【作者】 王延之； 吴军； 陈作懿； 邓超； 黎国强；

【Author】 WANG Yanzhi;WU Jun;CHEN Zuoyi;DENG Chao;LI Guoqiang;School of Naval Architecture & Ocean Engineering,Huazhong University of Science and Technology;School of Mechanical Science & Engineering,Huazhong University of Science and Technology;

【机构】 华中科技大学船舶与海洋工程学院； 华中科技大学机械科学与工程学院；

【摘要】 针对传统监测方法无法实现液压设备的智能化与个性化监测,且诊断效率低等问题,本文提出了一种基于边云端协同计算的液压设备健康监测机制,通过液压设备上的传感器实时采集其监测数据,经边缘计算,实现对液压设备运行状态的在线监测;结合云计算,运用人工智能算法实现液压设备的健康监测与寿命预测。研究结果表明,该机制可以实现液压设备异常状态的自动识别,且识别正确率较高,从而能够减少液压设备的维护成本,保障液压设备长时间安全稳定运行。更多还原

【Abstract】 Traditional monitoring methods are difficultly applied to the intelligent and personalized monitoring of hydraulic equipment, and diagnostic efficiency is low. This paper proposes a new health monitoring mechanism for hydraulic equipment based on edge cloud collaborative computing, which collects sensor data from the hydraulic equipment in real time, and realizes online monitoring of the running state of the hydraulic equipment through the edge calculation. Combined with cloud computing, artificial intelligence algorithms are introduced to realize the health monitoring and life prediction of hydraulic equipment. The results show that the proposed method can implement automatic identification of abnormal state of hydraulic equipment, and the recognition accuracy is high, which can reduce the maintenance cost of hydraulic equipment and ensure the safe and stable operation of hydraulic equipment for a long time.更多还原