Fault diagnosis of power systems
Article Abstract:
Knowledge-based systems designed for use with fault diagnosis of power systems provide effective fault diagnosis support of complex faults and unwanted operation of protective devices. A stable supply of electricity can be supplied with the fault diagnosis of power systems. Power system managers can increase the accuracy of fault diagnosis by using detailed relay and circuit breaker operation information and sensor information that reveals the status of the network. Accuracy is also improved when using higher-level inference that allows more detailed identification of fault locations, and when adding auto-learning functions and higher-speed inference. Enhancement of special expert systems and the use of a user interface that allows the diagnosis results to be visually displayed to the operator also provide improved accuracy.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1992
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Neural network model for control of muscle force based on the size principle of motor unit
Article Abstract:
A neural network model consisting of a single motor cortex output cell, (alpha) motoneurons, Renshaw cells, and muscle units is proposed. Linear relations between motor cortex output and force output observed in monkeys as well as firing rate versus force relations in human skeletal muscles are explained by computer simulations. It is suggested that Renshaw recurrent inhibition has the effect of linearizing the gain between motor cortex output and force output, and confirmed that the orderly recruitment of motor units is governed by unit size in accordance with a classical observation. (Reprinted by permission of the publisher)
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1990
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