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We describe how to detect and diagnose the causes of faults for stochastic processes.
Although basic statistical analysis provides a general knowledge of the primary causes of faults; nevertheless, it falls short of describing nuanced conditions that lead to a fault.
As one of the most important approaches for analyzing the mechanism of fault pervasion, fault root cause tracing is a powerful and useful tool for detecting the fundamental causes of faults so as to prevent any further propagation and amplification.
Additionally, the concerns of chip designers include not only the natural causes of faults but also the misbehavior of chips due to "planned" attacks, as, for example, in critical security applications.
The results obtained from simulated and practical experiments prove that exact wavelet analysis not only minimizes the undesirable effect of overlapping, but also helps operators to detect faults and distinguish the causes of faults.
Reasoning on this knowledge base by virtue of JESS (Java Expert Shell System) rule engine, maintenance personnel can find the causes of faults of a wind turbine quickly, and choose the proper solutions.
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However, induction motors manufacturers ensure that the machines present asymmetry as small as possible because it could be the main cause of faults [7].
Condition monitoring is a type of maintenance inspection where an operational asset is monitored and the data obtained is analyzed to detect signs of degradation, diagnose cause of faults, and predict for how long it can be safely or economically run.
At a high level, the network serves for localization of the process faults, and at a low level, a set of networks identifies the causes of these faults.
Causes of the faults are presumed to be deterioration of various.
To gain the competitive advantage, manufacturing companies must be able to analyze and predict product quality during the product design phase and identify root causes of all faults for productivity improvement during ramp-up time and production time.
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