TY - GEN
T1 - On-line system for fault detection in induction machines based on wavelet convolution
AU - Cusidó, J.
AU - Rosero, J. A.
AU - Cusidó, M.
AU - Garcia, A.
AU - Ortega, J. A.
AU - Romeral, L.
AU - Author, Q.
PY - 2007
Y1 - 2007
N2 - Motor Current Signature Analysis has been successfully used in induction machines for fault diagnosis. The method, however, does not always achieve good results when the load torque is not constant. For proper results, temporal analysis on certain frequency harmonics is needed. This paper proposes an automatic system for fault analysis based on wavelet functions, which allows on-line fault detection in the time domain, achieving good experimental results both on stationary and non-stationary states.
AB - Motor Current Signature Analysis has been successfully used in induction machines for fault diagnosis. The method, however, does not always achieve good results when the load torque is not constant. For proper results, temporal analysis on certain frequency harmonics is needed. This paper proposes an automatic system for fault analysis based on wavelet functions, which allows on-line fault detection in the time domain, achieving good experimental results both on stationary and non-stationary states.
UR - https://www.scopus.com/pages/publications/48349112339
U2 - 10.1109/PESC.2007.4342112
DO - 10.1109/PESC.2007.4342112
M3 - Conference contribution
AN - SCOPUS:48349112339
SN - 1424406552
SN - 9781424406555
T3 - PESC Record - IEEE Annual Power Electronics Specialists Conference
SP - 927
EP - 932
BT - PESC 07 - IEEE 38th Annual Power Electronics Specialists Conference
T2 - PESC 07 - IEEE 38th Annual Power Electronics Specialists Conference
Y2 - 17 June 2007 through 21 June 2007
ER -