Performance Verification of a Flexible Vibration Monitoring System

Bointon, Patrick; Todhunter, Luke; Clare, Adam; Leach, Richard

Abstract

The performance of measurement or manufacturing systems in high-precision applications is dependent upon the dynamics of the system, as vibration can be a significant contributor to the measurement uncertainty and process variability. Technologies making use of accelerometers and laser vibrometers are available to rapidly measure and process structural dynamic data but the software infrastructure is yet to be available in an open source or standardised format to allow rapid inter-platform use. In this paper, we present a novel condition monitoring system, which uses commercially available accelerometers in combination with a control-monitoring infrastructure to allow for the appraisal of the performance of a measurement or manufacturing system. A field-programmable gate array (FPGA)-based control system is implemented for high-speed data acquisition and signal processing of six triaxial accelerometers, with a frequency range of 1 Hz to 6000 Hz, a sensitivity of 102.5 mV/ms−2 and a maximum sample rate of 12,800 samples per second per channel. The system includes two methods of operation: real-time performance monitoring and detailed measurement/manufacturing verification. A lathe condition monitoring investigation is undertaken to demonstrate the utility of this system and acquire typical machining performance parameters in order to monitor the “health” of the system.

Citation

Bointon, P., Todhunter, L., Clare, A., & Leach, R. (2020). Performance Verification of a Flexible Vibration Monitoring System. Machines, 8(1), 3. https://doi.org/10.3390/machines8010003

• Journal Article Type: Article
• Acceptance Date: Dec 28, 2019
• Online Publication Date: Jan 3, 2020
• Publication Date: Jan 3, 2020
• Deposit Date: Jan 9, 2020
• Publicly Available Date: Jan 9, 2020
• Journal: Machines
• Electronic ISSN: 2075-1702
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 1
• Pages: 3
• DOI: https://doi.org/10.3390/machines8010003
• Public URL: https://nottingham-repository.worktribe.com/output/3696250
• Publisher URL: https://www.mdpi.com/2075-1702/8/1/3