Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.

Smart Material Systems and MEMS: Design and Development Methodologies

Abstract: Preface. About the Authors. PART 1: FUNDAMENTALS. 1. Introduction to Smart Systems. 1.1 Components of a smart system. 1.2 Evolution of smart materials and structures. 1.3 Application areas for smart systems. 1.4 Organization of the book. References. 2. Processing of Smart Materials. 2.1 Introduction. 2.2 Semiconductors and their processing. 2.3 Metals and metallization techniques. 2.4 Ceramics. 2.5 Silicon micromachining techniques. 2.6 Polymers and their synthesis. 2.7 UV radiation curing of polymers. 2.8 Deposition techniques for polymer thin films. 2.9 Properties and synthesis of carbon nanotubes. References. PART 2: DESIGN PRINCIPLES. 3. Sensors for Smart Systems. 3.1 Introduction. 3.2 Conductometric sensors. 3.3 Capacitive sensors. 3.4 Piezoelectric sensors. 3.5 Magnetostrictive sensors. 3.6 Piezoresistive sensors. 3.7 Optical sensors. 3.8 Resonant sensors. 3.9 Semiconductor-based sensors. 3.10 Acoustic sensors. 3.11 Polymeric sensors. 3.12 Carbon nanotube sensors. References. 4. Actuators for Smart Systems. 4.1 Introduction. 4.2 Electrostatic transducers. 4.3 Electromagnetic transducers. 4.4 Electrodynamic transducers. 4.5 Piezoelectric transducers. 4.6 Electrostrictive transducers. 4.7 Magnetostrictive transducers. 4.8 Electrothermal actuators. 4.9 Comparison of actuation schemes. References. 5. Design Examples for Sensors and Actuators. 5.1 Introduction. 5.2 Piezoelectric sensors. 5.3 MEMS IDT-based accelerometers. 5.4 Fiber-optic gyroscopes. 5.5 Piezoresistive pressure sensors. 5.6 SAW-based wireless strain sensors. 5.7 SAW-based chemical sensors. 5.8 Microfluidic systems. References. PART 3: MODELING TECHNIQUES. 6. Introductory Concepts in Modeling. 6.1 Introduction to the theory of elasticity. 6.2 Theory of laminated composites. 6.3 Introduction to wave propagation in structures. References. 7. Introduction to the Finite Element Method. 7.1 Introduction. 7.2 Variational principles. 7.3 Energy functionals and variational operator. 7.4 Weak form of the governing differential equation. 7.5 Some basic energy theorems. 7.6 Finite element method. 7.7 Computational aspects in the finite element method. 7.8 Superconvergent finite element formulation. 7.9 Spectral finite element formulation. References. 8. Modeling of Smart Sensors and Actuators. 8.1 Introduction. 8.2 Finite element modeling of a 3-D composite laminate with embedded piezoelectric sensors and actuators. 8.3 Superconvergent smart thin-walled box beam element. 8.4 Modeling of magnetostrictive sensors and actuators. 8.5 Modeling of micro electromechanical systems. 8.6 Modeling of carbon nanotubes (CNTs). References. 9. Active Control Techniques. 9.1 Introduction. 9.2 Mathematical models for control theory. 9.3 Stability of control system. 9.4 Design concepts and methodology. 9.5 Modal order reduction. 9.6 Active control of vibration and waves due to broadband excitation. References. PART 4: FABRICATION METHODS AND APPLICATIONS. 10. Silicon Fabrication Techniques for MEMS. 10.1 Introduction. 10.2 Fabrication processes for silicon MEMS. 10.3 Deposition techniques for thin films in MEMS. 10.4 Bulk micromachining for silicon-based MEMS. 10.5 Silicon surface micromachining. 10.6 Processing by both bulk and surface micromachining. 10.7 LIGA process. References. 11. Polymeric MEMS Fabrication Techniques. 11.1 Introduction. 11.2 Microstereolithography. 11.3 Micromolding of polymeric 3-D structures. 11.4 Incorporation of metals and ceramics by polymeric processes. 11.5 Combined silicon and polymer structures. References. 12. Integration and Packaging of Smart Microsystems. 12.1 Integration of MEMS and microelectronics. 12.2 MEMS packaging. 12.3 Packaging techniques. 12.4 Reliability and key failure mechanisms. 12.5 Issues in packaging of microsystems. References. 13. Fabrication Examples of Smart Microsystems. 13.1 Introduction. 13.2 PVDF transducers. 13.3 SAW accelerometer. 13.4 Chemical and biosensors. 13.5 Polymeric fabrication of a microfluidic system. References. 14. Structural Health Monitoring Applications. 14.1 Introduction. 14.2 Structural health monitoring of composite wing-type structures using magnetostrictive sensors/actuators. 14.3 Assesment of damage severity and health monitoring using PZT sensors/actuators. 14.4 Actuation of DCB specimen under Mode-II dynamic loading. 14.5 Wireless MEMS-IDT microsensors for health monitoring of structures and systems. References. 15. Vibration and Noise-Control Applications. 15.1 Introduction. 15.2 Active vibration control in a thin-walled box beam. 15.3 Active noise control of structure-borne vibration and noise in a helicopter cabin. References. Index.

Health Checks through Landmark Bridges to Sky-high Structures

Abstract: Massive infrastructure projects developed in Hong Kong make for big challenges and unique opportunities for engineers and researchers. The construction of the cables-stayed Stonecutters Bridge sets up a new landmark in the bridge engineering community, with its main span exceeding 1,000 m as well as its sophisticated instrumentation system comprising more than 1,500 sensors. The development of structural health monitoring (SHM) technology has evolved for over 10 years in Hong Kong since the implementation of the so-called “Wind And Structural Health Monitoring System (WASHMS)” on the suspension Tsing Ma Bridge in 1997. The successful engineering paradigms of implementing and operating SHM systems for five cable-supported bridges and experiences gained by practice and research in the past decade have promoted the applications of this technology beyond Hong Kong and extending from long-span bridges to high-rise structures. In this paper, the evolution in the design methodology for SHM systems, the advanceme...

On the Value of Monitoring Information for the Structural Integrity and Risk Management

Abstract: This article introduces an approach and framework for the quantification of the value of structural health monitoring (SHM) in the context of the structural risk and integrity management for systems. The quantification of the value of SHM builds upon the Bayesian decision and utility theory, which facilitates the assessment of the value of information associated with SHM. The principal approach for the quantification of the value of SHM is formulated by modeling the fundamental decision of performing SHM or not in conjunction with their expected utilities. The expected utilities are calculated accounting for the probabilistic performance of a system in conjunction with the associated structural integrity and risk management actions throughout the life cycle, the associated benefits, structural risks, and costs and when performing SHM, the SHM information, their probabilistic outcomes, and costs. The calculation of the expected utilities necessitates a comprehensive and rigorous modeling, which is introduced close to the original formulations and for which analysis characteristics and simplifications are described and derived. The framework provides the basis for the optimization of the structural risk and integrity management based on utility gains including or excluding SHM and inspection information. Studies of fatigue deteriorating structural Systems and their characteristics (1) provide decision Support for the performance of SHM, (2) explicate the influence of the structural component and system characteristics on the value of SHM, and (3) demonstrate how an integral optimization of SHM and inspection strategies for an efficient structural risk and integrity management can be performed.

Experimental modal analysis of an aircraft model wing by embedded fiber Bragg grating sensors

Abstract: A critical issue in practical structural health monitoring is related to the capability of proper sensing systems integrated within the host structures to detect, identify, and localize damage generation. To this aim, many techniques have been proposed involving dynamic measurements such as modal analysis, acoustic emission, and ultrasonics. This paper relies on the use of embedded fiber Bragg grating sensors for performing an experimental modal analysis on a wing of an aircraft model. Time domain response of the embedded fiber-optic sensors induced by hammer impacts were acquired and transformed into the frequency domain. Using a classical technique based on the frequency transfer function, the first displacement and strain mode shapes of the wing have been retrieved in terms of natural frequencies and amplitudes. Experimental results confirm the excellent performances of this class of sensing devices to determine the modal behavior within complex structures compared with conventional accelerometer-based detection systems.

Damage identification in civil engineering structures utilizing PCA-compressed residual frequency response functions and neural network ensembles

Abstract: This paper presents a non-destructive, global, vibration-based damage identification method that utilizes damage pattern changes in frequency response functions (FRFs) and artificial neural networks (ANNs) to identify defects. To extract damage features and to obtain suitable input parameters for ANNs, principal component analysis (PCA) techniques are applied. Residual FRFs, which are the differences in the FRF data from the intact and the damaged structure, are compressed to a few principal components and fed to ANNs to estimate the locations and severities of structural damage. A hierarchy of neural network ensembles is created to take advantage of individual information from sensor signals. To simulate field-testing conditions, white Gaussian noise is added to the numerical data and a noise sensitivity study is conducted to investigate the robustness of the developed damage detection technique to noise. Both numerical and experimental results of simply supported steel beam structures have been used to demonstrate effectiveness and reliability of the proposed method. Copyright © 2009 John Wiley & Sons, Ltd.