Cyber-Physical Codesign of Distributed Structural HealthMonitoring 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:

1. Abstract2. Introduction3. Previous/Related Works4. Damage localization approach5. Distributed architecture

1. Multi-Level Damage Localization2. Network Hierarchy3. Enhanced FDD

6. Implementation1. Hardware Platform2. Software Platform

7. Evaluation1. Cantilever Beam2. Truss

8. Conclusion

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 networksand structural engineering algorithms, this paper proposes a cyber-physical co-design approach to structural health monitoring based on wireless sensor networks. Our approach closely integrates (1) flexibility-based damage localizationmethods 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.

Abstract:

• 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.

Lets get started…

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 baselineF 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:

• 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