Research On Status Monitoring And Fault Diagnosis Of Ship Power System

During these years,as the scale of ships expands continuously,the control system requirements of ships augmented,the current control system is tough to adapt to the higher and higher requirements.The operating environment of the ship is abominable,and also the factors that affect the operation state have certain randomness.Once a fault happens,if it’s not handled in time,it’s straightforward to cause installations damage,influence the steadiness of the ship,and even cause accidents,threatening the security of the ship and its personnel.To guarantee the secure run of the boats,it is very important to carry out ship conditions monitoring and fault diagnosis.Given the above problems,this paper takes the new generation information technology as the core and takes the experimental vessel of Harbin Engineering University as the research object to research the condition monitoring and fault diagnosis of ship’s electric system.First,according to the structure of the power system of the experimental vessel of Harbin Engineering University and the parameters and mathematical model of each device,the modular modeling method is used to model each device.Then,according to the topology of the power system of the experimental vessel of Harbin Engineering University,each device is encapsulated and combined to complete the modeling of the power system of the experimental vessel of Harbin Engineering University.After that,the model is used to simulate the actual system and carry out simulation analysis of different operating conditions and typical faults to obtain the trend of system changes under different operating conditions and the signs of different faults of the equipment.Secondly,through advanced remote communication technology,data processing technology,and big data technology,an online UDPS algorithm with real-time is summarized,through which data related to equipment operation is associated and mapped to the digital system and stored in the virtual data table.Then QT visualization technology is used to realize the monitoring of real-time data of the system.Finally,Condition detection by analyzing data onto circuit breakers and relay protection devices in real-time data.Where the checked results showed that the circuit breaker and relay protection equipment are not acting,the data-based state identification algorithm is used to determine the operating state of the equipment and realize the state monitoring of the system;When the checked results showed the action of the circuit-breaker and the relay protection equipment,the location of the fault is determined in the location of the action signal,after which the fault is further diagnosed using the Troubleshooting technology based on multi-information fusion neural network to determine the specific type of faults and give maintenance recommendations for the corresponding fault to achieve fault diagnosis of the system.