机电设备服役寿命预测分析及研究

Analysis and Research on Service Life Prediction of Mechanical and Electrical Equipment

为提升设备可靠性并降低维护成本,需要对设备状态进行实时检测。在此基础上对设备的故障种类以及退化状态进行分析及预测,指定相应维修策略。考虑到设备服役寿命的关键问题为寿命预测以及故障维修决策,引入状态检测频率、检验检修方案、故障预测算法等相关概念来对设备寿命及维修成本进行分析。通过建立数据驱动的服役寿命预测模型对故障阶段进行有效分类,通过数值仿真的方式说明基于设备状态采集信息分析寿命预测效果并且对所提出决策方法的可靠性进行阐述。

In order to improve the reliability of equipment and reduce the maintenance cost,it is necessary to detect the equipment status in real time.On this basis,the failure types and degradation states of the equipment are analyzed and predicted,and the corresponding maintenance strategies are specified.Considering that the key problem of equipment service life is life prediction and fault maintenance decision,the paper introduces the concepts of state detection frequency,inspection and maintenance scheme,fault prediction algorithm and so on to analyze the equipment life and maintenance cost.Through the establishment of data-driven service life prediction model to effectively classify the fault stages,through the way of numerical simulation,the analysis of life prediction effect based on the equipment status acquisition information and the reliability of the proposed decision-making method are described.