摘要
船舶电力推进系统目前成为船舶推进系统的主流选择,电力推进系统对于保障船舶的安全稳定运行具有重要意义。因此,对采用电力推进系统的船舶进行电力推进系统故障诊断,成为船舶日常维护的一项重要工作。本文对船舶电力推进系统故障诊断系统进行研究,在Simulink环境下搭建故障诊断模型,并将BP神经网络应用于诊断系统,对电力推进系统的故障学习和诊断能力进行仿真。结果表明,该故障诊断系统可以提高网络的学习速度和诊断效果,具有很好的故障诊断能力,可以满足船舶电力推进系统的性能要求。
The ship electric propulsion system has become the mainstream choice of the current ship propulsion system,and the electric propulsion system is of great significance for ensuring the safe and stable operation of the ship. Therefore,it is an important task to diagnose the faults of the electric propulsion system accurately of the ship which uses the electric propulsion system. This paper,studied the ship power propulsion system fault diagnosis system, and built up the diagnostic model under the Simulink environment,and applied the application of BP neural network into the diagnosis system,did the simulation and analysis of the learning and diagnosing ability of the faults system. The results show that the fault diagnosis system can improve the learning speed and the diagnosis effect and has good ability for fault diagnosis,which can meet the requirements of the performance of the ship electric propulsion system.
出处
《舰船科学技术》
北大核心
2016年第6X期97-99,共3页
Ship Science and Technology
关键词
神经网络
电力推进
故障诊断
neural network
electric propulsion
fault diagnosis
