Condition monitoring of critical industrial assets using high performing low-cost MEMS accelerometers

Abstract

The high investment cost, which is in majority introduced by the sensor costs, is one of the barriers for adopting Predictive Maintenance/Condition-Based Maintenance strategy in the industry. To lower this barrier, the use of cost-effective sensors for such an application is, therefore, a necessity. This paper presents experiences in setting-up two different remote vibration monitoring systems using low-cost MEMS accelerometers available on the market in two different industrial settings. Some technical challenges and the state-of-the-art algorithms used to analyze the measured raw vibration signals are presented. The installed vibration monitoring systems have successfully detected faults on two different critical assets, namely an induction motor and an expander machine.