NDLI: Pattern Matching of In-Vehicle Acceleration Time Series Data

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Pramod, K. Vemulapalli Gregory, S. Ledva Sean, N. Brennan Karl, M. Reichard
Copyright Year	2012
Abstract	This paper presents a novel approach to find patterns in vehicle x-y-z acceleration data for use in prognostics and diagnostics. In this problem, vehicles are assumed to travel on the same routes and often times as a part of convoys but their GPS and other position information has been removed for privacy reasons. The goal of the pattern matching scheme is to identify the route or convoy associations within vehicles by using the acceleration data collected onboard these vehicles. A crucial step in solving this problem is to choose the right feature vector, as raw matching of acceleration signals is inappropriate due to different velocities, driving behaviors, vehicle loading, etc. In this paper, we demonstrate the feasibility of using ‘Multi-Scale Extrema Features’ for this application. The paper also addresses implementation details to enhance performance for in-vehicle acceleration data, corrupted by different sources of noise. A novel ‘Multi-Scale Encoding’ method is also proposed for the above feature vector and it leads to a significant improvement in the performance over traditional pattern matching methods. While the main focus of the paper is towards identifying feature vectors that effectively describe in-vehicle acceleration data, the feature vector could potentially be used with acceleration data obtained from other applications.
Sponsorship	Dynamic Systems and Control Division
Starting Page	761
Ending Page	770
Page Count	10
File Format	PDF
ISBN	9780791845301
DOI	10.1115/DSCC2012-MOVIC2012-8758
Volume Number	Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems
Conference Proceedings	ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
Language	English
Publisher Date	2012-10-17
Publisher Place	Fort Lauderdale, Florida, USA
Access Restriction	Subscribed
Subject Keyword	Noise (sound) Encryption Signals Time series Vehicles
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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