Research on the Life Prediction Method of Key Components for the Optimization of EMU Repair Class and Repair System
The EMU is a highly complex transportation tool,and the reliability of its key parts is directly related to the safe operation of the train.These parts will be affected by various factors,such as mechanical wear and fatigue damage in the course of a long period of service,which will lead to a gradual decline in their performance.Therefore,accurate life prediction and management of these parts is the key to ensuring the safe and efficient operation of EMUs.In the field of train life prediction research,many scholars predict from deterministic fatigue life and uncertainty fatigue life.In recent years,there are more and more life prediction researches in the field of high-end equipment such as airplanes,ships,etc.,and the life prediction is researched from the basic theories of multiple fields such as mechanics,statistics,and detection technology respectively.This article takes the key parts of the EMU as the research object,integrates data such as vehicle operation status and maintenance and operation,introduces data mining technology,builds a key part life prediction method based on the repair class and repair system to accurately predict the remaining service life of the parts,and uses digital means to dynamically monitor their remaining life,provides data support for accurate decision-making in maintenance and operation,spare part management,provides a basic guarantee for safe vehicle operation and decision-making basis for the railway bureau to effectively reduce the cost of train operation.
EMUrepair class and repair systemlife predictionkey partcomponent
万方数据
维普
