18 results about "Marine power system" patented technology

This application discloses a remote start-stop control system and method for ships, including a ship-end system and a shore-end system. The ship-end system includes: a ship-end sensing unit for acquiring ship status information and execution result data; a ship-end communication unit for uploading ship status information and execution result data to the shore-end system and receiving remote control commands; and a ship-end control unit for performing preparation control, start control, and stop control of the ship's power system according to the remote control commands. The shore-end system includes: a shore-end control unit for receiving remote control commands; a shore-end communication unit for receiving ship status information and execution result data and issuing remote control commands; and a shore-end display unit for displaying ship status information, remote control commands, and execution result data. This application can reduce the system's reliance on manual labor, improve its intelligence, operational efficiency, and reliability, and can be widely applied in the field of ship control technology.

The application relates to the technical field of ship power control, and discloses a ship power system energy efficiency optimization control system based on multi-sensor fusion, which comprises the following modules: a multi-source data acquisition module, which is used for synchronously collecting hull, shafting and air path parameters; a kinematics mapping calculation module, which is used for calculating a propeller transient immersion index; a phase extraction and mode determination module, which is used for extracting a wave phase and an amplitude output mode signal; a fuel mechanical dynamics feedforward module, which is used for generating an oil injection instruction according to the amplitude and the immersion index derivative; an air thermodynamics cooperative control module, which is used for controlling a valve and starting a scavenging blower according to a phase angle; and a long-term energy efficiency optimization module, which is used for finely adjusting a main rotating speed setting value according to an energy efficiency cost function gradient. The technical scheme of extracting the transient immersion index and the fluctuation amplitude to dynamically adjust the rotating speed control dead zone and superimpose a negative fuel feedforward instruction is adopted, so that the technical effects of suppressing abnormal fluctuation of the main engine rotating speed under high sea conditions and reducing unnecessary fuel consumption are achieved.

This invention belongs to the field of marine hybrid power system control and discloses an energy allocation optimization method and system for hierarchical control of a marine DC microgrid. The method includes: establishing a top-level optimized power allocation strategy model with the goal of minimizing diesel generator output and battery life loss; solving the top-level optimized power allocation strategy model using the second-generation non-dominated sorting genetic algorithm NSGA-II and the top-to-bottom solution distance method TOPSIS to obtain the power allocation scheme with optimal overall performance; introducing power regulation and voltage compensation in the intermediate layer, combined with droop control in the execution layer, to form an improved droop control, thereby achieving power allocation and current sharing control. This invention achieves optimal overall performance in marine power systems, including extended battery life, reduced fuel consumption, and efficient, energy-saving, and environmentally friendly operation.

This invention discloses an automatic control method for switching between main and auxiliary power systems in a ship's propulsion system, belonging to the technical field of automatic control methods for switching between main and auxiliary power systems. The automatic control method for switching between main and auxiliary power systems includes the following steps: a monitoring system; system determination of switching; diagnosis and decision-making; execution system; verification of switching; monitoring of the switching process and monitoring and maintenance. This invention enables the automatic control system to have powerful communication capabilities through a communication and human-machine interface system. Ship personnel can easily communicate with shore crew in real time through the communication and human-machine interface system. The communication and human-machine interface system more intuitively displays the system operation method, thereby making it easier for ship personnel to monitor and control the switching process between the main engine and auxiliary engine in a simple and easy-to-understand way.

This invention discloses an embedded simulation training method for ship propulsion systems based on existing monitoring systems. This method defines four core steps—mode switching and isolation, command acquisition and uplink, simulation calculation, and parameter downlink and drive—and their synergistic effects to construct a stable and secure training data closed loop. This enables highly realistic and zero-risk embedded simulation training using the existing monitoring system's human-machine interface components, without using real propulsion equipment or interfering with the normal operation of the monitoring system. Furthermore, this invention defines a standardized command uplink and parameter downlink mechanism and integrates dynamic fault injection and intelligent evaluation functions, effectively solving the problems of incomplete training coverage, insufficient realism, and evaluation difficulties caused by reliance on advanced platforms and lack of methodological processes in existing technologies.

This invention discloses a method and system for measuring engine intake air flow based on Venturi tube measurement and carbon balance method. By combining the synergistic effect of dynamic Venturi tube measurement and theoretical correction using the carbon balance method, this invention effectively improves the accuracy of engine intake air flow measurement. The Venturi tube design reduces fluid energy loss, and the dynamic calibration based on mass conservation using the carbon balance method overcomes the accuracy limitations of traditional flowmeters under transient conditions and new fuel scenarios. By optimizing the calibration curve through power function fitting, measurement errors are corrected in real time, significantly improving the system's adaptability to changes in different fuel compositions. The use of low-cost standard components and a lightweight algorithm architecture avoids the high cost and data dependence of complex sensor arrays or machine learning models, simplifying hardware deployment while ensuring accuracy, making it suitable for engineering applications in marine power systems.

This invention relates to the field of hydrogen-powered ship design, specifically to a method for assessing the adaptability of hydrogen-powered ship propulsion systems for different navigation domains. The method includes the following steps: rating candidate equipment for key components and constructing an equipment rating table; establishing safety constraints and eliminating candidate equipment that does not meet these constraints; establishing balance constraints and eliminating candidate equipment that does not meet these constraints; establishing a set of candidate propulsion system configurations and determining the score for each configuration; adjusting the weights of each configuration's score to generate a scenario-based index score matrix; calculating the variability and conflict of evaluation indicators and determining the combined weights of these indicators; calculating a comprehensive evaluation index and ranking the candidate configurations to output the preferred configuration. This invention significantly improves the objectivity and efficiency of hydrogen-powered ship propulsion system adaptability assessment, ensures operational safety, achieves accurate adaptability across multiple scenarios, and provides a reliable basis for engineering selection.

The application relates to the technical field of clutches, in particular to a marine friction clutch device and a marine power system. The clutch device comprises an input shaft, an output shaft, a clutch shell, a friction plate assembly and a ring-shaped piston. The input shaft and the output shaft are coaxially arranged, and both the input shaft and the output shaft are tubular bodies. In use, the friction plate assembly is compressed by the piston, so that the input shaft and the output shaft are connected. Since the input shaft and the output shaft are both hollow tubular bodies, the transmission shaft of the marine propulsion device can be directly connected with the power-providing main engine by penetrating the input shaft and the output shaft. The input shaft is connected with the output end of the main engine, and the output shaft is connected with the rotating shaft of the motor. The motor adopts a hollow rotating shaft, and the transmission shaft of the propulsion device penetrates the hollow rotating shaft of the motor. The motor can be connected with the output end of the main engine through the clutch device, thereby providing hybrid power or reserve power. The motor, the main engine and the propulsion device can be coaxially arranged, and the structure of the power system is simplified.

The present application relates to the technical field of health management of ship power system, and in particular to a ship diesel engine control and diagnosis collaborative method based on double-agent reinforcement learning, comprising the following steps: running state data acquisition and observation space construction, local feature coding and intention vector generation, two-way intention communication and feature fusion: each agent carries out cross-level information interaction, exchanges each other's intention vector, collaborative action generation and environment interaction, based on the fused features, two agents respectively output the decision action of the current time step through the action mapping head, collaborative action generation and environment interaction, and the network parameters are optimized through continuous interaction in the simulation environment; online deployment and execution of the control and diagnosis collaborative strategy, compared with the traditional control and diagnosis separation mode and single reinforcement learning control algorithm, the present application can not only effectively realize active fault tolerance and inhibit control performance degradation, but also improve the diagnosis accuracy rate of early weak faults and system robustness.

This utility model relates to the technical field of radiator-related components, and more particularly to a finned optimized air-cooled radiator, comprising a radiator shell, a liquid circulation pipe, a fin assembly, a dual-fan assembly, and a cover plate. The fin assembly consists of a first fin group, a middle fin group, and a second fin group, with a turbulence component disposed between the first fin group and the middle fin group. This utility model utilizes the shape memory alloy sheets of the turbulence component to automatically adjust their shape according to temperature. When the fin temperature exceeds 50 degrees Celsius under high load, the fins bend to form a spiral vortex, increasing the airflow disturbance intensity of the middle fin group and improving heat exchange efficiency compared to traditional fixed fin structures. This allows for rapid dissipation of instantaneous high heat from marine power systems, preventing equipment overheating and shutdown. The airflow distribution effect of the turbulence component reduces damage to the equipment from localized thermal stress. The first and second fin groups reduce wind resistance to ensure airflow, while the middle fin group increases the heat exchange area. The synergistic effect of these three sections enhances the overall heat dissipation capacity.

This invention relates to the technical field of ship systems, specifically to a ship intelligent engine room signal acquisition and analysis system, including a signal acquisition module, a reconstruction and fusion module, a safety domain calculation module, a safety margin prediction module, and a graded response module. The signal acquisition module is used to synchronously acquire multi-source time-series signals of the ship's power system; the reconstruction and fusion module constructs a joint state vector; the safety domain calculation module calculates the safety domain volume of the ship's power system at the current moment; the safety margin prediction module outputs the remaining safety margin of the system; and the graded response module is used to execute graded early warning or control actions based on the remaining safety margin of the system. In the deeply coupled control scenario of a ship's intelligent engine room, this invention achieves real-time, quantitative, and forward-looking assessment and proactive safety protection of the stability state of a high-dimensional nonlinear system, laying a crucial safety foundation for intelligent ship navigation.

The application provides a new energy ship power system failure mode identification method, device, computer equipment, storage medium and computer program product. The method comprises the following steps: acquiring real-time multi-modal data of a new energy ship power system, and extracting multi-modal fusion features based on the real-time multi-modal data; based on the multi-modal fusion features, searching in a pre-constructed failure mode knowledge graph to obtain each knowledge graph associated result associated with the real-time state of the new energy ship power system; splicing the multi-modal fusion features and the graph features of each knowledge graph associated result to obtain a feature splicing result; inputting the feature splicing result into a large language model to obtain a failure mode identification result for the new energy ship power system. The method can accurately and reliably identify the failure mode of the new energy ship power system.

This invention discloses a pre-trained online Gaussian process device and method for predicting hydrogen fuel cell voltage, applicable to marine propulsion systems. Addressing the problems of traditional models relying on real-ship data, weak generalization ability, and inability to adapt to battery aging, the device includes a sensor module, a memory, and a processor. The sensor module collects pressure, current, temperature, and voltage data; the memory stores the model and program; and the processor performs data processing and prediction calculations. The method pre-trains a Gaussian process regression model using experimental data, updates it online according to preset rules using real-time ship data, and outputs the prediction results after data preprocessing, model construction, updating, and prediction. This invention achieves high-precision prediction in zero-sample / few-sample stages, dynamically adapts to complex operating conditions and battery aging, operates efficiently without redundancy, and ensures reliable operation of marine hydrogen fuel cell propulsion systems.

This invention relates to the field of marine power system control technology, and particularly to a hybrid power management method for ships based on the synergy of shaft-driven power generation and lithium batteries. The method includes: real-time acquisition of the ship's power grid load demand, the output power of the shaft-driven power generation system, the state of charge of the lithium battery system, and the rotational speed of the ship's main engine; adaptively determining the current system operating mode; calculating the real-time power difference between the load demand and the output power of the shaft-driven power generation system; generating a target charge / discharge power for the lithium battery system; obtaining a safe command charge / discharge power; controlling the lithium battery system to execute the command charge / discharge power, and controlling the shaft-driven power generation system to operate according to the target of the current mode. Through precise power scheduling and adaptive switching of system operating modes, the method ensures that the ship's power system always operates in an energy-optimal state under different operating conditions.

A kind of ship power condenser system fault detection method based on multiscale feature fusion, the present application relates to ship power condenser system fault detection method based on multiscale feature fusion, belongs to ship power system fault diagnosis and safety monitoring field.The present application aims to solve the problem of insufficient detection accuracy and high false alarm rate of traditional fault diagnosis method.Process is as follows:step one, obtain the input and output information of condenser system;Step two, construct multiscale feature extraction model;Step three, obtain trained multiscale feature extraction model and parameters;Step four, input the online data of condenser system into trained multiscale feature extraction model, and trained multiscale feature extraction model outputs the predicted value of condenser liquid level and vacuum degree;Residual generator obtains online prediction error signal based on predicted value;Step five, fault diagnosis based on online prediction error.

The application discloses a kind of methanol fuel ship power system layered multi-dimensional fault diagnosis method and system, it is related to ship power system fault diagnosis and monitoring technical field, including: along the path of "methanol supply-chemical electric energy conversion-motor propulsion-ship energy efficiency", it is divided into four coupling levels, constructs and includes the layered coupling diagnosis model of each level local diagnosis function, system overall diagnosis function, collaborative monitoring and diagnosis iterative relationship and coupling correlation model;Collect and pre-process each level real-time operation data, input the model for fault diagnosis and cross-level correlation analysis, obtain diagnostic result and output, generate differentiated disposal proposal;The diagnosis numerical quantization of the application is accurate, strong objectivity, level correlation formula is extremely simple and practical, real-time is optimal;Coupling fault recognition is efficient, covers comprehensive, cascade fault trace accuracy, disposal is efficient;Strong adaptability, high reliability.

This invention relates to the field of simulation technology, providing a method and apparatus for thermal simulation of a ship's propulsion system. The method includes: acquiring simulation input parameters of the ship's propulsion system, the simulation input parameters including at least time information and spatial location information; inputting the simulation input parameters into a pre-trained thermal simulation model to obtain the simulation state prediction results output by the thermal simulation model; wherein the pre-trained thermal simulation model is obtained by iteratively updating the parameters of an initial deep neural network model with the objective of minimizing physical constraint loss; the physical constraint loss includes at least the equation residuals constructed based on the thermodynamic control equations of the ship's propulsion system, the initial condition residuals constructed based on the initial conditions corresponding to the thermodynamic control equations, and the boundary condition residuals constructed based on the boundary conditions corresponding to the thermodynamic control equations. This invention improves the real-time performance and generalization ability of thermal simulation of ship propulsion systems.

This invention discloses a fault diagnosis method for ship propulsion systems based on deep reinforcement learning, comprising: S1, standardizing the original acquired data to address noise, outliers, and dimensionality differences, ensuring the data is compatible with the input requirements of an LSTM network; S2, constructing an LSTM feature extraction network to mine key features of equipment health status from preprocessed time-series data, fully extracting time-series features; S3, transforming the feature vectors output by the LSTM into specific fault decisions, and intelligently optimizing the diagnostic strategy by constructing a reasonable state space, action space, reward function, and weight coefficient settings, combined with an experience replay mechanism. This invention also discloses a fault diagnosis device for ship propulsion systems based on deep reinforcement learning. This invention is applicable to real-time fault monitoring and precise location of core ship propulsion units and can be widely applied in the fields of ship automated operation and maintenance and artificial intelligence fault diagnosis technology.