Abstract
Summary: A new inspection technique for complex mechanical structures is proposed in this paper, where a fuzzy inference system carries out structural inspection. The inputs to the fuzzy inference system are the elements of a fault signature, an array of numbers prepared with use of below 5 kHz resonance frequencies of faultless and a number of faulty specimens. Advantage: Below 5 kHz resonance frequencies are easier and less expensive to obtain compared to higher frequency ones. Limit: Due to high expenses of experiments, reliable finite element models were alternatively used to obtain resonance frequencies of the faulty specimens. Results: The developed fuzzy inference system in this research accurately located an under-surface fault in an engine cylinder block.
Highlights
Structural inspection [1], structural damage detection [2] or structural health monitoring [3] are roughly equivalent terms used for fault diagnosis of mechanical structures
The fuzzy inference system (FIS) has been developed using below 5 kHz resonance frequencies
This paper presents a new method to structural inspection of complex mechanical parts, based on development of a fuzzy inference system
Summary
Structural inspection [1], structural damage detection [2] or structural health monitoring [3] are roughly equivalent terms used for fault diagnosis of mechanical structures. Two approaches may be used in structural inspection or, in a wider view, fault diagnosis: (i) local or signal-based approach, and (ii) global or model-based approach. A metal part with no internal void space permits an ultrasonic wave to pass at a certain speed. Due to this evident response of the faultless system, only the response/information (in this example, the ultrasonic wave speed) of the faulty system is employed in fault diagnosis [7]. Such methods are called ‘signal-based’ methods [6, 8]. All signal-based techniques of structural inspection should be used in the locality of the
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