矿山机电设备故障诊断技术与管理措施探讨

Exploration of fault diagnosis technology and management measures for mining electromechanical equipment

本文深入探讨了矿山机电设备故障诊断技术及其管理措施的加强,旨在通过先进的诊断技术和有效的管理策略,提升设备的运行效率和安全性。首先,介绍了故障诊断技术的基本框架,包括数据采集、处理与分析,以及预测模型的构建;然后,详细探讨了实用技术如专家系统、故障记录分析和神经网络等在实际应用中的优势与局限性;最后,本文强调了建立完善的管理体系、强化设备监管以及提升安全意识与培训的重要性。通过对比分析改进前后的设备故障率、维护成本和运行效率,本文展示了加强故障诊断技术和管理措施的显著效果,为矿山机电设备的高效可靠运行提供了有力支持。

This paper delves into the strengthening of fault diagnosis technology and management measures for mining electromechanical equipment,aiming to improve the operational efficiency and safety of equipment through advanced diagnostic technology and effective management strategies.Firstly,it introduces the basic framework of fault diagnosis technology,including data collection,processing and analysis,as well as the construction of predictive models.Subsequently,the advantages and limitations of practical technologies such as expert systems,fault record analysis,and neural networks in practical applications are discussed in details.Furthermore,it emphasizes the importance of establishing a sound management system,strengthening equipment supervision,and enhancing safety awareness and training.By comparing and analyzing the equipment failure rate,maintenance cost,and operational efficiency before and after improvement,this paper demonstrates the significant effect of strengthening fault diagnosis technology and management measures,providing strong support for the efficient and reliable operation of mining electromechanical equipment.