Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Session Chair: Dr. Anna Gegenava, National Electric Coil, United States of America
Location:Heron
Session Topics:
Partial Discharge On-Line and Off-Line testing (TD), Testing Technologies (TD), Diagnostics, Monitoring, and Condition Assessment (TD), Numerical Modeling (TD)
Presentations
9:00am - 9:30am
Polarization and depolarization currents experience return on hydroelectric generators
S. Bernier1, M. Lévesque1, H. Provencher1, É. David2, A. Bertrand3
1Institut de recherche d'Hydro-Québec; 2École de Technologie Supérieure; 3Hydro-Québec
Polarization and Depolarization Current measurements (PDC) are well-known in the industry. Hydro-Québec has been using PDC measurements as a diagnostic tool for more than 25 years. Since 2012, systematic PDC measurements are conducted every 6 years on the stator windings of all the hydrogenerator fleets. When the tool was first implemented, thresholds were defined to convert insulation resistance values into a condition health index. These limits were decided based on preliminary results obtained from a few hydrogenerators and laboratory measurements on accelerated-aged samples. However, with more than 500 PDC measurement results, the database can now help refine the limits for each type of insulation system (asphalt, epoxy and polyester). The purpose of this paper is to present the evolution of the insulation resistance value as global aging occurs and to observe the trending of insulation resistance over time. The influence of factors such as humidity, and the nature of the stress grading coating are also presented to describe how the limits can be managed for diagnostic purpose with statistical uncertainty.
9:30am - 10:00am
A Novel Approach to Detecting Electric Machinery Insulation Defects with Electrical and Current Signature Analysis
H. W Penrose
MotorDoc LLC, United States of America
In this paper we will discuss the use of electrical and current signature analysis on electric machinery for the detection of insulation defects. The project involved the practical study of electric machinery field testing and evaluation at repair facilities. In this paper we will identify the use of two different types of electrical signature and motor current signature analysis devices and how insulation system direct and inferred defects are detected. The use of expert and machine learning/AI for this type of analysis will be distinguished. Direct insulation system defects include electrical insulation system breakdown and inferred defects involves the identification of conditions that lead to breakdown. The study and results also includes results from both across-the-line clean, high harmonic, and inverter environments.
