Combustion anomaly detection via wavelet analysis of dynamic sensor signals

A method for detecting combustion anomalies within a gas turbine engine comprising:

• obtaining a sampled dynamic signal that is representative of combustion conditions comprising:
• obtaining a signal measured by a sensor associated with a combustor of the engine;
• and
• converting the signal obtained by the sensor to a sampled dynamic signal with an analog to digital convertor;
• providing a processor that:
• divides the sampled dynamic signal into time segments to derive a plurality of data points for each of the time segments;
• and
• transforms the sampled dynamic signal to a form that enables detection of whether the sensed combustion conditions within the combustor are indicative of one or more combustion anomalies of interest comprising processing each time segment by:
• performing a wavelet transform to calculate wavelet coefficients for the data points within the processed time segment;
• targeting at least one region of interest within the wavelet transformed segment;
• and
• normalizing the amplitude of the wavelet coefficients within each targeted region by a baseline signal;
• and
• determining whether any combustion anomalies have occurred during each of the time segments using the normalized amplitudes of the wavelet coefficients within each targeted region by comparing the normalized amplitudes of the wavelet coefficients within each target region to a predetermined threshold amplitude.