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Motor monitoring system for a continuous miner

Public Domain
File Language:
English


Details

  • Personal Author:
  • Corporate Authors:
    United States. Bureau of Mines
  • Description:
    The U.S. Bureau of Mines has investigated the early detection of insulation failure in squirrel cage induction motors for the past 4 years. Research was done using a sophisticated empirical data-modeling technique based on values calculated from a motor's voltage and current phasors. This technique produces two polynomial equations that calculate the insulation leakage current and power. These models were implemented in a prototype system that monitors six motors on a continuous miner for insulation leakage. These insulation leakage values are used to anticipate insulation failure. The system consists of a motor-data-system for each motor on the machine and a control computer located away from the miner. Each motor-data-system consists of an analog interface to the motor's voltages and currents, a single-board computer that reads digitized data and calculates voltage and current phasors, and a bus node that interfaces the single-board computer with the rest of the system by way of a serial bus system. Using this bus system, the control computer requests and receives phasor data from the motor-data-systems. From these data the control computer calculates and displays two deterioration values for each motor, for leakage current and power, using Bureau-developed models. These values are stored in a data base from which the user can display graphs of each motor's deterioration values over time.
  • Subjects:
  • Series:
    Mining Publications
  • Subseries:
    Information Circular
  • Document Type:
    Text
  • Genre:
    Report
  • CIO:
    National Institute for Occupational Safety and Health (NIOSH)
  • Pages in Document:
    12 numbered pages
  • NIOSHTIC Number:
    nn:10011188
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:56e0327a0b87a69fceb0daa4c04137df7015e12a3f2d1966259a90dc521492d5c01a3cb2321cdaa8486dbc8ed15b78b8d5ec1eb0492aeb2687e5081cc5c07057
  • Download URL:
  • File Type:
    Filetype[PDF - 2.32 MB ]
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