Mones, Zainab, Feng, G., Ogbulaor, U.E., Wang, T., Gu, Fengshou and Ball, Andrew (2016) Performance evaluation of wireless MEMS accelerometer for reciprocating compressor condition monitoring. In: Power Engineering: Proceedings of the International Conference on Power Transmissions. ICPT (2016). Taylor & Francis, Chongqing, P.R. China, pp. 893-900. ISBN 978-1-138-03267-5
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Abstract
With recent development in wireless communication and Micro Electro Mechanical Systems (MEMS) technology, it becomes easier to monitor rotating machinery conditions by mounting compact wireless MEMS accelerometers directly on the rotor. This has the potential to provide more accurate dynamic characteristics of the rotating machine and hence achieving high monitoring performance. In this paper, a tiny MEMS accelerometer together with a battery powered microcontroller is mounted on the flywheel to acquire the on-rotor accelerations of a two-stage reciprocating compressor. The measured acceleration data is streamed to a host computer wirelessly via Bluetooth Low Energy (BLE) module. The true tangential acceleration is reconstructed by combining two orthogonal outputs of the sensor, which contain gravitational accelerations. To evaluate the performance of the wireless sensor, three different fault conditions including intercooler leakage, second stage discharge valve leakage and asymmetric stator winding of the motor driver are simulated individually on the compressor test rig. To confirm the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the Instantaneous Angular Speed (IAS) signal for comparison with signals from the wireless sensor. The experimental results show that the running status of the compressor can be remotely monitored, allowing different leakages and motor faults to be diagnosed based on the tangential acceleration reconstructed from a wireless on-rotor MEMS accelerometer.
Item Type: | Book Chapter |
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Subjects: | T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery |
Schools: | School of Computing and Engineering |
Related URLs: | |
Depositing User: | Sara Taylor |
Date Deposited: | 12 Jan 2017 11:04 |
Last Modified: | 28 Aug 2021 16:22 |
URI: | http://eprints.hud.ac.uk/id/eprint/30918 |
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