A novel fault diagnosis technique for enhancing maintenance and reliability of rotating machines

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    Abstract

    Equipment standardisation as a cost-effective means of rationalising maintenance spares has significantly increased the existence of several identical (similar components and configurations) ‘as installed’ machines in most industrial sites. However, the dynamic behaviours of such identical machines usually differ due to variations in their foundation flexibilities, which is perhaps why separate analysis is often required for each machine during fault diagnosis. In practice, the fault diagnosis process is even further complicated by the fact that analysis is often conducted at individual measurement locations for different speeds, since a significant number of rotating machines operate at various speeds. Hence, through the experimental simulation of a similar practical scenario of two identically configured ‘as installed’ rotating machines with different foundation flexibilities, this study proposes a simplified vibration-based fault diagnosis technique that may be valuable for fault detection irrespective of foundation flexibilities or operating speeds. On both experimental rigs with different foundation flexibilities, several common rotor-related faults were independently simulated. Data combination method was then used for computing composite higher order spectra (composite bispectrum and composite trispectrum), after which principal component analysis is used for fault separation and diagnosis of the grouped data. Hence, this article highlights the usefulness of the proposed fault diagnosis approach for enhancing the reliability of identical ‘as installed’ rotating machines, irrespective of the rotating speeds and foundation flexibilities.
    Original languageEnglish
    Pages (from-to)604-621
    Number of pages17
    JournalStructural Health Monitoring
    Volume14
    Issue number6
    Early online date24 Sept 2015
    DOIs
    Publication statusPublished - 1 Nov 2015

    Keywords

    • reliability
    • condition-based maintenance
    • data fusion
    • composite spectra
    • principal component analysis
    • multiple speeds
    • multiple foundations

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