Condition-Based Maintenance of Electrical Machines

Details

• Personal Author:
  Kohler, Jeffrey L. ; Sottile, Joseph ; Trutt, Frederick C.
• Description:
  Twenty-five years ago, the former U.S. Bureau of Mines funded a research project aimed at developing the enabling technology for incipient failure prediction in electric power system components as a means of reducing the injuries and fatalities that sometimes occur when equipment malfunctions. Over the ensuing years, interest in this has waxed and waned, but recently interest has been growing for both civilian and military applications. This paper addresses the level of turn-to-turn insulation deterioration that can be resolved using an on-line monitoring technique. The detection of turn-to-turn defects is especially important because they are believed to represent the beginning stage of most motor winding failures. [Description provided by NIOSH]
• Subjects:
  Electric Injuries Electricity Occupational Health Safety
• Keywords:
  Electrical-failure-prediction Electrical-hazards Electrical-safety Electrical-systems Monitoring-systems
• Series:
  Mining Publications
• ISBN:
  078035589X
• ISSN:
  0197-2618
• Publisher:
  Institute of Electrical & Electronics Engineers Industry Applications Society
• Document Type:
  Text
• Genre:
  Proceedings
• Place as Subject:
  Kentucky ; OSHA Region 3 ; OSHA Region 4 ; Pennsylvania
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  PRL - Pittsburgh Research Laboratory
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  205-211
• Volume:
  1
• NIOSHTIC Number:
  nn:20022726
• Citation:
  IAS '99: Conference Record of the 1999 IEEE Industry Applications Conference: Thirty forth IAS Annual Meeting, October 3-7, 1999, Phoenix, Arizona. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 1999 Oct; 3:205-211
• Federal Fiscal Year:
  2000
• Peer Reviewed:
  False
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:523ab1f4ae21bee48166b6d51122803f3b64332fc386cb2b51be26a0f76e35d68dff87eb7afc1a08b4e04e3b23fb9e0c2c33b05b01024170383f9492de386c82
• Download URL:
  https://stacks.cdc.gov/view/cdc/220570/cdc_220570_DS1.pdf
• File Type:
  [PDF - 433.47 KB ]