Short-time Fourier Transform Using Odd Symmetric Window Function

Miaofen Li; Youmin Liu; Shaodan  Zhi; Tianyang Wang; Fulei Chu

doi:10.37965/jdmd.v2i2.39

Authors

Miaofen Li Department of Mechanical Engineering, Tsinghua University, Beijing , China
Youmin Liu Beijing Institute of Space Launch Technology, Beijing, China
Shaodan Zhi Beijing Jiaotong University, Beijing, China
Tianyang Wang Department of Mechanical Engineering, Tsinghua University, Beijing, China
Fulei Chu Department of Mechanical Engineering, Tsinghua University, Beijing, China

DOI:

https://doi.org/10.37965/jdmd.v2i2.39

Keywords:

STFT, instantaneous frequency (IF), time-frequency analysis

Abstract

In this paper, a novel time–frequency (TF) analysis method, called the short-time Fourier transform using odd symmetric window function (OSTFT), is proposed using odd symmetric window function to replace the conventional even window function of STFT. Different from conventional STFT acquiring the amplitude maximum at time and frequency centers, OSTFT acquires the minimum amplitude of 0. Hence, OSTFT can obtain a TF representation (TFR) with high TF resolution by utilizing the leaked energy rather than restraining it. It is worth to mention that the proposed OSTFT can vitiate the effect of window size we choose on the TFR obtained. Furthermore, it also has a good performance on signals with complex instantaneous frequencies (IFs), even crossing IFs. Because we just replace the conventional window function of STFT, the time-consuming of the proposed OSTFT is at the same level as the conventional STFT. The effectiveness of proposed OSTFT has been validated on two complex multi-component simulated numerical signals and a signal collected from the brown bat.

Conflict of Interest Statement
Fulei Chu is an Editor-in-Chief and Tianyang wang is an editorial board member for the Journal of Dynamics, Monitoring and Diagnostics, and both were not involved in the editorial review or the decision to publish this article. The authors declare that they have no conflict of interest.

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Author Biography

Tianyang Wang, Department of Mechanical Engineering, Tsinghua University, Beijing, China

Mainly engaged in research work in the field of fault diagnosis and signal analysis of large rotating machinery such as wind turbines and aero engines. Research directions: Modern signal processing, Dynamic modeling, Artificial intelligence, Pattern recognition.