Using energy time–frequency of Hilbert Huang transform to analyze the performance of the variable valve timing engine

Abstract

In this study, a diagnosis method was successfully implemented to identify different sounds coming from individual mechanical parts within a group of engine moving parts controlled through a variable valve timing system. The novelty of this diagnosis method is in the determination of specific sounds coming from each part within this group when they are in good working condition and without any defects. This will facilitate in early detection of faults occurring on the parts, identified through changes in the sound wave energy. Through this study, this diagnosis method was validated in three ways, namely the consistency of the results with previous studies, the synchronization of sounds from mechanical parts in overlapping cases, and the cross-correlation of engine sound modes that results from analysis using the Hilbert Huang Transform. In this paper, the distribution of sound energy according to its frequencies was utilized to distinguish which of the engine combustion chambers of a Dodge Journey 2.4 was faulty. To conduct that, the noise-based test technique was selected to record the engine sound. The results show that there is a link between the RMS energy of the engine sound and the engine output torque.

Early detection of myocardial ischemia in resting ECG: Analysis by HHT

“…The instantaneous frequency obtained by HHT has a clear physical meaning and can characterize the signal's local characteristics [14]. Despite the limited theoretical analysis, nonlinear and nonstationary signal problems can be solved with HHT [15][16][17][18]. HHT with EMD and Hilbert spectral analysis has been extensively used to analyze nonstationary signals, including heart failure, atrial brillation, and CAD [5].…”