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Normalisation of the amplitude modulation caused by time-varying operating conditions for condition monitoring
•Varying Operating Conditions (VOC) result in amplitude and frequency modulation.•The amplitude modulation impedes effective diagnosis and prognosis.•NAMVOC methods are proposed to attenuate the amplitude modulation under VOC.•This allows diagnosis and prognosis to be performed consistently under VO...
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Published in: | Measurement : journal of the International Measurement Confederation 2020-01, Vol.149, p.106964, Article 106964 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Varying Operating Conditions (VOC) result in amplitude and frequency modulation.•The amplitude modulation impedes effective diagnosis and prognosis.•NAMVOC methods are proposed to attenuate the amplitude modulation under VOC.•This allows diagnosis and prognosis to be performed consistently under VOC.•The method is investigated on numerical and experimental datasets.
Performing condition monitoring under time-varying operating conditions is challenging. The time-varying operating conditions result in amplitude and frequency modulation which mask the presence of incipient damage and make it difficult to distinguish between changes in the condition of the machine and changes in its operating conditions. In this work, the benefits of normalising the amplitude modulation caused by the varying operating conditions for condition monitoring are illustrated and a method is proposed to perform this normalisation. It is shown that the proposed method can be used as a pre-processing methodology for deterministic-random separation, it can be used to detect incipient damage and it can be used to reliably estimate the severity of the damage under time-varying operating conditions as well. The proposed method is investigated on numerical gearbox data and experimental gearbox data, where its benefits for condition monitoring under time-varying operating conditions are shown. |
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ISSN: | 0263-2241 1873-412X |
DOI: | 10.1016/j.measurement.2019.106964 |