Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

6-2018

Abstract

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.

Keywords

Chinese Remainder Theorem, Frequency Estimation, Optical Sampling, Unobtrusive Multi-frequency Vibration Measurement

Discipline

Artificial Intelligence and Robotics | Software Engineering

Research Areas

Data Science and Engineering

Publication

IoPARTS '18: Proceedings of the 2018 International Workshop on Internet of People, Assistive Robots and ThingS: June 10, Munich, Germany

First Page

55

Last Page

59

ISBN

9781450358439

Identifier

10.1145/3215525.3215529

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3215525.3215529

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