• Nishchal K. VermaEmail author
  • Al Salour
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 256)


As mentioned in Chap.  1, the real-time machine data is collected, which may be corrupt or inconsistent due to the presence of environmental noise. Therefore, the cleaning of data is required to remove unwanted frequencies as well to reduce the size of data for further analysis. This chapter details the second most important step of fault diagnosis framework, i.e., pre-processing of data. Low-quality data leads to misleading results, therefore, to make a better, robust, and more accurate fault classification model, pre-processing is required. The pre-processing involves filtering, clipping, smoothing, and normalization methods. Further, a graphical representation of the acoustic signal has been introduced. The chapter ends by   a briefing of the development of pre-processing tool.


  1. 1.
    Verma, N.K., Sevakula, R.K., Dixit, S., Salour, A.: Intelligent condition based monitoring using acoustic signals for air compressors. IEEE Trans. Rel. 65(1), 291–309 (2016)CrossRefGoogle Scholar
  2. 2.
    Verma, N.K., Agarwal, A., Sevakula, R.K., Prakash, D., Salour, A.: Improvements in preprocessing for machine fault diagnosis. In: IEEE 8th International Conference on Industrial and Information Systems, Kandy, Sri Lanka, pp. 403–408 (2013)Google Scholar
  3. 3.
    Verma, N.K., Sevakula, R.K., Thirukovalluru, R.: Pattern analysis framework with graphical indices for condition-based monitoring. IEEE Trans. Rel. 66(4), 1085–1100 (2017)CrossRefGoogle Scholar
  4. 4.
    Verma, N.K., Singh, S., Gupta, J.K., Sevakula, R.K., Dixit, S., Salour, A.: Smartphone application for fault recognition. In: 6th International Conference on Sensing Technology, Kolkata, India, pp. 1–6 (2012)Google Scholar
  5. 5.
    Verma, N.K., Singh, J.V., Gupta, M., Sevakula, R.K., Dixit, S.: Windows mobile and tablet app for acoustic signature machine health monitoring. In: International Conference on Industrial and Information Systems, Gwalior, India, pp. 1–6 (2014)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Inter-disciplinary Program in Cognitive ScienceIndian Institute of Technology KanpurKanpurIndia
  2. 2.Boeing Research and TechnologySaint LouisUSA

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