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Experiments are conducted using Spectra Quest machine fault simulator with different prefabricated faulted bearings.
The paper proposes a new methodology of machine fault detection for industrial gas turbine (IGT) systems.
Vibration-based analysis is an important technique in machine fault diagnosis.
Wavelet transform has been widely used for vibration-based machine fault diagnosis.
Possible internal machine fault conditions can be detected and remedial action can be undertaken.
The diagnosis scheme is finally validated with experiments performed with the help of a machine fault simulator (MFS) system.
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Based on the available data on the shop floor, the potential fault/error patterns, referring to machining errors, machine faults and maintenance states, are mined for unsuitable scheduling arrangements before machining as well as upcoming errors during machining.
normal behaviour, transient operation, and characteristics of emerging machine faults.
This pseudo-phase portrait is then used to extract qualitative features of machine faults.
Online induction machine faults diagnosis is a concern to guarantee the overall production process efficiency.
These merits are presented in this paper and applied to diagnose three types of machine faults.
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