Eventuality segments extraction from a time series based on phase space reconstruction

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (19) : 39-47.

WU Xu1, DONG Yonggui2, HOU Zhongjie2, CHENG Weidong1

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Abstract

In a condition monitoring system, extracting similarity segments containing some potentially useful imformation from a time series obtained with a signal acquisition system is the basis for further data processing, such as, feature extraction and state analysis. The existing similarity subsequences searching algorithm usually uses a fixed sliding length window to extract equal length subsequences for similarity matching calculation. However, in practical applications, subsequences with similar characteristics are not inevitably equal in length to make the extracted similarity segments not have eventuality. Here, aiming at this problem, a similarity subsequence extraction method was studied based on phase space reconstruction. Firstly, a 1-D time series was embedded in a 2-D phase space according to the time delay method, and a peak feature sequence corresponding to the time series was calculated. Then, the existing empirical knowledge was used to determine the position of subsequence segmentation with the peak feature sequence, and divide eventuality subsequences with unequal lengths. Finally, the acquired eventuality subsequences were clustered to extract similarity subsequences. Test results of ECG signals and faulty bearing vibration signals indicated that the similarity segments extracted using the proposed method are unequal in length and have eventuality characteristics.

Key words

time series / similarity subsequence / eventuality subsequence / phase space

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WU Xu1, DONG Yonggui2, HOU Zhongjie2, CHENG Weidong1. Eventuality segments extraction from a time series based on phase space reconstruction[J]. Journal of Vibration and Shock, 2020, 39(19): 39-47

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