The order-frequency spectral coherence and its integrated spectra (e.g. improved envelope spectrum, squared envelope spectrum) are some of the most powerful methods for performing fault diagnosis under time-varying operating ...

Incipient damage detection is important for critical rotating machines such as gearboxes found in the power generation, mining and aeronautical industries. However, the fault information frequently manifests in weak frequency ...

Performing condition monitoring on critical machines such as gearboxes is essential to ensure that the machines operate reliably. However, many gearboxes are exposed to variable operating conditions which impede the condition ...

Condition monitoring is very important to avoid unexpected breakdowns of expensive rotating machines found in the power generation and mining industries. The fault information in vibration signals is often buried in low ...

Hybrid methods for prognosis of mechanical components have the potential of improving remaining useful life (RUL) estimations. Hybrid methods combine physics-based and data-driven methods to diagnose faults and predict ...

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Performing condition monitoring on rotating machines which operate under fluctuating conditions remains a challenge, with robust diagnostic techniques being required for the condition inference task. Some of the developed ...

Condition monitoring is usually performed over long periods of time when critical rotating machines such as wind turbine gearboxes are monitored. There are many potential signal processing and analysis techniques that can ...

In this paper, a fault diagnostic methodology is developed which is able to detect, locate and trend gear faults under fluctuating operating conditions when only vibration data from a single transducer, measured on a healthy ...

Many sophisticated signal analysis techniques are developed to efficiently detect, localise and trend damage in rotating machine components such as bearings and gears for example. However, these techniques are generally ...