Cyber-Physical Codesign of Distributed Structural Health
Monitoring With Wireless Sensor Networks
Gregory Hackmann*, Weijun Guo*, Guirong Yany, Chenyang Lu*,
Shirley Dykey
• *Department of Computer Science and Engineering,
• Washington University in St. Louisy School of Mechanical
Engineering, Purdue University
Presented By:
Ayush Khandelwal
About the Authors:
• Gregory Hackmann :Postdoctoral Research Assistant, Washington University
in St. Louis .Department of Computer Science and Engineering
• Weijun Guo: Research Associate at North Carolina State Univ.
• Guirong Yany: Researcher in Mechanical Engineering, Purdue University
• Chenyang Lu: Professor of Computer Science and Engineering ,Washington
University in St. Louis
• Shirley J. Dyke : Purdue University, Professor of Mechanical and Civil
Engineering
Acknowledgements:
This work is supported by NSF NeTS-NOSS Grant CNS-0627126 and CRI
Grant CNS-0708460
Content:
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Abstract
Introduction
Previous/Related Works
Damage localization approach
Distributed architecture
1. Multi-Level Damage Localization
2. Network Hierarchy
3. Enhanced FDD
6. Implementation
1. Hardware Platform
2. Software Platform
7. Evaluation
1. Cantilever Beam
2. Truss
8. Conclusion
Abstract:
Our deteriorating civil infrastructure faces the critical challenge of long-term
structural health monitoring for damage detection and localization. In contrast to
existing research that often separates the designs of wireless sensor networks
and structural engineering algorithms, this paper proposes a cyber-physical codesign approach to structural health monitoring based on wireless sensor networks.
Our approach closely integrates (1) flexibility-based damage localization
methods that allow a tradeoff between the number of sensors and the resolution of
damage localization, and (2) an energy-efficient, multi-level computing architecture
specially designed to leverage the multi-resolution feature of the flexibility-based
approach. The proposed approach has been implemented on the Intel Imote2
platform. Experiments on a physical beam and simulations of a truss structure
demonstrate the system's efficacy in damage localization and energy efficiency.
Lets get started…
• Deteriorating Civil Infrastructures
• Problems with sensors in Wired Technology
• Growth in Wireless Sensor Networks (WSN’s )
•
Problems With Centralized Systems viz. High latency
and high Energy consumption.
• Best Solution : Usage of CPS to provide Structural Health
Monitoring using de-centralized systems.
Related Works..
• UC Berkley Project to monitor Golden Gate Bridge
• Clarkson’s University Implementation on a bridge structure In New
York.
Problems:
• Limited data Collection in a time frame.
• Inadequacy for time constraint events due to large time for data
analyzation and collection.
Solution:
Usage of Distributed Approach based on Damage Localization
Damage localization approach :
 Physical Aspect using Flexibility based Algorithm
 Two stages of Flexibility Algorithm
• Baseline Structural Model Identification (Fb)
• Repeatedly collecting data over the passage of time (F)
The data flow of a traditional flexibility-based method
 Methods of Flexibility-Based Algorithm :
• Angles-Between-String-and-Horizon flexibility-based method (ASHFM)
•
Axial Strain flexibility-based method (ASFM)
• Formula for difference in matrix for ASHFM:
∆F = |Fb – F|
Fb is the flexibility matrix on baseline
F is computed the newly computed flexibility matrix
∆F is damage matrix
Damage Indicator:
Distributed Architecture:
Described method is good for Centralized networks. But is not energy efficient and good
for localization
Multi-Level damage Localization:
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Uses multi level search
If damage not found return nodes to sleep
If found, Multi-level search is performed and identify adjacent sensors.
Key feature: doesn’t activate all sensors at once.
Damage localization results on the cantilever beam
Network Hierarchy:
Roles of nodes:
• Cluster Member
• Cluster Head
• Base Station
Accelerometers are used to collect information.
Enhanced FDD:
Problem: High number of outputs from CSD and SVD which is not energy
efficient
Solution: Peak Picking Routine in FDD stage which allows each node to
independently identify these P natural frequencies solely from local data.
Implementation:
Hardware:
• Imote2 wireless Sensor
• PXA271 Xscale processor
• 256kb SRAM, 32 MB SDRAM
• Dynamically clocking from 13-416 MHz
• Modular stackable platform providing add-on accelerometers
Software:
 Components:
• nesC Programming Language
• TinyOS Operating System
• ISHM’s ReliableComm
• DistributedDataAcquireApp
 The Two stage Search
 Usage of TDMA for time synchronization of collected samples
Evaluation/ Deployment :
• On Cantilever Beam (using ASHFM)
• On Truss (using ASFM)
Cantilever Beam Deployement:
Damage localization results on the cantilever beam
Truss Deployement:
1.Damage Localization:
2. Energy Consumption:
Conclusion:
• Flexibility-based structural engineering methods that can localize
damages at different resolution and costs
• An efficient, multi-level computing architecture that leverage on the
multi-resolution feature of flexibility-based methods