LAUSR

According to industry statistics, bearings are the components of low-voltage motors that fail most often. At the same time, the diagnostics of rollingelement bearings constitute a well-established component of the rotating machinery condition-monitoring domain. In many cases, however, the cost of installing a high-end, accelerometer-based bearing condition-monitoring system, which is the most common approach in the industry, may be difficult to justify for noncritical machinery due to the amount of time needed to see a return on this investment. This article examines the potential benefits of using modern, off-the-shelf mobile phones for recording acoustic signals originating from elements of rotating machines to monitor the conditions of rolling-element bearings. The main difficulty in using embedded mobile phone microphones for rotating machinery diagnostic purposes is that the frequency response of the mobile phone's microphone is very poor, i.e., below 200 Hz. The results presented in this article indicate that, with an appropriate signal processing approach, it is possible to detect the presence of faults in the bearings. More specifically, mobile-phone-based sound measurements may contain sufficient information that can not only distinguish between healthy and faulty cases but also determine the specific bearing fault type.