Analysing multi-point multi-frequency machine vibrations using optical sampling

• Main Authors: ROY, Dibyendu, GHOSE, Avik, CHAKRAVARTY, Tapas, MUKHERJEE, Sushovan, PAL, Arpan, MISRA, Archan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Chinese Remainder Theorem; Frequency Estimation; Optical Sampling; Unobtrusive Multi-frequency Vibration Measurement; Artificial Intelligence and Robotics; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4368; https://ink.library.smu.edu.sg/context/sis_research/article/5371/viewcontent/p55_Roy__1_.pdf
• Institution: Singapore Management University

Vibration analysis is a key troubleshooting methodology for assessing the health of factory machinery. We propose an unobtrusive framework for at-a-distance visual estimation of such (possibly high frequency) vibrations, using a low fps (frames-per-second) camera that may, for example, be mounted on a worker's smart-glass. Our key innovation is to use an external stroboscopic light source (that, for example, may be provided by an assistive robot), to illuminate the machine with multiple mutually-prime strobing frequencies, and use the resulting aliased signals to efficiently estimate the different vibration frequencies via an enhanced version of the Chinese Remainder Theorem. Experimental results show that our technique estimates multiple such frequencies faster, and compares favourably to an equipment-mounted accelerometer alternative, with frequency estimation errors below 0.5% for vibrations occurring up to 500 Hz.