Chapter
Jul 11, 2012
Monitoring System for Operational Efficiency and Environmental Performance of Construction Operations Using Vibration Signal Analysis
Authors: Changbum R. Ahn [email protected], SangHyun Lee [email protected], and Feniosky Peña-Mora [email protected]Author Affiliations
Publication: Construction Research Congress 2012: Construction Challenges in a Flat World
Abstract
Construction operations are highly energy-intensive and generate a significant amount of air pollutant emissions, including carbon emissions. Controlling the operational efficiency of equipment is key to managing and improving the environmental performance of construction operations. However, efforts to improve environmental performance are limited due to the industry's lack of a practical method for monitoring the operational efficiency of construction equipment and related environmental performance. Currently available methods are costly or have compatibility issues. In this context, this paper aims to develop a monitoring system that ensures economic feasibility and compatibility, and that uses vibration signal analysis. First, the paper discusses the relationship between operational efficiency and environmental performance. Then, the paper presents a method for using vibration signal analysis to monitor the operational status of equipment. Finally, a case study of an excavator demonstrates the presented method's feasibility in a real-world operation.
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© 2012 American Society of Civil Engineers.
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Published online: Jul 11, 2012
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Ph.D. Candidate, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801. E-mail: [email protected]
Assistant Professor, University of Michigan, 2350 Hayward St., Suite 2340 G.G. Brown Building, Ann Arbor, MI 48109. E-mail: [email protected]
Dean of The Fu Foundation School of Engineering and Applied Science and Morris A. and Alma Schapiro Professor of Civil Engineering and Engineering Mechanics, Earth and Environmental Engineering, and Computer Science, Columbia University, 500 W. 120th St., Mudd 510, New York, NY 10027. E-mail: [email protected]
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