Internal combustion engine sound-based fault detection and diagnosis using adaptive line enhancers

Abstract In an internal combustion engine, the impulsive sounds are very often radiated owing to the faults of the engine. Thus it is important for a noise, vibration, and harshness engineer to detect and analyse impulsive sound signals for both fault diagnoses. However, it is often difficult to detect and identify impulsive signals because of interfering signals such as those due to engine firing, harmonics of crankshaft speed, and broadband noise components. These interferences hinder the early detection of faults and improvement of sound quality. In order to overcome this difficulty, a two-stage adaptive line enhancer which is capable of enhancing impulsive signals embedded in background noise is developed. This method is used to pre-process signals prior to time—frequency analysis via a bilinear methods such as the Wigner—Ville distribution and the Choi—Williams distribution.