Analyzing Fault Characteristics Using Wavelet Transform Technology

Early damage in helicopter gearboxes typically generates non-stationary disturbance signals with variable periods superimposed on accompanying vibration signals. To replicate this phenomenon, we construct physically meaningful simulated datasets using amplitude-modulated signals combining base vibration frequencies with transient impulses. Code implementation involves generating synthetic signals through MATLAB's wavelet toolbox, where we apply continuous wavelet transforms (CWT) with Morlet wavelets for time-frequency analysis or discrete wavelet transforms (DWT) for multi-resolution decomposition. Key functions include cwt for continuous transform visualization and wavedec for signal decomposition up to 5 levels, enabling precise identification of fault-initiated transient components through detailed coefficient analysis. This methodology facilitates accurate characterization of early-stage gearbox faults and their temporal localization, supporting proactive maintenance strategies for helicopter systems.