1. 汇报安排

题目：参加IMAC-XXXVI总结报告会

时间：2018年3月3日10:00—11:00

地点：曲江校区西五楼南A228会议室

报告人：博1601班同超玮

2. 参加国际会议信息

会议名称：The 36th International Modal Analysis Conference

会议时间：Feb 12-15, 2018

会议地点：Rosen Plaza Hotel - Orlando ( Florida ), America

会议简介：

IMAC-XXXVI is the 36nd International Modal Analysis Conference of the Society for Experimental Mechanics, focusing on structural dynamics. IMAC has evolved to encompass the latest technologies supporting structural dynamics.

The current thrusts in simulation and modeling, nonlinear dynamics, sensors, signal processing and control spanning the full range of engineering disciplines, civil, mechanical, industrial, electrical, aerospace, automotive, etc. are discussed.

The theme for IMAC-XXXVI is ‘Engineering Extremes: Unifying Concepts in Shock, Vibration, and Nonlinear Mechanics.’ This theme attempts to address the current demands in design as we push the limits of our materials, performance and response.

In addition to topics associated with our theme, this Call for Papers offers the traditional general topics associated with IMAC as well as topics developed by our technical divisions. We are also offering an emerging technologies topic that encourages the development of sessions addressing relating technologies that are being integrated into our standard topics.

We encourage IMAC participants to also develop sessions and be involved with the various technical divisions within the Society.

会议交流工作：

Presentation:Nonlinear Squeezing Wavelet Transform for Rub-Impact Fault Detection.汇报人—同超玮

3. 参会论文信息

Title：Nonlinear Squeezing Wavelet Transform for Rub-Impact Fault Detection

Author：同超玮，陈雪峰，王诗彬

Abstract:Classical time-frequency analysis methods can depict time-frequency structure of non-stationary signals. However, they may have a shortage in extracting the weak components with small amplitude hidden in complex signals, because their time-frequency representation coefficients are proportional to the amplitude or energy of a signal. In this paper, we present a new data analysis method, called nonlinear squeezing wavelet transform, to extract the weak feature of highly oscillating frequency modulation for rotor rub-impact fault. The time-frequency representation of the proposed method is independent of the signal amplitude and only relevant to the signal phase, thus it can be used to characterize the time-frequency pattern of non-stationary multi-component signals, especially for weak components detection. The experiments on simulated signals verify the effectiveness of the proposed method in weak signal detection. Finally, the validity of this method is demonstrated to extracting the feature on a real rotor system with weak rub-impact fault.