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Using vibration analysis, the condition of a machine can be periodically monitored.
Determining the condition of the machine insulation systems is not a trivial task for non-experts.
Using vibration analysis, the condition of a machine can be constantly monitored.
Artificial neural networks allow for a quick and effective association of the symptoms with the condition of the machine.
As the stress condition of the machine changes with the production rate, the failure rate of the machine is assumed to be dependent on the production rate.
Creating a program in the Matlab language to calculate the error model, the position stance error of the probe is obtained under the condition of determinate machine error.
This bundles the real-time readings of the current, maximum and minimum temperature for comparison in order to ascertain the current condition of the machine.
Look at the general condition of the machine.
This type of active balancer maintains the balanced condition of machine by permanent magnets rather than clutch and external energy.
Because of high connection, the health condition of a single machine has greater influence on the factory operation than ever before.
This paper describes the development of an expert system to assist rotating machine maintenance personnel in assessing the insulation condition of their machines.
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