Damage Identification of an Automotive Engine Based on Detection of Impact Vibration Using an Adaptive Filter

Abstract

In an automotive engine, faults induce impulsive vibrations and thereby degrade engine performance, making it important for an automotive engineer to detect and analyze impulsive vibration signals for fault diagnosis. However, detecting and identifying impulsive signals is often difficult because of interfering signals such as those due to engine firing, harmonics of crankshaft speed and broadband noise components. These interferences hinder early fault detection. To overcome this difficulty we present a two-stage ALEF (Adaptive Line Enhancer Filter) that is capable of enhancing impulsive signals embedded in background noise. This method is used to pre-process signals prior to time-frequency analysis via higher order methods such as the combined higher order time-frequency.

Diagnosis of Engine Misfiring Based on the Adaptive Line Enhancer

“…This approach has the disadvantage of requiring a triggering signal at the rate of once per revolution. In this paper a two-stage ALE (Adaptive Line Enhancer) (Lee and Cho, 2006)is applied for the enhancement of an impulsive signal embedded in background noise. This method does not require a reference signal and so can be simply applied.…”