Method for the extraction of shock signal features based on the upper limit of density integral

Haikun Yang1 , Hongxia Pan2

1School of Mechatronics Engineering, North University of China, Taiyuan, China

2School of Mechanical and Power Engineering, North University of China, Taiyuan, China

1Corresponding author

Journal of Vibroengineering, Vol. 21, Issue 6, 2019, p. 1751-1760.
Received 10 September 2018; received in revised form 13 January 2019; accepted 26 January 2019; published 30 September 2019

Copyright © 2019 Haikun Yang, et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Creative Commons License

Shock signal features must be extracted for use in pattern recognition or fault diagnosis. In this work, we proposed a method for the feature extraction of shock signals, which are vibration signals that change faster and have larger amplitude ranges than general signals. First, we proposed the concepts of amplitude density for monotonic functions and piecewise monotonic functions. On the basis of these concepts, we then proposed the concept of the upper limit of density integral (ULDI), which was adopted to obtain signal features. Then, we introduced two types of serious fault cracks to the latch sheet of an automatic gun mechanism that is used on warships. Next, we applied the proposed method to extract the features of shock signals from data acquired when the automatic gun mechanism fired with normal and two fault patterns. Finally, we verified the effectiveness of our proposed method by applying the features that it extracted to a support vector machine (SVM). Our proposed method provided good results and was superior to the traditional statistics-based feature extraction method when applied to a SVM for classification. In addition, the former method demonstrated better generalisation than the latter. Thus, our method is an efficient approach for extracting shock signal features in pattern recognition and fault diagnosis.

Method for the extraction of shock signal features based on the upper limit of density integral

  • We proposed the concept of upper limit of density integral to obtain signal features.
  • The proposed method was applied to extract the features about an automatic gun mechanism.
  • The proposed method was superior to the traditional statistics-based feature extraction method.

Keywords: signal processing, feature extraction, pattern recognition, fault diagnosis.


The authors gratefully acknowledge the support from the National Natural Science Foundation of China (Grants 51675491 and 51175480).


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