基于全寿命周期退化信息的高速列车轮对轴承剩余寿命预测方法研究

项目名称： 基于全寿命周期退化信息的高速列车轮对轴承剩余寿命预测方法研究

项目编号： No.51505066

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 刘志亮

作者单位： 电子科技大学

项目金额： 20万元

中文摘要： 高速列车轮对轴承振动信号在退化过程中呈现出强噪声干扰与强耦合调制等复杂特点，建立其运行状态信息与剩余寿命之间的关联存在巨大挑战。本课题以轮对轴承为研究对象，采用动态信号处理、优化理论和人工智能等分析手段，结合加速退化试验验证，研究以下内容：（1）研究基于一体优化框架的局部均值分解理论及以其为核心的动态信号解调分析方法，研究退化过程不同阶段中敏感频带和敏感乘积函数分量的准确定位与识别方法；（2）研究退化状态表征的非线性评价指标及其自适应解析优化方法，研究多种评价准则的融合策略及表征优选方法；（3）研究基于健康状态评估的剩余寿命预测理论与建模方法，建立退化状态表征与剩余寿命之间的复杂映射关系，实现高精度的轮对轴承剩余寿命估计。本课题源于重大技术装备与重大设施寿命预测共性基础研究中的重要科学问题，将为高速列车的安全监测与健康管理提供理论支撑，具有重要的研究价值和工程应用前景。

中文关键词： 轮对轴承；信号解调分析；退化状态表征评价与选择；健康状态评估；剩余寿命预测

英文摘要： Degradation process for wheelset bearings of high-speed trains exhibits many complex characteristics, e.g. strong noise interference and strong coupling modulation, which bring a big challenge in establishing a link between condition monitoring information and remaining useful life. This project focuses on the objective of wheelset bearings. By validating with accelerated degradation tests and using advances in dynamic signal processing, optimization theory and artificial intelligence, this project aims to study the following key issues. (1) Study an integrated optimization framework for local mean decomposition algorithm; study dynamic signal demodulation methods with the optimized local mean decomposition at the core; and study accurate location methods for sensitive bands in frequency domain and recognition methods for sensitive production functions. (2) Study nonlinear evaluation metrics and their adaptive analytical optimization methods for degradation characterization indicators; study multi-metric fusion strategy and selection methods for those indicators; and achieve an accurate evaluation and selection for the life-cycle degradation indicators. (3) Study remaining useful life prediction strategies and modeling methods based on health state assessment; build a complex mapping between the degradation indicators and remaining useful life; and achieve remaining useful life prediction of wheelset bearings with high precision. The project adheres to well accepted scientific research guidelines in the field of remaining useful life prediction of sophisticated engineering systems and complex infrastructures. The expected results from this project could provide theory support to safety monitoring and health management for high-speed trains, and thus the project has important scientific significance and engineering application value.

英文关键词： wheelset bearing;signal demodulation analysis;degradation indicator evaluation and selection;health state assessment;remaining useful life prediction