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This paper addresses the use of two algorithms based on symbolic dynamics analysis of vibration signal for fault diagnosis in gearboxes. The symbolic dynamics algorithm (SDA) works by subdividing the phase space described by the Poincaré plot into several angular regions; then, a symbol is assigned to each region. The probability distributions generated by the set of symbols are considered as features...
The number of extracted features for fault diagnosis in rotating machinery can grow considerably due to the large amount of available data collected from different monitored signals. Usually, feature selection or reduction are conducted through several techniques proposing a unique set of representative features for all available classes; nevertheless, in feature selection, it has been recognized...
Rotating machinery plays an important role in industries for motion transmission in machines; the breakdowns of gearboxes are mostly produced by gear and bearings failures. Thus, some strategies are sought to avoid unscheduled stops, or catastrophic damages, in order to reduce maintenance costs and increase reliability. This paper describes a methodological framework to detect eleven rotating machinery...
Fault detection and diagnostic software (FDDS) supports technicians and engineers to deal with operational matters, in major cases related to complicated systems and advanced technology that require higher performance expectation. Information and communication technologies play an importantrole for implementing efficient maintenance software, therefore, the development of FDDS is posed as an industrial...
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