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NON-STATIONARY SIGNAL DENOISING USING TIME-FREQUENCY CURVE SURFACE FITTING

Journal of Electronics(China) 2007年第6期24卷 776-781页

作者： Liu Xiaofeng Qin Shuren Bo Lin Test Center of Mechanical Engineering Chongqing University Chongqing 400044 China

Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.

关键词： Time-frequency decomposition elementary function Time-Frequency Distribution Series (TFDS) Curve surface fitting Noise suppressing

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Adaptive Time Frequency Distribution Based on Linear Chirp Modulated Gaussian functions

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Advances in Manufacturing 2000年第1期4卷 31-37页

作者： Shi-wei Ma Guang-hua Chen Jia-mei Deng Jia-lin Cao School of Mechanical and Electronic Engineering and Automation Shanghai University Shanghai China

We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an improved adaptive time frequency distribution is developed, which is non negative, free of cross term interference, and of better time frequency resolution. The paper presents an effective numerical algorithm to estimate the optimal parameters of the basis. Simulations indicate that the proposed approach is effective in analyzing signal's time frequency behavior.

关键词： adaptive time frequency distribution elementary function subspace decomposition STFT WVD

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