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博士生谯自健参加国际会议回国报告通知

发布时间:2017-05-31 点击数:

博士生谯自健参加国际会议回国报告通知

汇报题目:参加IEEE International Instrumentation Measurement and Technology Conference (IEEE I2MTC) 2017 参会报告

汇报时间:2017年6月2日(星期五) 19:00

汇报地点:科技园西五楼南205会议室

汇报人:谯自健

会议名称:2017 IEEE International Instrumentation Measurement and Technology Conference

会议时间:22-25 May 2017

会议地点:Turin, Italy

会议简介:I2MTC 2017 conference spans research, development and applications in the field of instrumentation and measurement science and technology. To enhance industry engagement and increase exchange between industry members, as well as between industry and academic members, I2MTC 2017 conference is employing Industry Sessions. These sessions will focus on all aspects of instrumentation and measurement technologies, methods, and applications achieved by our industry colleagues, giving an opportunity to the I&M industry to present to their colleagues their new technologies, new applications, or even new challenges.

会议交流工作

Oral and poster presentation: Weak signal detection based on underdamped multistable stochastic resonance

报告人:谯自健

参加论文信息

Title: Weak signal detection based on underdamped multistable stochastic resonance

Author: Yaguo Lei, Zijian Qiao, Xuefang Xu, Jing Lin

Abstract: Traditional overdamped stochastic resonance (SR) methods are difficult to match with complicated and variable input signals due to single stable-state types. Moreover, their performance depends on the parameter selection of highpass filters. To further explore the potential of SR, this paper studies the behavior of underdamped SR in a multistable nonlinear system by analyzing its output frequency responses, and presents a promising underdamped multistable SR method for weak signal detection and further incipient fault diagnosis of machinery. Numerical analyses indicate that the proposed method is supposed to possess two advantages: 1) the stable-state diversity of the multistable potential makes it easily match with input signals and 2) under-damped multistable SR is equivalent to a bandpass filter as the rescaling ratio varies, which is able to suppress the interference from multiscale noise. Simulated and experimental data of rolling element bearings demonstrate the effectiveness of the proposed method. For comparison, ensemble empirical mode decomposition (EEMD) method and traditional overdamped bistable SR method are also employed to process the data. The comparison results show that the proposed method can effectively detect incipient fault characteristics and perform better than traditional SR and EEMD methods.

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