Desenvolvimento de um sistema de manutenção inteligente embarcado

AUTOR(ES)

Luiz Fernando Gonçalves

FONTE

IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia

DATA DE PUBLICAÇÃO

2011

RESUMO

The technological evolution of sensors, electronics, and embedded systems has improved the performance, reliability and robustness of systems as well the maintenance activities, especially the proactive maintenance. These technological advances have provided a new view about the existing maintenance practices. The expansion of signal processing and artificial intelligence has provided new approaches in industrial control systems leading to the proposal of new reliability and availability models for equipments and systems. Moreover, it has increased the precision in failure pattern recognition, has extended the assessment and diagnosis of damages in equipments and systems, and has added intelligence to existing maintenance systems. Several techniques for signal processing (such as Fourier transform), artificial intelligence (artificial neural networks, for example) and adaptive filtering (adaptive filters, as an example) are already used successfully to detect and prevent failures in several kinds of equipments. The maintenance systems that use, for example, the techniques for signal processing and artificial intelligence together are known as intelligent maintenance systems. It is possible to control the physical conditions, make decisions, perform maintenance activities and do accurate diagnosis of failures using those systems. This work presents the implementation of an embedded intelligent maintenance system using wavelet packet analysis and self organizing maps or adaptive filters for detection, classification, and prediction of failures in electrical actuators. The main idea is to determine which of these tools, self-organizing maps or adaptive filters, is the most suitable for the implementation in embedded systems. It is expected that with the implementation of this maintenance system, failures in actuators are avoided, and that a greater reuse of parts is achieved.

ASSUNTO(S)

manutenção industrial adaptive filtering artificial intelligence embedded systems fpga maintenance sistemas embarcados inteligência artificial signal processing processamento de sinais

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