面向船舶的基于WPA-BP与虚拟现实的机舱安全监测

Ship-oriented Cabin Safety Monitoring Based on WPA-BP and Virtual Reality

为了提高对船舶机舱安全运行远程故障诊断的效率,对船舶机舱的智能化诊断与监测进行了研究,设计了一种船舶机舱安全监测系统;采用优化后的狼群算法对反向传播神经网络进行改进,并创新建立了狼群算法-反向传播基础上的机舱柴油机故障诊断模型;经实验测试实现了平均诊断准确率高达99.102%、响应时间0.048 ms的验证结果;经实际应用满足了船舶安全运行的需求,提高了故障诊断有效性。

In order to improve the efficiency of remote fault diagnosis for the safe operation of ship engine rooms,this paper studies the intelligent diagnosis and monitoring of ship engine rooms,and designs a ship engine room safety monitoring system.The optimized wolf pack algorithm is used to improve the back propagation neural network and innovatively establish the fault diagnosis model for cabin diesel engines based on the wolf pack algorithm back propagation.After experimental testing,the verification results show an average diagnostic accuracy of 99.102% and a response time of 0.048 ms.Through practical application,it meets the requirements for safe operation of ships,and improves the effectiveness of fault diagnosis.