SUMMARY

In most instances, rotating machines have a unique vibration signature that relates to their health status. Therefore, vibration analysis is a powerful tool for predictive maintenance. This is especially true for bearings that are a frequent cause of machine breakdown. Presently, bearing analysis of many machines results in significant cost and complexity due to a large amount of vibration data that must be analyzed. The purpose of this thesis is to develop a vibration analysis system that locally collects vibration data, analyzes it automatically and provides feedback as to the bearing condition.