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- W2955845446 abstract "ABSTRACTVibration analysis is an effective tool to identify and predict failure using SignalProcessing based on condition monitoring. Accordingly, machine faults can bedetected and diagnosed using different post processing of vibration signature. Thepresent study is to prove that Machine Health and availability achievement becomingeasier by using different vibration analysis techniques. Three different types ofnonstationary signals are addressed in this paper to evaluate the technical conditionsof Paper Machine Forming Roll. Forming Roll consists of frequency drive motor,gearbox and a symmetric rotor supported on two similar bearings. The present studyis focusing on Forming Roll Bearings Condition Monitoring. A cost wise comparisonof maintenance strategies is made to confirm that Condition based Maintenance isthe most cost-effective strategy. In the past portable data-collectors were used tomeasure vibration levels, but Condition based Monitoring had taken place to avoidany sudden fault developing before next time schedule. Applying different vibrationanalysis techniques such as Spectrum, Waveform and Impact Demodulation willsupport fault detection, diagnosis and decision-making. The present study provedthat Impact demodulation is recommended to specify faulty bearing source locationand severity, while time waveform or spectrum analysis techniques can detect faultprogress but couldn’t distinguish severity due to bearings similarity. Based on ImpactDemodulation technique decision is made to exchange only the higher severity faultybearing and postponed the other one for next planned shutdown. Consequently, themachine availability and health can be achieved by reducing vibration impact around100 % through continuous condition monitoring." @default.
- W2955845446 created "2019-07-12" @default.
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- W2955845446 date "2018-04-01" @default.
- W2955845446 modified "2023-09-24" @default.
- W2955845446 title "MACHINE HEALTH MONITORING USING VIBRATION ANALYSIS" @default.
- W2955845446 cites W2196451457 @default.
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- W2955845446 doi "https://doi.org/10.21608/amme.2018.34729" @default.
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