摘要
针对复杂装备故障诊断实际需求,论文以装备故障智能诊断技术为研究对象,在分析故障特征及诊断方法的基础上,依托大数据分析平台,运用基于深度神经网络(DNN)的学习框架,构建基于模糊推理机制和深度学习的故障诊断预测模型。实验结果表明,该模型有效提高了舰船装备的故障诊断精度。
Aiming at the actual demand of complex equipment fault diagnosis,this paper makes the fault intelligent diagnosis technology of a certain type of equipment as research object,analyzes the characteristic of equipment and its fault diagnosis method,utilizes the learning framework of deep neural network,and presents an intelligent diagnosis model which is based on fuzzy reason mechanism and deep neural network.The experimental shows that this method improves the fault diagnosis accuracy of naval equipment.
作者
郑贵文
ZHENG Guiwen(Equipment Project Management Center of Naval Equipment Department,Beijing 100071)
出处
《舰船电子工程》
2019年第12期183-186,195,共5页
Ship Electronic Engineering
关键词
大数据分析
故障诊断
深度神经网络
big data analytics
fault diagnosis
deep neural network
