机械制动器摩擦故障快速融合诊断与智能预报方法研究

项目名称： 机械制动器摩擦故障快速融合诊断与智能预报方法研究

项目编号： No.51205393

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 机械工程学科

项目作者： 阴妍

作者单位： 中国矿业大学

项目金额： 25万元

中文摘要： 本项目将机械制动器由于摩擦状态异常变化而导致其制动性能下降的现象称为"摩擦故障"，以盘式制动器作为研究对象，以避免摩擦故障引发的制动事故为研究目标，开展制动器摩擦故障快速融合诊断与智能预报方法研究。首先，通过模拟制动试验，研究制动过程中的动态摩擦特征，构建制动器动态摩擦状态的客观表征方法，并基于此研究制动器摩擦故障的特征提取和模式识别方法。其次，通过制动器摩擦故障诊断试验，研究制动器摩擦状态信号的快速采集方法、高可靠性传输技术和多传感器信息快速融合分析机制；基于证据理论和人工智能技术，研究制动器摩擦故障的异类多源信息快速融合诊断方法。最后，基于人工智能技术和制动器摩擦试验结果，研究制动器摩擦状态的智能预测方法；基于模糊专家系统和制动器故障诊断试验结果，研究制动器摩擦故障的智能预报方法。本项目的研究结果对于提高机械制动器的工作可靠性和保障机械系统的制动安全，都将具有重要的理论价值和现实意义。

中文关键词： 摩擦故障；盘式制动器；融合监测；智能诊断；故障预报

英文摘要： This project focuses on the friction faults of mechanical brakes (FFMB) which are defined as any braking performance deteriorations connected with abnormal tribological variations of the brake pairs. By taking the disc brake as research object, this project will investigate on the fast fusion diagnosis and intelligent forecast methods of the FFMB for avoiding any connected braking accidents. Firstly, based on some simulating braking experiments, the dynamic friction features of the brakes will be extracted and the objective method characterizing the dynamic friction states will be established. Then the fault features of the FFMB will be extracted and the fault mode will be identified based on the objective tribological characterizing method. Secondly, based on some FFMB diagnosis experiments, the quick signal collecting method, the high reliability signal transmission technology and the fast fusion analysis method based on multi-sensor data will be bulit up. Then the fast fusion diagnosis method based on multi-source informations for the FFMB will be established by the evidence theory and artifical intelligent (AI) technology. Finally, an intelligent predicting method for the friction state of brakes will be founded based on the AI technology and the simulating braking experiments. The intelligent forecast metho

英文关键词： Friction fault；Disc brake；Fusion monitoring；Intelligent diagnosis；Fault predicting