ABSTRACT
Instantaneous Angular Speed (IAS) is a widely used technique for monitoring the dynamic condition of rotating machinery. Many studies have evaluated the condition of rotating machines using IAS measurement based on shaft encoder. In (Renaudin 2010), a magnetic encoder was used to measure the IAS of an automotive gearbox in different operating conditions. The results proved that different faults, like pitting in bearing, causing small angular speed fluctuations are measurable with magnetic encoders, meaning abnormal conditions can be detected. Roy et al investigated the behavior of IAS signal for different gearboxes under various speed and load conditions. They concluded that by applying Time Synchronous Averaging (TSA)
attention. (Albarbar 2008) studied the usage of MEMS accelerometers in condition monitoring and investigated the performance of three different MEMS accelerometers. From their investigation, it is concluded that MEMS sensors could be used instead of standard sensors especially for wireless implementation. (Arebi 2010) developed a wireless MEMS accelerometer that was attached directly on a rotating shaft and the results demonstrated that different degrees of misalignments can be successfully monitored using MEMS accelerometer. Furthermore, (Arebi 2011) studied and compared response from data collected via a MEMS accelerometer and shaft encoder under different degrees of shaft misalignment. Findings from their study showed that the wireless MEMS accelerometer outperforms the shaft encoder in detecting small shaft misalignment. The authors previously mounted a three-axial MEMS data logger on the flywheel of a reciprocating compressor to record the on-rotor accelerations. By combining the acceleration from two axes, the gravitational acceleration was effectively removed and the tangential acceleration was reconstructed with good accuracy (Feng 2016). The focus of this study is to improve on the data collection method by bringing in the wireless data transmission technique which enables online condition monitoring. Furthermore, the reconstructed tangential acceleration signal is compared with the IAS signal from an optical encoder.
