensured to always meet the constraint condition of the problem, and the optimization result of the genetic algorithm is legalized by adopting the rounding method, so that the purpose of efficiently and accurately solving the BACAP is achieved.

The utility model discloses an outdoor module box with a cooling system. The outdoor module box comprises a box body, an air conditioner and a temperature and humidity detection sensor, the air conditioner penetrating body is arranged on the side face of the box body and used for reducing the temperature in the box body. The temperature and humidity detection sensor is arranged in the box body and establishes data communication with a main PLC (Programmable Logic Controller) of the quay crane; the air conditioner is an integrated air conditioner, and a controller on the air conditioner is in control connection with a master control PLC of the quay crane. According to the utility model, the refrigerating system and the temperature adjusting and limiting device are additionally arranged in the outdoor module box, so that equipment in the outdoor module box can work normally in a hot environment.

The present application provides a vision-based safety intelligent electronic fence protection system and method for quay crane operations. The system according to the present application includes: monitoring equipment, a switch, a perception workstation, and an audible and visual alarm; the monitoring equipment is used to monitor the quay crane operation area to obtain monitoring images, integrate the monitoring images into monitoring data, and send the monitoring data to the perception workstation through the switch; the switch is used to transmit the monitoring data to the perception workstation; the perception workstation is used to configure the intelligent electronic fence protection function for the quay crane operation area, and identify the lane lines on the driving path of the quay crane in real time; perform real-time processing, identification and detection of abnormal intrusion in the quay crane operation area, and generate a warning signal; the audible and visual alarm is used to give an audible and visual alarm according to the warning signal. The technical solution provided by the present application can accurately detect obstacles in the operation area and can warn of abnormal situations within a specific range.

The invention discloses a container terminal resource overall planning optimization method based on an operation actuarial model, and the method comprises the steps: constructing a quay crane and field crane parameter set, constructing a quay crane and field crane operation time actuarial model according to the parameter set, and constructing a container quay crane and field crane basic operation time actuarial model. The calculation precision of the field bridge and shore bridge operation time actuarial model is improved, finally, an operation efficiency evaluation model is built through the model, the most efficient method is obtained, and the purposes of optimizing berths, ships, storage yards and resource key business processes and finally achieving wharf lean operation are achieved through operation actuarial logic and strategy guidance.

The invention discloses an electric energy feedback collection and load peak suppression system for a wharf crane, and relates to the technical field of wharf power supply and distribution and energy management. Wherein the wharf crane comprises a quayside container crane (quay crane), a rail or rubber-tyred container portal crane (gantry crane) and the like, which are called cranes for short hereinafter. According to the system, instantaneous power, average power, peak duration and power increasing rate of a wharf power station, feedback power and feedback electric energy of a crane, capacity and charging and discharging parameters of an energy storage device, and electric energy quality indexes of a power grid are collected in real time; respectively calculating a peak impact index, a feedback absorption coefficient, a peak valley switching coefficient and a harmonic suppression coefficient, and comparing and analyzing with a preset threshold to generate a corresponding strategy; and integrating the results of the modules, carrying out unified scheduling on the energy storage device, and realizing power fluctuation compensation and stable output through a smooth scheduling strategy, thereby constructing an operation mechanism. According to the method, the instantaneous peak power of the wharf power station can be effectively inhibited, the feedback energy consumption capability is improved, the peak-valley scheduling economy is optimized, the electric energy quality is improved, and the safety, stability and energy efficiency of system operation are improved.

The present invention discloses a multi-agent collaborative optimization operation method for an automated container port, which relates to the field of port scheduling operations. This method constructs two models with the shortest port operation time and the least operation cost, and considers port fixed costs, carbon emissions, carbon taxes, etc., making assumptions and constraints on the models; uses the Grey Wolf Algorithm for steps such as individual coding and generating an initial population, and tests the performance of the Grey Wolf Algorithm; finally, calculates with an example to verify the effectiveness of the model and the algorithm. This solution uses a mathematical model to simulate the actual container port collaborative operation method, can analyze the relevant factors affecting the container port operation efficiency, and conducts collaborative optimization around the three main bodies of berths, quay cranes, and AGVs in the operation process to transform the multi-objective problem into a single-objective problem, facilitating the simulation and analysis of actual problems. At the same time, the standard deviation of the Grey Wolf Algorithm is lower than that of the other two algorithms, having higher stability.

An intelligent control system and method for automatic wheel guidance of a quay crane trolley, comprising: driving units (6) connected to wheels (2, 3, 4, 5) of a quay crane trolley (1) and used for controlling the guidance of the wheels (2, 3, 4, 5); displacement sensors (7) arranged on the driving units (6) and used for obtaining the displacements of the wheels (2, 3, 4, 5); distance measuring sensors (8) arranged on tracks (9) and positioned close to the proximal sides of the wheels (2, 3, 4, 5) and used for obtaining gaps between rims of the wheels (2, 3, 4, 5) and edges of the tracks (9); and an intelligent controller (10) used for reading the measured values of the displacement sensors (7) and the distance measuring sensors (8), so that the wheels (2, 3, 4, 5) undergo torsion for automatic deviation correction, the wheel orientation of the quay crane trolley (1) can be corrected in time, deviation and rail gnawing are avoided, and the problem of deviation of the quay crane trolley (1) is solved.

The invention discloses a port operation scheduling method, device and equipment, a storage medium and a program product, and the method comprises the steps: determining the state information of a to-be-scheduled port, and the state information comprises a ship unloading operation task table, real-time traffic flow data, container truck operation information, shore bridge operation information and field bridge operation information; and inputting the state information into a container truck-quay crane-field crane collaborative scheduling model, determining scheduling information of the port to be scheduled through the collaborative scheduling model, and performing collaborative operation scheduling of the container truck, the quay crane and the field crane according to the scheduling information. Therefore, due to the fact that the operation information of the container trucks, the quay cranes, the field cranes and the like is considered at the same time, the operation efficiency of the container trucks, the quay cranes and the field cranes can be maximized through the scheduling information obtained through the collaborative scheduling model, and then the transportation cost of port operation is reduced.

The invention discloses an incremental learning enhanced integrated agent assisted evolutionary algorithm, which comprises the following steps of: setting parameters of a self-adaptive rolling time domain strategy according to information of a ship to be allocated, and dividing a long-term berth quay crane collaborative allocation problem (LBACAP) into continuous sub-LBACAPs; solving the sub LBACAP by using an integrated agent assisted evolutionary algorithm; the arrival time and departure time are predicted according to the arrival sequence of the ships, dynamic adjustment and processing of the continuous arrival ships are achieved, time windows are divided, and it is ensured that the algorithm can adapt to the continuous arrival field of the ships by dynamically adjusting the time windows; three proxy models of Kriging, RBFN and SVR are utilized, so that the calculation cost is remarkably reduced, and meanwhile, the strong search capability is kept; historical decision information is used for guiding the optimization process of a subsequent time window, and the optimization effect of the algorithm is gradually improved; through combination of a rolling window and incremental learning, an optimal berth and quay crane distribution scheme can be found in a global range.

The invention provides a mechanical hook type girder pitching safety hook and a working method, relates to the field of quay crane safety facilities, and aims to solve the problems of power dependence defect of the existing hook type safety hook and high alignment difficulty of a plug pin type safety hook, the pitching safety hook is composed of a base, a hook tongue, a lock pin and a hook, and the hook tongue is rotatably mounted on the base; the thrust part and the hook part are ingenious in design, when the hook abuts against the thrust part, the hook tongue can rotate through pushing of the hook, rapid hooking action is achieved, manual high-altitude operation is not needed, the operation efficiency is greatly improved, and meanwhile the falling risk of personnel is eliminated; the lock pin is installed on the base in a sliding mode in the direction parallel to the rotating axis of the hook tongue, the trigger block and the lock block of the lock pin can synchronously act along with the action of the thrust block, the mechanical structure is simple, corrosion resistance is better in the high-salt-mist and high-humidity environment of a port, and the maintenance cost is reduced.

The invention relates to the field of radiation scanning, in particular to a radiation scanning inspection system and a control method. The radiation scanning inspection system includes: a quay crane including a gantry structure and a cargo handling mechanism disposed on the gantry structure, where the gantry structure includes a sea side gantry and a land side gantry, the cargo handling mechanism configured to perform cargo handling between a first position on the sea side and a second position on the land side; the first radiation scanning inspection device is arranged on the sea side door frame and is configured to carry out radiation scanning inspection on the goods in the process that the goods carrying mechanism carries out goods carrying from the first position to the second position; the cargo carrying mechanism is further configured to adjust the length direction of the cargo before the first radiation scanning inspection device conducts radiation scanning inspection on the cargo. According to the embodiment of the invention, the loading, unloading and checking efficiency of goods can be improved, and the occupation of the internal space of the frame of the quay crane can be reduced.

The present invention provides a comprehensive information platform for iron-water intermodal transport, which relates to the field of transportation technology. The comprehensive information platform for iron-water intermodal transport described in the present invention includes a rack rail vehicle operation monitoring system, an iron-water intermodal transport operation information system and operation site equipment; the rack rail vehicle operation monitoring system includes a data acquisition module, a data processing module and a data display module; the iron-water intermodal transport operation information system includes an intermodal transport management system and a statistical analysis system, the intermodal transport management system is used to manage intermodal transport plans, intermodal transport processes and intermodal transport bills, and the statistical analysis system is used to analyze the operation efficiency. The technical solution described in the present invention adopts a new mode of direct vehicle-ship pickup for iron-water intermodal transport, incorporates the rack rail vehicle and other operation site equipment into the comprehensive information platform for iron-water intermodal transport for management, conducts real-time and precise control of vehicle-ship docking operations throughout the entire process, and realizes direct loading and unloading from the quay crane to the railway truck through the rack rail tractor and the iron-water intermodal transport information platform, thereby improving port operation efficiency.