Sensor network paradigms for structural health monitoring

2006 ◽  
Vol 13 (1) ◽  
pp. 210-225 ◽  
Author(s):  
Charles R. Farrar ◽  
Gyuhae Park ◽  
David W. Allen ◽  
Mike D. Todd
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Structural Health

Validation of HDOP Measure for Impact Detection in Sensor Network-Based Structural Health Monitoring

2009 ◽  
Vol 9 (9) ◽  
pp. 1098-1102 ◽  
Author(s):  
David Akopian ◽  
Arsen Melkonyan ◽  
C. L. Philip Chen
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Structural Health ◽  
Impact Detection

Sensor Network for Structural Health Monitoring of a Highway Bridge

2010 ◽  
Vol 24 (1) ◽  
pp. 11-24 ◽  
Author(s):  
Michael Fraser ◽  
Ahmed Elgamal ◽  
Xianfei He ◽  
Joel P. Conte
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Highway Bridge ◽  
Structural Health

scholarly journals A Wireless Strain Sensor Network for Structural Health Monitoring

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Chengyin Liu ◽  
Jun Teng ◽  
Ning Wu
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Evaluation System ◽  
Strain Sensor ◽  
Modal Testing ◽  
Dynamic Strain ◽  
Structural Dynamic ◽  
Structural Health ◽  
Strain Monitoring

Structural strain under external environmental loads is one of the main monitoring parameters in structural health monitoring or dynamic tests. This paper presents a wireless strain sensor network (WSSN) design for monitoring structural dynamic strain field. A precision strain sensor board is developed and integrated with the IRIS mote hardware/software platform for multichannel strain gauge signal conditioning and wireless monitoring. Measurement results confirm the sensor’s functionality regarding its static and dynamic characterization. Furthermore, in order to verify the functionality of the designed wireless strain sensor for dynamic strain monitoring, a cluster-star network evaluation system is developed for strain modal testing on an experimental steel truss structure. Test results show very good agreement with the finite element (FE) simulations. This paper demonstrates the feasibility of the proposed WSSN for large structural dynamic strain monitoring.

A prototype mobile sensor network for structural health monitoring

2009 ◽  
Author(s):  
Dapeng Zhu ◽  
Quanquan Qi ◽  
Yang Wang ◽  
Kok-Meng Lee ◽  
Shaohui Foong
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Mobile Sensor ◽  
Mobile Sensor Network ◽  
Structural Health

Impact Detection Using an Array of Piezoelectric Wafer Active Sensors and a Microcontroller Unit

2010 ◽  
Author(s):  
Abraham Light-Marquez ◽  
Andrei Zagrai
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Detection System ◽  
Active Sensors ◽  
Structural Health ◽  
Impact Detection ◽  
Piezoelectric Wafer Active Sensors ◽  
Piezoelectric Wafer ◽  
The Impact

This report discusses the development of an embeddable impact detection system utilizing an array of piezoelectric wafer active sensors (PWAS) and a microcontroller. Embeddable systems are a critical component to successfully implement a complete and robust structural health monitoring system. System capabilities include impact detection, impact location determination and digitization of the impact waveform. A custom algorithm was developed to locate the site of the impact.. The embedded system has the potential for additional capabilities including advanced signal processing and the integration of wireless functionality. For structural health monitoring applications it is essential to determine the extent of damage done to the structure. In an attempt to determine these parameters a series of impact tests were conducted using a ball drop tower on a square aluminum plate. The response of the plate to the impact event was recorded using a piezoelectric wafer sensor network attached to the surface of the plate. From this testing it was determined that several of the impact parameters are directly correlated with the features recorded by the sensor network.

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