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research-article

Computationally-Efficient Optimal Video-Comparison for Machine Monitoring and Process Control

[+] Author and Article Information
Brian W. Anthony

Member of ASME, Laboratory for Manufacturing and Productivity, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
banthony@mit.edu

Fitriani Chua

Graduate Researcher, Center for Design Optimization, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
fitriani@mit.edu

1Corresponding author.

ASME doi:10.1115/1.4037234 History: Received January 31, 2017; Revised June 16, 2017

Abstract

Real-time algorithms are needed to compare and analyze digital videos of machines and processes. Techniques for the efficient dimensionality-reduction of, extraction of actionable-information from, and comparison of, videos will enable new opportunities in system monitoring and control. We define the Video Alignment Path (VAP) as the sequence of local time-and-space transformations required to optimally register two video-clips. We develop an algorithm, Dynamic Time and Space Warping (DTSW), which calculates the VAP. Measures of video-similarity, and therefore system-similarity, are estimated based on properties of the VAP. These measures of similarity are then monitored over time and used for decision making and process control. We describe the performance, structure, and computational complexity of a DTSW implementation which is parallelizable and which can achieve the processing rates necessary for many video-based industrial monitoring applications. We describe two case studies of unsupervised monitoring for mechanical wear and for fault detection. Results suggest opportunities for boarder applications of video-based instrumentation for real-time feedback control, wear and defect detection, or statistical process-control.

Copyright (c) 2017 by ASME
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