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Signal Processing Techniques for Condition Monitoring

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Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot

Part of the book series: Springer Theses ((Springer Theses))

Abstract

Signal processing plays a significant role in building any condition monitoring system. Many types of signals can be used in the condition monitoring of machines, such as vibration signals as in this research; and processing these signals in an appropriate way is crucial in extracting the most salient features related to different fault types. A number of signal processing techniques can fulfil this purpose, and the nature of the captured signal is a significant factor in the selection of the appropriate technique. This chapter starts with a discussion of the proposed robot condition monitoring algorithm. Then, a consideration of the signal processing techniques which can be applied in condition monitoring is carried out to identify their advantages and disadvantages, from which the time-domain and discrete wavelet transform signal analysis are selected.

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Authors and Affiliations

  1. School of Mechanical and Systems Engineering, Newcastle University, Newcastle upon Tyne, UK

    Alaa Abdulhady Jaber

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  1. Alaa Abdulhady Jaber
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Correspondence to Alaa Abdulhady Jaber .

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Jaber, A.A. (2017). Signal Processing Techniques for Condition Monitoring. In: Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-44932-6_3

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  • DOI: https://doi.org/10.1007/978-3-319-44932-6_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44931-9

  • Online ISBN: 978-3-319-44932-6

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