Neural network based sensor signal monitoring of instrumented structures

Stuart S. Chen; Sungkon Kim

Neural network based sensor signal monitoring of instrumented structures

Stuart S. Chen
, Sungkon Kim

Department of Civil, Structural & Environmental Engineering

SUNY Buffalo

Research output: Contribution to conference › Paper › peer-review

2 Scopus citations

Abstract

Signal monitoring of instrumented structures will require an appropriate suite of information processing techniques. One such technique, involving neural networks, is developed to identify and locate structural damage in a 3D steel truss-type structure instrumented with accelerometers and strain gauges. Results of the investigation indicate that neural networks provide a promising approach as one component of the computational toolkit required for autonomous signal monitoring of instrumented structures.

Original language	English
Pages	52-55
Number of pages	4
State	Published - 1995
Event	Proceedings of the 13th Structures Congress. Part 1 (of 2) - Boston, MA, USA Duration: Apr 3 1995 → Apr 5 1995

Conference

Conference	Proceedings of the 13th Structures Congress. Part 1 (of 2)
City	Boston, MA, USA
Period	04/3/95 → 04/5/95

Cite this

@conference{7278e146110f4c4ca484a5df944c0d3b,

title = "Neural network based sensor signal monitoring of instrumented structures",

abstract = "Signal monitoring of instrumented structures will require an appropriate suite of information processing techniques. One such technique, involving neural networks, is developed to identify and locate structural damage in a 3D steel truss-type structure instrumented with accelerometers and strain gauges. Results of the investigation indicate that neural networks provide a promising approach as one component of the computational toolkit required for autonomous signal monitoring of instrumented structures.",

author = "Chen, \{Stuart S.\} and Sungkon Kim",

year = "1995",

language = "English",

pages = "52--55",

note = "Proceedings of the 13th Structures Congress. Part 1 (of 2) ; Conference date: 03-04-1995 Through 05-04-1995",

}

TY - CONF

T1 - Neural network based sensor signal monitoring of instrumented structures

AU - Chen, Stuart S.

AU - Kim, Sungkon

PY - 1995

Y1 - 1995

N2 - Signal monitoring of instrumented structures will require an appropriate suite of information processing techniques. One such technique, involving neural networks, is developed to identify and locate structural damage in a 3D steel truss-type structure instrumented with accelerometers and strain gauges. Results of the investigation indicate that neural networks provide a promising approach as one component of the computational toolkit required for autonomous signal monitoring of instrumented structures.

AB - Signal monitoring of instrumented structures will require an appropriate suite of information processing techniques. One such technique, involving neural networks, is developed to identify and locate structural damage in a 3D steel truss-type structure instrumented with accelerometers and strain gauges. Results of the investigation indicate that neural networks provide a promising approach as one component of the computational toolkit required for autonomous signal monitoring of instrumented structures.

UR - https://www.scopus.com/pages/publications/0029220599

M3 - Paper

AN - SCOPUS:0029220599

SP - 52

EP - 55

T2 - Proceedings of the 13th Structures Congress. Part 1 (of 2)

Y2 - 3 April 1995 through 5 April 1995

ER -

Neural network based sensor signal monitoring of instrumented structures

Abstract

Conference

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