Wavelet Analysis and Neural Networks for Bearing Fault Diagnosis
نویسنده
چکیده
Today, most maintenance actions are carried out by either corrective (run to failure) or preventive (scheduled or predetermined) strategy. In Corrective Maintenance (CM) the components are maintained after obvious faults or actual breakdown has occurred. With this maintenance strategy the associated costs are usually high due to the production losses, fault occurrence damages, restoring equipment until is being used at failure condition, and the safety/health hazards presented by the fault. However, the Preventive Maintenance (PM) approach has been developed to overcome the CM deficiencies. Traditionally, PM is a time driven process which is performed at regular time intervals, commonly termed the maintenance cycle, regardless of the components actual condition, in order to prevent component or systems breakdown. For example, changing the car engine oil at every 5000 KMs traveled distance, where no concern as to the actual condition and performance capability of the replaced oil.
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