Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Frey's Scenario F simulation mentioned in account of the Democratic Party's tribulations

U-M Poverty Solutions funds nine projects

Dynarski says NY's Excelsior Scholarship Program could crowd out low-income and minority students

More News

Highlights

Workshops on EndNote, NIH reporting, and publication altmetrics, Jan 26 through Feb 7, ISR

2017 PAA Annual Meeting, April 27-29, Chicago

NIH funding opportunity: Etiology of Health Disparities and Health Advantages among Immigrant Populations (R01 and R21), open Jan 2017

Russell Sage 2017 Summer Institute in Computational Social Science, June 18-July 1. Application deadline Feb 17.

More Highlights

Next Brown Bag

Mon, Jan 23, 2017 at noon:
Decline of cash assistance and child well-being, Luke Shaefer

Embedding Damage Detection Algorithms in a Wireless Sensing Unit for Operational Power Efficiency

Archived Abstract of Former PSC Researcher

Lynch, J.P., A. Sundararajan, K.H. Law, A.S. Kiremidjian, and E. Carryer. 2004. "Embedding Damage Detection Algorithms in a Wireless Sensing Unit for Operational Power Efficiency." Smart Materials and Structures, 13(4): 800-810.

A low-cost wireless sensing unit is designed and fabricated for deployment as the building block of wireless structural health monitoring systems. Finite operational lives of portable power supplies, such as batteries, necessitate optimization of the wireless sensing unit design to attain overall energy efficiency. This is in conflict with the need for wireless radios that have far-reaching communication ranges that require significant amounts of power. As a result, a penalty is incurred by transmitting raw time-history records using scarce system resources such as battery power and bandwidth. Alternatively, a computational core that can accommodate local processing of data is designed and implemented in the wireless sensing unit. The role of the computational core is to perform interrogation tasks of collected raw time-history data and to transmit via the wireless channel the analysis results rather than time-history records. To illustrate the ability of the computational core to execute such embedded engineering analyses, a two-tiered time-series damage detection algorithm is implemented as an example. Using a lumped-mass laboratory structure, local execution of the embedded damage detection method is shown to save energy by avoiding utilization of the wireless channel to transmit raw time-history data.

DOI:10.1088/0964-1726/13/4/018 (Full Text)

Browse | Search : All Pubs | Next