Android app for intelligent CBM

Smartphone applications have changed the traditional way of using cellphones. They are not only used for calling and messaging, but also for specialized and multiple engineering applications like face recognition, navigation, driving style recognition, etc. In this paper we present a scalable android application which enables smartphones to diagnose faults in rotating machines. With this ability of fault detection, it can be used for Condition Based Monitoring (CBM), which is a popular maintenance strategy used in industry. The smartphone performs fault detection by analyzing acoustic signatures generated by a rotating machine in running condition. The acoustic signature is recorded and analyzed by the inbuilt microphone and processor respectively, thus enabling the smartphone to be a complete fault detection and recognition system. The advantage of this is that we get an industrial fault detection system which is portable, economically viable and easily deployable. The performance of the system has been assessed by training and testing on an industrial air compressor acoustic data for three different machine conditions. Observed fault recognition accuracies were approximately 93%.

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