In this paper we present a system for fault detection and isolation of electrical motors for vacuum cleaners, which serves for on-line quality assessment at the end of the production line. The main focus of the paper is on detection of incipient mechanical faults by means of sound analysis. A detailed description of the procedures for detection and isolation of faults with mechanical origin is given. One of the contributions concerns innovative implementation of the feature extraction algorithm in a way that spectral procedures used in system analysis are substituted by much simpler and computationally more effective algorithms. Herewith the system is able to accurately isolate three different types of mechanical faults. Additional contribution regards diagnostic system integration which generates highest product end quality and traceability. In order to fully utilize a huge amount of diagnostic data, possibilities for the upgrade of the present diagnostic system with advanced production line supervision support are indicated.
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