This paper investigates a machinery health monitoring method using dynamic gearbox models (DGM) and harmonic wavelet transforms (HWT) for vibration response analysis. Gearbox vibration measurement is typically processed via frequency spectrum analysis to identify faults. However, the gearbox system may operate with varying rotational speed, as in many types of wind turbines. In such applications, harmonic wavelet transform analysis has been shown to capture the physics of events with minimal leakage between frequency bands, good frequency resolution and good time resolution. Implementing HWT signal processing for fault detection requires the development of libraries of healthy and faulty gear states to use with pattern recognition. The development of DGM can help to greatly reduce the library development and provide a physically meaningful connection of fault indicators to the actual fault patterns. In this research, a comprehensive DGM is developed, followed by HWT analyses to illustrate the fault detection and diagnosis procedure and capability.

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