Doctoral Dissertations

Autonomous triggering system and measurement protocols for smart bridge testing

Abstract

"This work describes the development and field trials of an autonomous triggering system for fast, economical bridge testing. Quantitative testing of bridges offers the ability to manage the structures better than with just qualitative inspections. The primary objectives of the proposed system are to acquire quantitative performance information from a load test while minimizing setup time at the bridge and closure time to traffic. Secondary objectives are minimizing the number of personnel required for the test and removing the need for personnel with specialized knowledge at the test site. The smart instrumentation consists of in-situ strain sensors, an embedded data acquisition module, and an infrared-based triggering system. Protocols are presented for static, quasi-static, and dynamic tests which integrate the embedded devices with the smart triggering. The triggering system detects the proper positioning of the load truck for measurements. The control unit in the truck serving as a load receives control and sensor data through a wireless link from in-situ instrumentation. Test parameters can be set through the control unit including the type of test (static, dynamic, or quasi-static), number of sensors, and several parameters for processing the data received. Only the driver of the load vehicle is required to operate the system. This procedure offers improvement in available information and economics. Timing and positional accuracy issues were investigated to insure that the protocols and triggering and positioning system were viable options for field instrumentation. In addition to system integration, data from laboratory tests of the system parameters, laboratory tests on a model bridge, and field tests on a large-scale bridge are given"--Abstract, page iii.

Advisor(s)

Watkins, Steve Eugene, 1960-

Committee Member(s)

Story, J. Greg
Grant, Steven L.
Stanley, R. Joe
Moss, Randy Hays, 1953-

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2009

Pagination

x, 83 pages

Note about bibliography

Includes bibliographical references (pages 79-82).

Rights

© 2009 Theresa Mae Swift, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Subject Headings

Bridges -- InspectionIntelligent agents (Computer software)Smart structuresStructural health monitoring

Thesis Number

T 9532

Print OCLC #

606871978

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