2014•Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and ReliabilityRequires access

Combined bispectrum and trispectrum for faults diagnosis in rotating machines

Akilu Yunusa‐Kaltungo, Jyoti Kumar Sinha

Open publisher page 19 citations

Abstract

Over the years, condition monitoring of rotating machines has been extensively applied for enhancing equipment reliability and maintenance cost-effectiveness, through the early detection and reliable diagnosis of incipient machine faults. Earlier studies suggest that bispectrum analysis is a good tool for detecting and distinguishing rotor-related faults in rotating machines, with a significantly reduced number of vibration sensors. Now, the trispectrum analysis is also applied to the measured vibration data, so as to explore the usefulness of this analysis in the diagnosis. It is observed that the trispectrum further improves the reliability of rotating machines’ faults diagnosis. This article presents the results and observations related to the bispectrum and trispectrum analyses for fault(s) diagnosis, through an experimental rig with different faults simulation.

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What this paper is about

Over the years, condition monitoring of rotating machines has been extensively applied for enhancing equipment reliability and maintenance cost-effectiveness, through the early detection and reliable diagnosis of incipient machine faults. Earlier studies suggest that bispectrum analysis is a good tool for detecting and distinguishing rotor-related faults in rotating machines, with a significantly reduced number of vibration sensors. Now, the trispectrum analysis is also applied to the measured vibration data, so as to explore the usefulness of this analysis in the diagnosis. It is observed that the trispectrum further improves the reliability of rotating machines’ faults diagnosis. This article presents the results and observations related to the bispectrum and trispectrum analyses for fault(s) diagnosis, through an experimental rig with different faults simulation.

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Available abstract

Over the years, condition monitoring of rotating machines has been extensively applied for enhancing equipment reliability and maintenance cost-effectiveness, through the early detection and reliable diagnosis of incipient machine faults. Earlier studies suggest that bispectrum analysis is a good tool for detecting and distinguishing rotor-related faults in rotating machines, with a significantly reduced number of vibration sensors. Now, the trispectrum analysis is also applied to the measured vibration data, so as to explore the usefulness of this analysis in the diagnosis. It is observed that the trispectrum further improves the reliability of rotating machines’ faults diagnosis. This article presents the results and observations related to the bispectrum and trispectrum analyses for fault(s) diagnosis, through an experimental rig with different faults simulation.

Key concepts: Trispectrum, Bispectrum, Reliability (semiconductor), Vibration, Fault (geology), Rotor (electric), Engineering, Computer science

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