露天煤矿机电设备故障诊断及维修系统设计

Design of Fault Diagnosis and Maintenance System of Mechanical and Electrical Equipment in Open-Pit Coal Mines

露天煤矿机电设备故障诊断是保障生产效率和经济效益的关键。针对露天煤矿机电设备的常见故障,设计一套集数据采集、特征提取、故障诊断、维修决策于一体的智能诊断与维修系统。该系统采用支持矢量机与卷积神经网络相结合的诊断算法,实现了高精度的设备状态评估和剩余寿命预测。通过对某矿山电铲的实证研究,验证了所提出系统的有效性。

Fault diagnosis of mechanical and electrical equipment in open-pit coal mine is the key to ensure production efficiency and economic benefit.Aiming at the common faults of electromechanical equipment in open-pit coal mine,an intelligent diagnosis and maintenance system is designed,which integrates data collection,feature extraction,fault diagnosis and maintenance decision.The diagnosis algorithm which supports vector machine and convolutional neural network is adopted in this system to realize high precision equipment state evaluation and remaining life prediction.The validity of the proposed system is verified by the empirical study of a mine electric shovel.