TY - JOUR
T1 - Risk assessment of low voltage motors based on PD measurements and insulation diagnostics
AU - Hassan, Waqar
AU - Mahmood, Farhan
AU - Hussain, Ghulam Amjad
AU - Amin, Salman
N1 - Hassan, W., Mahmood, F., Hussain, G. A., & Amin, S. (2021). Risk assessment of low voltage motors based on PD measurements and insulation diagnostics. Measurement, 176. https://doi.org/10.1016/j.measurement.2021.109151
PY - 2021/5
Y1 - 2021/5
N2 - Partial discharge (PD) diagnostics is a reliable technique for the health assessment of electrical motors. This paper presents a unique methodology for the failure risk assessment of the low voltage motors containing various insulation defects based on PD measurements. The severity of PD in the motors increases with the time during their operation due to electrical and environmental stresses. In this work, several artificial PD defects have been created in low voltage induction motors under laboratory conditions. Accordingly, the characteristic parameters of PD measured in the laboratory for the artificial defects are evaluated to identify their impact on the resulting degradation of the insulation. Furthermore, the classification of these defects has been carried out based on cumulative energy function using K-mean clustering algorithm followed by the estimation of insulation lifetime. In this regard, Weibull distribution has been employed to quantify the probability of failure and risk evaluation corresponding to the severity of PD defects. The proposed risk assessment framework may be utilized to support asset managers in scheduling the regular maintenance activities and assist them in decision making about the type of actions required to eliminate the latent threat.
AB - Partial discharge (PD) diagnostics is a reliable technique for the health assessment of electrical motors. This paper presents a unique methodology for the failure risk assessment of the low voltage motors containing various insulation defects based on PD measurements. The severity of PD in the motors increases with the time during their operation due to electrical and environmental stresses. In this work, several artificial PD defects have been created in low voltage induction motors under laboratory conditions. Accordingly, the characteristic parameters of PD measured in the laboratory for the artificial defects are evaluated to identify their impact on the resulting degradation of the insulation. Furthermore, the classification of these defects has been carried out based on cumulative energy function using K-mean clustering algorithm followed by the estimation of insulation lifetime. In this regard, Weibull distribution has been employed to quantify the probability of failure and risk evaluation corresponding to the severity of PD defects. The proposed risk assessment framework may be utilized to support asset managers in scheduling the regular maintenance activities and assist them in decision making about the type of actions required to eliminate the latent threat.
KW - Cumulative energy function
KW - K-mean clustering
KW - Motor insulation
KW - Partial discharge measurements
KW - Risk assessment
KW - Weibull distribution
UR - http://www.scopus.com/inward/record.url?scp=85101310960&partnerID=8YFLogxK
U2 - 10.1016/j.measurement.2021.109151
DO - 10.1016/j.measurement.2021.109151
M3 - Article
SN - 0263-2241
VL - 176
JO - Measurement: Journal of the International Measurement Confederation
JF - Measurement: Journal of the International Measurement Confederation
M1 - 109151
ER -