Design of Adaptive Filter for Health Monitoring on a Gearbox

2006 ◽  
Vol 321-323 ◽  
pp. 1237-1240
Author(s):  
Sang Kwon Lee ◽  
Jung Soo Lee
Keyword(s):  
Signal Processing ◽  
Frequency Domain ◽  
Adaptive Filter ◽  
Health Monitoring ◽  
Background Noise ◽  
Adaptive Signal Processing ◽  
Vibration Signals ◽  
Time Frequency ◽  
Frequency Representation ◽  
Adaptive Signal

Impulsive vibration signals in gearbox are often associated with faults, which lead to due to irregular impacting. Thus these impulsive vibration signals can be used as indicators of machinery faults. However it is often difficult to make objective measurement of impulsive signals because of background noise signals. In order to ease the measurement of impulsive signal embedded in background noise, we enhance the impulsive signals using adaptive signal processing and then analyze them in time and frequency domain by using time-frequency representation. This technique is applied to the diagnosis of faults within laboratory gearbox.

Fault Identification for Rotating Machinery Using Adaptive Signal Processing and Time-Frequency Analysis

1997 ◽  
Author(s):  
Sang-Kwon Lee ◽  
Paul R. White
Keyword(s):  
Signal Processing ◽  
Background Noise ◽  
Combustion Engine ◽  
Adaptive Signal Processing ◽  
Rotating Machinery ◽  
Fault Identification ◽  
Vibration Signals ◽  
Time Frequency ◽  
Frequency Representation ◽  
Adaptive Signal

Abstract Impulsive sound and vibration signals in rotating machinery are often associated with faults which lead to due to irregular impacting. Thus these impulsive sound and vibration signals can be used as indicators of machinery faults. However it is often difficult to make objective measurement of impulsive signals because of background noise signals. In order to ease the measurement of impulsive sounds embedded in background noise, we enhance the impulsive signals using adaptive signal processing and then analyze them in time and frequency domain by using time-frequency representation. This technique is applied to the diagnosis of faults within internal combustion engine and industrial gear.

Two-Stage Adaptive Line Enhancer and Sliced Wigner Trispectrum for the Characterization of Faults from Gear Box Vibration Data

1999 ◽  
Vol 121 (4) ◽  
pp. 488-494 ◽  
Author(s):  
S. K. Lee ◽  
P. R. White
Keyword(s):  
Background Noise ◽  
Two Stage ◽  
Vibration Signals ◽  
Time Frequency ◽  
Vibration Data ◽  
Frequency Representation ◽  
Frequency Domains ◽  
Adaptive Line Enhancer ◽  
Gear Fault

Impulsive sound and vibration signals in gears are often associated with faults which result from impacting and as such these impulsive signals can be used as indicators of faults. However it is often difficult to make objective measurements of impulsive signals because of background noise signals. In order to ease the measurement of impulsive sounds embedded in background noise, it is proposed that the impulsive signals are enhanced, via a two stage ALE (Adaptive Line Enhancer), and that these enhanced signals are then analyzed in the time and frequency domains using a Wigner higher order time-frequency representation. The effectiveness of this technique is demonstrated by application to gear fault data.

scholarly journals A Fast Adaptive Speech Extraction Method using Blind Source Separation for Audio Signal Processing

2020 ◽  
Vol 9 (4) ◽  
pp. 727-733
Keyword(s):  
Signal Processing ◽  
Extraction Method ◽  
Statistical Approach ◽  
Audio Signal ◽  
Noise Removal ◽  
Adaptive Signal Processing ◽  
Audio Signal Processing ◽  
Time Frequency ◽  
Signal Processing Methods ◽  
Adaptive Signal

The adaptive signal processing methods are used in several applications like channel estimation, Noise removal and extraction of signals also. The methods vary on time, frequency and statistical approach. In this paper, the source speech signals are separated using different methods like FastICA,PCA and kICA. Comparison of original signal and estimated signals are evaluated for different methods. The implementation was done in MATLAB. The spectrogram, Negentropy and Kurtosis waveforms are plotted for different methods.

scholarly journals Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3725
Author(s):  
Paweł Zimroz ◽  
Paweł Trybała ◽  
Adam Wróblewski ◽  
Mateusz Góralczyk ◽  
Jarosław Szrek ◽  
...  
Keyword(s):  
Signal Processing ◽  
Acoustic Signal ◽  
Processing Technique ◽  
Underground Mine ◽  
Search And Rescue ◽  
Reference Spectrum ◽  
Signal Processing Technique ◽  
Time Frequency ◽  
Communication Device ◽  
Frequency Representation

The possibility of the application of an unmanned aerial vehicle (UAV) in search and rescue activities in a deep underground mine has been investigated. In the presented case study, a UAV is searching for a lost or injured human who is able to call for help but is not able to move or use any communication device. A UAV capturing acoustic data while flying through underground corridors is used. The acoustic signal is very noisy since during the flight the UAV contributes high-energetic emission. The main goal of the paper is to present an automatic signal processing procedure for detection of a specific sound (supposed to contain voice activity) in presence of heavy, time-varying noise from UAV. The proposed acoustic signal processing technique is based on time-frequency representation and Euclidean distance measurement between reference spectrum (UAV noise only) and captured data. As both the UAV and “injured” person were equipped with synchronized microphones during the experiment, validation has been performed. Two experiments carried out in lab conditions, as well as one in an underground mine, provided very satisfactory results.

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