Adaptive Line Enhancer Filter Research Articles

Development of two-input adaptive noise canceller for wideband and narrowband noise signals

In this paper, the development of the single-stage two-input adaptive noise canceller that proposed by Widrow et al. is investigated. It is shown that the use of multi-stage cancellers instead of a single stage improves the performance of the conventional two-input adaptive noise canceller in a real life high-noise environment. In such environment, the background noise may contain both the wideband and narrowband (sinusoidal) noise components. In this contribution, the wideband noise and sinusoidal noise signals can be significantly suppressed using a new multi-stage adaptive noise cancellation scheme based on adaptive line enhancer (ALE) and Least Mean Square (LMS) filter. The proposed scheme is comprised of two stages. The first stage uses ALE filters, which are used to cancel the sinusoidal noise from the primary and reference input signals, whereas the wideband noise is cancelled using LMS adaptive filter in the second stage. The good performance of the proposed scheme has been verified via real-time implementation on the Texas Instruments TMS320C6713DSK.

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

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.