Abstract
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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