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A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition

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Abstract

A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference characteristics. However, it suffers from heavy computational overhead and large execution time. The paper, therefore, uses a novel fast discrete sparse S-transform (SST) suitable for extracting time frequency response to monitor non-stationary signal parameters, which can be ultimately used for disturbance detection, and their pattern classification. From the sparse S-transform matrix, some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based classifier. This algorithm is robust under noisy conditions. Various power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as well. Some real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed algorithm. All the simulation results imply that the proposed technique is very much efficient.

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Authors and Affiliations

  1. Multidisciplinary Research Cell, Siksha O Anusandhan University, Khandagiri Square, Bhubaneswar, 751030, India

    N. R. Nayak, P. K. Dash & R. Bisoi

Authors
  1. N. R. Nayak
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  2. P. K. Dash
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  3. R. Bisoi
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Corresponding author

Correspondence to P. K. Dash.

Additional information

N. R. Nayak received the B. Eng. in electronics and telecommunication from Utkal University, India in 1992, the M. Eng. degree in communication system engineering from Biju Patnaik University of Technology, India in 2004, and the Ph. D. degree from Siksha “O” Anusandhan University, India in 2017. He is currently the director of Microsys Infotech, India.

His research interests include signal processing, pattern recognition and classification.

P. K. Dash received the M. Eng. degree in electrical engineering from Indian Institute of Science, India in 1964, the Ph. D. degree in electrical engineering from the Sambalpur University, India in 1972, and the D. Sc. degree in electrical engineering from the Utkal University, India in 2003.

He is currently director of research in the Multidisciplinary Research Cell of the Siksha “O” Anusandhan University, India. He has published more than 500 papers in international journals and conferences.

His research interests include renewable energy, micro and smart grid, machine intelligence, signal processing and control, power quality.

R. Bisoi received the M. Eng. degree in computer application from North Orissa University, India in 2011, and the Ph. D. degrees in computer engineering from Siksha “O” anusandhan University, India 2015. She is currently working as a research officer in the Multidisciplinary Research Cell of Siksha “O” Anusandhan University, India.

She has published 25 papers in international journals and conferences.

Her research interests include computing software, data mining, machine intelligence and bioinformatics.

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Nayak, N.R., Dash, P.K. & Bisoi, R. A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition. Int. J. Autom. Comput. 16, 398–412 (2019). https://doi.org/10.1007/s11633-018-1113-3

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