TY  - JOUR
T1  - Bearing Health Monitoring and Diagnosis Using ANC
Based Filtered Vibration Signal
AU - Sahoo, Sudarsan AU - Das, Jitendra Kumar 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 10
SP  - 3587
EP  - 3593
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.3587.3593
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.3587.3593
KW  - Condition monitoring
KW  -bearing fault
KW  -Adaptive Noise Cancellation (ANC)
KW  -LMS
KW  -EMD
KW  -wavelet transform
AB  - Continuous monitoring of the condition of a rotating machine is an important and required task for
engineers and researchers in industry. For any rotating machinery bearing is the core element. For that reason
health monitoring of bearing in a rotating machinery is very important. Vibration is one of the most widely used
signature used for the health monitoring of the bearings. In this research, the experiment is executed in two
stages. As the vibration signal acquired from the bearing set-up is in general noisy in nature, so in the first
phase of the experiment, the noise present in the vibration signal is removed to improve the SNR. This noise
filtering is done using the ANC (Adaptive Noise Cancellation) technique. Initially, three ANC techniques are
employed on the vibration signal acquired from the experimental set-up. The performance of the ANC
techniques are compared. From the comparison EMD is found better. So, EMD algorithm is used for the
implementation of the adaptive noise cancellation in the preprocessing of the vibration signal and then the
filtered signal is used in the next phase of the experiment for further analysis to detect the bearing defect. As
the time domain (static analysis) or frequency domain analysis alone may not provide the precise information
about the defect, so in the second phase of the experiment the static analysis and the frequency domain
analysis along with the time-frequency analysis is done on the filtered vibration signal to identify the defect
in the bearing.
ER  - 