TY - JOUR
T1 - Analytic signal space partitioning and symbolic dynamic filtering for degradation monitoring of electric motors
AU - Chakraborty, Subhadeep
AU - Ray, Asok
AU - Subbu, Aparna
AU - Keller, Eric
N1 - Funding Information:
This work has been supported in part by NASA under Cooperative Agreement No. NNC04GA49G and Contract No. NNC07QA08P.
PY - 2010/11
Y1 - 2010/11
N2 - This study presents an application of the recently reported theories of analytic signal space partitioning (ASSP) and symbolic dynamic filtering (SDF) to address degradation monitoring in permanent magnet synchronous motors (PMSM). An (experimentally validated) mathematical model of generic PMSM is chosen to monitor degradation/fault events on a simulation test bed; and the estimated parameter of health condition is observed to vary smoothly and monotonically with degradation in magnetization of the PMSM.
AB - This study presents an application of the recently reported theories of analytic signal space partitioning (ASSP) and symbolic dynamic filtering (SDF) to address degradation monitoring in permanent magnet synchronous motors (PMSM). An (experimentally validated) mathematical model of generic PMSM is chosen to monitor degradation/fault events on a simulation test bed; and the estimated parameter of health condition is observed to vary smoothly and monotonically with degradation in magnetization of the PMSM.
UR - http://www.scopus.com/inward/record.url?scp=78649320977&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649320977&partnerID=8YFLogxK
U2 - 10.1007/s11760-009-0133-4
DO - 10.1007/s11760-009-0133-4
M3 - Article
AN - SCOPUS:78649320977
SN - 1863-1703
VL - 4
SP - 399
EP - 403
JO - Signal, Image and Video Processing
JF - Signal, Image and Video Processing
IS - 4
ER -