Structural Health Monitoring 2011 : condition-based maintenance and intelligent structures

1386 Pages·2011·84.225 MB·English

by  Fu-Kuo Chang, Fu-Kuo Chang

VOLUME 1
S
TRUCTURAL
H
EALTH
M
ONITORING
2011
Condition-based Maintenance and Intelligent Structures
Edited by
Fu-Kuo Chang
Department of Aeronautics and Astronautics
Stanford University, Stanford, CA 94305
Proceedings of the 8th International Workshop on Structural
Health Monitoring, Stanford University, Stanford, CA
September 13–15, 2011
Sponsors:
Air Force Office of Scientific Research
Army Research Office
National Science Foundation
Office of Naval Research
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Preface

This proceedings is a collection of papers detailing the most recent technology devel-
opment in the field of Structural Health Monitoring (SHM) from around the world since
2009. These papers were presented at the 8th International Workshop on Structural Health
Monitoring held at Stanford University on September 13-15, 2011. More than 325 papers
were selected and included in the proceedings with applications expanding from tradi-
tional aerospace structures and civil infrastructures to marine/offshore and wind power
infrastructures as well as structures in different platforms. Significant progress since the
last meeting, in 2009, is clearly noticeable, particularly in the area of sensors/actuators
development, detection capabilities, and system maturation for implementation.
SHM is a technology to automate the inspection process to assess and evaluate the
health condition of structures in real-time or at specified time intervals. Because it is a sys-
tem technology which integrates sensors/actuator networks with structures, software to in-
terpret sensor signals, and hardware to process and manage the signals, the technology ma-
turity based on its complexity and targeted solutions can be classified into four different
sequential levels: detection, identification, quantification, and decision. Detection is the
lowest level that the technology can be achieved for its maturity. Once detection is con-
firmed with a high degree of confidence, identification of the occurrence of the event in
time and space domain is critical which then can possibly lead to quantification of the
event. A more accurate quantification may produce a better decision, which provides a
much more efficient management solution for the structures than traditional inspections.
Therefore, the theme of the 8th International Workshop on Structural Health Monitor-
ing is “Condition-Based Maintenance and Intelligent Structures”. It is clear that
SHM is the key technology to enable the transition from traditional schedule-driven
maintenance to Condition-Based Maintenance (CBM). In a CBM environment, operating
platforms, embedded sensors, inspections, and other triggering events determine when
restorative maintenance tasks are required based on evidence of need. With the continu-
ing maturation of SHM technology to higher levels, it is foreseeable that SHM technol-
ogy will enable prediction of structural health conditions ahead of event and take appro-
priate actions. This is actually the goal of CBM+ in the US Department of Defense, a
proactive equipment maintenance capability to extend the availability of structural sys-
tems throughout their life cycles and reduce costs.
xxxiii
xxxiv Preface
From the proceedings, it can be seen that significant attention of the SHM community
continues to focus on the SHM technology development for achieving the goal of CBM+
in order to improve operation efficiency, reduce maintenance cost, as well as enhance the
structural reliability in a real-time operation basis. A growing number of papers focus on
verification, validation, and qualification of the technology for implementation, particu-
larly with attention to the aerospace platforms. Considerable studies also emphasize envi-
ronmental influences on SHM system stability, reliability, and applicability. New re-
search topics that deserve more fundamental studies are also identified from these devel-
opments.
With the continuing maturation of the SHM technology to higher levels, the SHM
system can potentially create a structural platform with a complete self-responsiveness
capability from sensing, diagnostics, to decision-making and then back to sensing in a
close loop, which is the exact foundation that is needed for construction of the so-called
“intelligent structures”. With advanced manufacturing technologies that allow hardware
and software to be built into the materials with SHM capabilities, it seems to be a logical
step for this research community to start exploring the linkage between Structural Health
Monitoring and intelligent structures.
Clearly, the development of SHM technology sets the foundation for the development
of intelligent structures. The roadmap of SHM technology development seems to target
CBM+ as its near-term goal with a long-term objective to develop new generation mate-
rials for intelligent structures. Numerous papers dealing with new concepts and ideas of
intelligent structures and bio-mimetic structures appeared in the proceedings. Special ses-
sions were organized to focus on bio-inspired sensor networks and intelligent sensor
nodes, which are the key fundamental elements in providing intelligence to the overall
systems.
Special thanks to the special session organizers whose contributions are listed below:

Bio-inspired Sensing and Actuation Technology J. Lynch, K. Loh
Wind Turbines Monitoring W. Staszewski
Monitoring of Civil Engineering Structures with MEMS C. Grosse, J. Lynch
Verification and Validation of Damage Sensing E. Medina
Intelligent sensor networks for SHM J. Lynch, A. Swartz
Structural Health Monitoring of Wind Turbines J. R. White
Advanced SHM for Ship Structures L. Salvino
Hot Spot Monitoring H. Sohn, J.B. Ihn, M. Leonard
Wave Propagation Simulation W. Staszewski, W. Ostachowicz
Decision Making in Structural Health Monitoring D. Zonta, M. Todd
SHM Benchmark for High-rise Structures Y.Q. Ni
Non-contact Sensing Technologies H. Sohn

This workshop is co-sponsored by the Air Force Office of Scientific Research (Les
Lee and David Stargel), the Army Research Office (Bruce LaMattina), the Office of Na-
val Research (Ignacio Perez), and the National Science Foundation (Shih-Chi Liu and
Preface xxxv
M.P. Singh). The workshop could not have been successfully organized without the sup-
port of the international organization committee, which includes the following members:

Academia
D. Adams, Purdue University, USA, ([email protected])
G. Akhras, Royal Military College of Canada, Canada, ([email protected])
A. Emin Aktan, Drexel University, USA, ([email protected])
A. Braga, Rio Pontificia Unversidade Catolica do Rio de Janiero, Brazil, ([email protected])
F. Casciati, University of Pavia, Italy, ([email protected])
F.-K. Chang (Organizer), Stanford University, USA, ([email protected])
W. K. Chiu, Monash University, Australia, ([email protected])
C.-P. Fritzen, University of Siegen, Germany, ([email protected])
B. Glisic, Princeton University, ([email protected])
A. Guemes (Co-Organizer), Universidad Politecnica de Madrid, Spain, ([email protected])
P. Hagedorn, TU Darmstadt, Germany, ([email protected])
D. Inman, Virginia Tech, USA, ([email protected])
S. Kapuria, India Institute of Technology, New Delhi, ([email protected])
A. Kiremidjian, Stanford University, USA, ([email protected])
T. Kundu, University of Arizona, USA, ([email protected])
J. Lynch, University of Michigan, USA, ([email protected])
A. Mita, Keio University, Japan, ([email protected])
Y.Q. Ni, Hong Kong Polytechnic University, Hong Kong, ([email protected])
W. Ostachowicz, Polish Academy of Sciences, Poland, ([email protected])
U. Peil, Technical University of Braunschweig, Germany, ([email protected])
W. Staszewski, Sheffield University, UK, ([email protected])
F. Lanza di Scalea, UC San Diego, USA, ([email protected])
H. Sohn, KAIST, Korea, ([email protected])
N. Takeda, University of Tokyo, Japan, ([email protected])
M. Wang, Northeast University, USA, ([email protected])
Z. Wu, Dalian Institute of Technology, China, ([email protected])
Z. Wu, Ibaraki University, Japan, ([email protected])

Industry
S. Arms, Microstrain, USA, ([email protected])
S. Beard, Acellent Technologies, USA, ([email protected])
M. Buderath, Cassidian, Germany, ([email protected])
P. Foote, BAE, UK, ([email protected])
B. Glass, Lockheed-Martin, USA, ([email protected])
G. Gordon, Honeywell, USA, ([email protected])
M. Hansen, Goodrich, USA, ([email protected])
E. Haugse, Boeing Company, USA, ([email protected])
H. Speckmann, Airbus, Germany, ([email protected])
P. Anchieta da Silva, Embraer, Brazil, ([email protected])
H. Wenzel, VCE Holding GmbH, Austria, ([email protected])

Government
C. Boller, IZFP, Germany, ([email protected])
M. Derriso, Wright-Patterson Air Force Laboratories, USA, ([email protected])
C. Farrar, Los Alamos National Laboratory, USA, ([email protected])
S. Galea, DSTO Australia, Australia, ([email protected])
B. Lamattina, Army Research Office, USA, ([email protected])
D. Le, US Army Research Laboratory, USA, ([email protected])
B.L. Lee, Air Force Office of Scientific Research, USA, ([email protected])
S. Liu, National Science Foundation, USA, ([email protected])
xxxvi Preface
S. Mahmood, Naval Surface Warfare Center, USA, ([email protected])
W. Prosser, NASA-Langley, USA, ([email protected])
O.Venta, VTT, Finland, ([email protected])
L. Salvino, ([email protected])
A. Srivastava, NASA-Ames, USA, ([email protected])
D. Stargel, ([email protected])
H. F. Wu, NIST, USA, ([email protected])
N. Li, China Communications Construction, China, ([email protected])

The committee would also like to express its sincere appreciation for the dedication
and support of the workshop coordinators Ingolf Mueller, Surajit Roy, Kuldeep Lonkar,
Yu-Hung Li, Cecilia Larrosa, Zhiqiang Guo, Vishnuvardhan Janapati, Nathan Salowitz,
Yitao Zhuang, Philipp Maier, Sang-Jong Kim, David Wang, Kerstin Vonnieda, Alex
Guo, and many volunteers, as well as to Grace Fontanilla, Haruko Markitani and other
staff members from the Department of Aeronautics and Astronautics for making this
workshop possible.

Fu-Kuo Chang Alfredo Güemes
Organizing Chairman Organizing Co-Chairman
Department of Aeronautics and Astronautics E.T.S.I. Aeronauticos
Stanford University, Universidad Politecnica de Madrid,
Stanford, CA 94305, USA Madrid, Spain

September 13, 2011
Table of Contents
VOLUME 1
Preface xxxiii
KEYNOTE PRESENTATIONS
Integration of Structural Health Monitoring Systems into Unmanned
Aerial Systems—Challenges and Opportunities . . . . . . . . . . . . . . 3
M. BUDERATH and L. BENASSI
The Journey to Incorporate Health Monitoring and Condition Based
Maintenance of Sikorsky Commercial Helicopters. . . . . . . . . . . . 11
J. P. CYCON
EmbraerPerspective on the Introduction of SHM into Current and
Future Commercial Aviation Programs. . . . . . . . . . . . . . . . . . 19
L. G. DOS SANTOS
Structural Health Monitoring forCivil Infrastructure—From
Instrumentation to Decision Support . . . . . . . . . . . . . . . . . . . 27
A. S. KIREMIDJIAN
Does the Maturity of Structural Health Monitoring Technology
Match UserReadiness?. . . . . . . . . . . . . . . . . . . . . . . . . . . 39
D. ROACH and S. NEIDIGK
ADVANCED DIAGNOSTICS FOR DAMAGE ASSESSMENT
Damage Diagnosis Algorithm forCivil Structures Using a Sequential
Change Point Detection Method and Time-Series Analysis . . . . . . . 55
H. Y. NOH, R. RAJAGOPAL and A. S. KIREMIDJIAN
Cointegration and SHM of Bridges . . . . . . . . . . . . . . . . . . . . 63
E. J. CROSS, K. WORDEN, K.-Y. KOO and J. M. W. BROWNJOHN
iii
iv TableofContents
Piezoceramic-Based 2-D Spiral Phased Array forDamage Detection
of Thin Orthotropic Composite Laminates . . . . . . . . . . . . . . . . 71
B. YOO and D. J. PINES
Guided Wave and Probability Based Diagnostic Imaging for
Detection of Multiple Welding Damages in Welded
Tubular Steel Structures . . . . . . . . . . . . . . . . . . . . . . . . . . 79
X. LU, M. LU, L. ZHOU, Z. SU, L. CHENG, L. YE and G. MENG
NonlinearCointegration as a Combinatorial Optimisation
Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
E. J. CROSS and K. WORDEN
Characterizing Damage in Plate Structures Based on Local
Perturbance to Dynamic Equilibrium. . . . . . . . . . . . . . . . . . . 95
H. XU, L. CHENG and Z. SU
Robust Diagnostics forBayesian Compressive Sensing Technique in
Structural Health Monitoring. . . . . . . . . . . . . . . . . . . . . . . 103
Y. HUANG, J. L. BECK, S. WU and H. LI
Damage Monitoring and Evaluation forBuilding Structures
Based on Measurement of Relative Story Displacements by
Noncontact-Type Sensors . . . . . . . . . . . . . . . . . . . . . . . . . 111
T. HATADA, M. TAKAHASHI, R. KATAMURA, H. HAGIWARA,
I. MATSUYA, K. KANEKAWA, Y. NITTA and A. NISHITANI
Joint Condition Identification with Partially Measured Frequency
Response Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
M. WANG and G. ZHENG
Multi-ClassifierFusion Method Based on the Reliability of the
Individual Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
L. AL-SHROUF and D. SOEFFKER
Validation of a Hybrid Automated Modal Identification Algorithm
forStructural Health Monitoring Applications . . . . . . . . . . . . . 135
C. RAINIERI and G. FABBROCINO
PowerLosses in PZTDisk Actuators' Adhesive. . . . . . . . . . . . . 143
R. DUGNANI
Sensitivity of the Excitelet Imaging Algorithm on Material
Properties forIsotropic Structures . . . . . . . . . . . . . . . . . . . . 151
P.-C. OSTIGUY, P. MASSON, N. QUAEGEBEUR and S. ELKOUN
Damage Detection Index Based on Statistical Inference and PCA. . . 159
L. E. MUJICA, M. RUIZ, F. POZO and J. RODELLAR
TableofContents v
Effective Damage Sensitive Feature Extraction Methods forCrack
Detection Using Flaw Scattered Ultrasonic Wave Field Signal. . . . . 167
S. K. YADAV, S. BANERJEE and T. KUNDU
Time-Domain Localized Structural Damage Identification with
Incomplete Excitation Measurements . . . . . . . . . . . . . . . . . . 175
J. HE and B. XU
ANovel Damage Sensitive Feature Based on State-Space
Representation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
A. CLEMENT, S. LAURENS and S. GIRARD
Damage Classification in Composite Laminates: Matrix
Micro-Cracking and Delamination. . . . . . . . . . . . . . . . . . . . 191
C. C. LARROSA, K. LONKAR, S. SHANKAR and F.-K. CHANG
Identifying ScatterTargets in 2D Space Using In Situ
Phased-Arrays forGuided Wave Structural Health Monitoring. . . . 200
E. B. FLYNN, M. D. TODD, S. S. KESSLER and C. T. DUNN
Reference-Free Damage Identification Using Statistical
Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
A. MEDDA and V. DEBRUNNER
Infrared Thermography and Piezoelectric Patches forImpact
Damage Detection in Composite Structures . . . . . . . . . . . . . . . 216
G. M. CARLOMAGNO, C. MEOLA and F. RICCI
An Integrated Structural Intensity Based Damage Detection
Approach forNonlinearBehaving Damage . . . . . . . . . . . . . . . 224
F. SEMPERLOTTI, S. C. CONLON and E. C. SMITH
Experimentation and Detection Characters of Lamb Wave Phase
Array on a Large Thin Aluminium Plate . . . . . . . . . . . . . . . . 233
D. GAO, Z. WU, M. LIU and Z. WANG
Damage Detection of Composite Structure Using Independent
Component Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
R. HAJRYA, N. MECHBAL and M. VERGÉ
Rapid Localization and Ultrasonic Imaging of Multiple Damages in
Structural Panel with Piezoelectric Sensor-ActuatorNetwork. . . . . 249
G. K. GEETHA, V. T. RATHOD, N. CHAKRABORTY,
D. R. MAHAPATRA and S. GOPALAKRISHNAN
Damage Assessment of CFRPStiffened Panels by Electro-Mechanical
Impedance Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
N. J. FERREIRA, J. M. SILVA, R. J. GUIMARAES, P. J. ANTUNES,
M. A. BAPTISTA, J. C. VIANA and G. R. DIAS
vi TableofContents
Optimal SensorFusion forStructural Health Monitoring of Aircraft
Composite Components. . . . . . . . . . . . . . . . . . . . . . . . . . 266
S. COSTINER, H. A. WINSTON, M. R. GURVICH, A. GHOSHAL, G. S.
WELSH, S. L. BUTLER, M. R. URBAN and N. BORDICK
Impact and Damage Location Detection on Plate-Like Structures
Using Time—Reversal Method. . . . . . . . . . . . . . . . . . . . . . 274
C. CHEN, Y. LI and F.-G. YUAN
Fatigue Crack Detection Using Guided Waves and Probability-Based
Imaging Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282
M. LU, X. LU, L. ZHOU, Z. SU, L. YE and F. LI
Adaptive Fuzzy-Based Approach forClasification of
System's States. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290
H. ALJOUMAA and D. SOEFFKER
Image Processing Technique forVibrothermographic Field Tests. . . 298
M. SZWEDO, L. PIECZONKA and T. UHL
An Optimal Image-Based Method forIdentification of AE Sources
on Plate Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306
G. YAN and L. ZHOU
Structural Health Monitoring System Based on Electromechanical
Impedance Measurements . . . . . . . . . . . . . . . . . . . . . . . . 314
M. ROSIEK, A. MARTOWICZ and T. UHL
Damage Monitoring Based on Wave Illumination of Structures. . . . 322
Y. LIU, N. MECHBAL and M. VERGÉ
ADVANCED MONITORING FOR LOAD/ENVIRONMENTS
Design of a Self-Powered Load Monitoring System forHot Spot
Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
Y. LIN, M. TAYA and J. B. IHN
ARobust Impact Force Determination Technique forComplex
Structures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
I. MUELLER, K. VONNIEDA, S. DAS and F.-K. CHANG
Analytical Formulation forthe Determination of Torsional
Forces and ShearStresses in Hydraulic Steel Structures
from Field Experiments. . . . . . . . . . . . . . . . . . . . . . . . . . 354
Á. J. ALICEA-RODRÍGUEZ and G. RIVEROS
Experimental Evaluation of a Wavelet-Based FEM and its
Application to Load History Identification . . . . . . . . . . . . . . . 362
M. M. MOTA, L. PAHLAVAN and C. KASSAPOGLOU