报告题目：Nonstationary signal processing based on time-frequency analyses for fault diagnosis of rotating machinery
报 告 人： 李富才教授（上海交通大学）
时间： 2017年11月１日下午3:30
地点： 安徽大学磬苑校区理工A楼102室
主办单位：电气工程与自动化学院
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科学技术处
2017年 10月 30日
报告人简介：
李富才，教授、博士生导师。上海交通大学机械系统与振动国家重点实验室、船舰设备噪声与振动控制国防重点学科实验室。教育部新世纪优秀人才，曾担任悉尼大学宇航与机电工程学院担任副研究员、东京大学环境与海洋工学系日本学术振兴会（JSPS）特别研究员。中国通用机械工业协会振噪检测与故障诊断专业委员会副主任委员兼秘书长、中国振动工程学会转子动力学分会常务理事、故障诊断专业委员会理事、中国仪器仪表学会设备结构健康监测与预警分会理事、《Journal of Vibration Engineering and Technologies》编委。研究方向：机电系统健康监测与故障诊断、振动噪声检测与动力学分析、传感技术与信号处理。
报告内容简介：
The condition monitoring and system (CMS) substantiates potential economic benefits and enables prognostic maintenance in rotating machinery failure prevention. The vibration-based analysis has been widely applied in the detection of weak or incipient faults. Several non-stationary signal processing methods, including succinct and fast empirical mode decomposition (SFEMD), enhanced empirical wavelet transform (EEWT), Modified polynomial chirplet transform (MPCT), time frequency analysis and enhanced empirical wavelet transform (TFA-EEWT), will be introduced. A variety of simulated and experimental signals of the rotating machinery under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the abovementioned methods. Results show that these methods are effective in diagnosing the bearing faults and the planetary gearbox faults.