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Y.q. Ni - One of the best experts on this subject based on the ideXlab platform.
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Structural Health monitoring of cable-supported bridges in Hong Kong
Structural Health Monitoring of Civil Infrastructure Systems, 2020Co-Authors: Kai Yuen Wong, Y.q. NiAbstract:Abstract: Structural Health monitoring in bridge engineering is the tracing of the Structural conditions of the bridge based on four major categories of physical quantities, namely: environmental loads and status, operation loads, bridge features and bridge responses by reliable on-structure instrumentation system and effective evaluation tools. In the past decade, Structural Health monitoring system has been adopted to monitor and evaluate the Structural Health conditions of cable-supported bridges in Hong Kong. The Structural Health monitoring in Hong Kong is carried out by wind and Structural Health monitoring system (WASHMS). The WASHMS is devised based on modular architecture and is currently composed of six modules, namely: Module 1 – Sensory system, Module 2 – Data acquisition and transmission system, Module 3 – Data processing and control system, Module 4 – Structural Health evaluation system, Module 5 – Structural Health data management system, and Module 6 – Inspection and maintenance system. This chapter introduces the functional and operational requirements of each modular system and tabulates the details of physical quantities required for monitoring and evaluation. Graphical outputs of some typical monitoring results from WASHMS are presented for the demonstration of WASHMS operation. Examples of WASHMS applications are also quoted.
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Structural Health monitoring of cable-supported bridges in Hong Kong
Structural Health Monitoring of Civil Infrastructure Systems, 2009Co-Authors: Kai Yuen Wong, Y.q. NiAbstract:Structural Health monitoring in bridge engineering is the tracing of the Structural conditions of the bridge based on four major categories of physical quantities, namely: environmental loads and status, operation loads, bridge features and bridge responses by reliable on-structure instrumentation system and effective evaluation tools. In the past decade, Structural Health monitoring system has been adopted to monitor and evaluate the Structural Health conditions of cable-supported bridges in Hong Kong. The Structural Health monitoring in Hong Kong is carried out by wind and Structural Health monitoring system (WASHMS). The WASHMS is devised based on modular architecture and is currently composed of six modules, namely:. Module 1 - Sensory system,Module 2 - Data acquisition and transmission system,Module 3 - Data processing and control system,Module 4 - Structural Health evaluation system,Module 5 - Structural Health data management system, andModule 6 - inspection and maintenance system.This chapter introduces the functional and operational requirements of each modular system and tabulates the details of physical quantities required for monitoring and evaluation. Graphical outputs of some typical monitoring results from WASHMS are presented for the demonstration of WASHMS operation. Examples of WASHMS applications are also quoted. © 2009 Woodhead Publishing Limited All rights reserved.
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technology developments in Structural Health monitoring of large scale bridges
Engineering Structures, 2005Co-Authors: J.m. Ko, Y.q. NiAbstract:Abstract The significance of implementing long-term Structural Health monitoring systems for large-scale bridges, in order to secure Structural and operational safety and issue early warnings on damage or deterioration prior to costly repair or even catastrophic collapse, has been recognized by bridge administrative authorities. Developing a long-term monitoring system for a large-scale bridge—one that is really able to provide information for evaluating Structural integrity, durability and reliability throughout the bridge life cycle and ensuring optimal maintenance planning and safe bridge operation—poses technological challenges at different levels, from the selection of proper sensors to the design of a Structural Health evaluation system. This paper explores recent technology developments in the field of Structural Health monitoring and their application to large-scale bridge projects. The need for technological fusion from different disciplines, and for a Structural Health evaluation paradigm that is really able to help prioritize bridge rehabilitation, maintenance and emergency repair, is highlighted.
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Technology developments in Structural Health monitoring of large-scale bridges
Engineering Structures, 2005Co-Authors: J.m. Ko, Y.q. NiAbstract:The significance of implementing long-term Structural Health monitoring systems for large-scale bridges, in order to secure Structural and operational safety and issue early warnings on damage or deterioration prior to costly repair or even catastrophic collapse, has been recognized by bridge administrative authorities. Developing a long-term monitoring system for a large-scale bridge-one that is really able to provide information for evaluating Structural integrity, durability and reliability throughout the bridge life cycle and ensuring optimal maintenance planning and safe bridge operation - Poses technological challenges at different levels, from the selection of proper sensors to the design of a Structural Health evaluation system. This paper explores recent technology developments in the field of Structural Health monitoring and their application to large-scale bridge projects. The need for technological fusion from different disciplines, and for a Structural Health evaluation paradigm that is really able to help prioritize bridge rehabilitation, maintenance and emergency repair, is highlighted. © 2005 Elsevier Ltd. All rights reserved.
Charles R Farrar - One of the best experts on this subject based on the ideXlab platform.
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Sensing Network Paradigms for Structural Health Monitoring
Structural Control & Health Monitoring, 2020Co-Authors: Charles R Farrar, Gyu Hae Park, Michael D. ToddAbstract:The process of Structural Health monitoring (SHM) requires an integrated paradigm of networked sensing and actuation, data interrogation (signal processing and feature extraction), and statistical assessment (classification of damage existence, location, and/or type) that treats Structural Health assessments in a systematic way. An appropriate sensor network is always required in observing the Structural system behaviour in such a way that suitable signal processing and damage-sensitive feature extraction on the measured data can be performed efficiently. Consequently, several sensing network paradigms for SHM have emerged in the past, and this chapter is intended to provide an overview of these paradigms. Various parameters of SHM sensing systems that must be considered in its design and subsequent field deployment are also summarized.
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On assessing the robustness of Structural Health monitoring technologies
Conference Proceedings of the Society for Experimental Mechanics Series, 2012Co-Authors: Christopher J. Stull, Fran??ois M. Hemez, Charles R FarrarAbstract:As Structural Health monitoring continues to gain popularity, both as an area of research and as a tool for use in industrial applications, the number of technologies associated with Structural Health monitoring will also continue to grow. As a result, the engineer tasked with developing a Structural Health monitoring system is faced with myriad hardware and software technologies from which to choose, often adopting an ad hoc qualitative approach based on physical intuition or past experience to making such decisions, and offering little in the way of justification for a particular decision. This article offers a framework that aims to provide the engineer with a quantitative approach for choosing from among a suite of candidate Structural Health monitoring technologies. The framework is outlined for the general case, where a supervised learning approach to Structural Health monitoring is adopted and is then demonstrated on two problems commonly encountered when developing Structural Health monitoring systems: (a) selection of damage-sensitive features, where the engineer must determine the appropriate order of an autoregressive model for modeling of time-history data, and (b) selection of a damage classifier, where the engineer must select from among a suite of candidate classifiers, the one most appropriate for the task at hand. The data employed for these problems are taken from a preliminary study that examined the feasibility of applying Structural Health monitoring technologies to the RAPid Telescopes for Optical Response observatory network. © The Author(s) 2012.
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Sensing network paradigms for Structural Health monitoring
Lecture Notes in Electrical Engineering, 2011Co-Authors: Charles R Farrar, Gyu Hae Park, Michael D. ToddAbstract:The process of Structural Health monitoring (SHM) requires an integrated paradigm of networked sensing and actuation, data interrogation (signal processing and feature extraction), and statistical assessment (classification of damage existence, location, and/or type) that treats Structural Health assessments in a systematic way. An appropriate sensor network is always required in observing the Structural system behaviour in such a way that suitable signal processing and damage-sensitive feature extraction on the measured data can be performed efficiently. Consequently, several sensing network paradigms for SHM have emerged in the past, and this chapter is intended to provide an overview of these paradigms. Various parameters of SHM sensing systems that must be considered in its design and subsequent field deployment are also summarized. © 2011 Springer-Verlag Berlin Heidelberg.
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Nonlinear feature identification of impedance-based Structural Health monitoring
Smart Structures and Materials 2004: Smart Structures and Integrated Systems, 2004Co-Authors: Amanda C. Rutherford, Gyu Hae Park, H. Sohn, Charles R FarrarAbstract:The impedance-based Structural Health monitoring technique, which utilizes electromechanical coupling properties of piezoelectric materials, has shown feasibility for use in a variety of Structural Health monitoring applications. Relying on high frequency local excitations (typically>20 kHz), this technique is very sensitive to minor changes in Structural integrity in the near field of piezoelectric sensors. Several damage sensitive features have been identified and used coupled with the impedance methods. Most of these methods are, however, limited to linearity assumptions of a structure. This paper presents the use of experimentally identified nonlinear features, combined with impedance methods, for Structural Health monitoring. Their applicability to for damage detection in various frequency ranges is demonstrated using actual impedance signals measured from a portal frame structure. The performance of the nonlinear feature is compared with those of conventional impedance methods. This paper reinforces the utility of nonlinear features in Structural Health monitoring and suggests that their varying sensitivity in different frequency ranges may be leveraged for certain applications.
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Integrated Structural Health monitoring
Proceedings of the SPIE - The International Society for Optical Engineering, 2001Co-Authors: Charles R Farrar, M L Fugate, H. Sohn, Joseph J CzarneckiAbstract:Structural Health monitoring is the implementation of a damage detection strategy for aerospace, civil and mechanical engineering infrastructure. Typical damage experienced by this infrastructure might be the development of fatigue cracks, degradation of Structural connections, or bearing wear in rotating machinery. The goal of the research effort reported herein is to develop a robust and cost-effective Structural Health monitoring solution by integrating and extending technologies from various engineering and information technology disciplines. It is the author's opinion that all Structural Health monitoring systems must be application specific. Therefore, a specific application, monitoring welded moment resisting steel frame connections in structures subjected to seismic excitation, is described along with the motivation for choosing this application. The Structural Health monitoring solution for this application will integrate Structural dynamics, wireless data acquisition, local actuation, micro-electromechanical systems (MEMS) technology, and statistical pattern recognition algorithms. The proposed system is based on an assessment of the deficiencies associated with many current Structural Health monitoring technologies including past efforts by the authors. This paper provides an example of the integrated approach to Structural Health monitoring being undertaken at Los Alamos National Laboratory and summarizes progress to date on various aspects of the technology development
H. Sohn - One of the best experts on this subject based on the ideXlab platform.
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Nonlinear feature identification of impedance-based Structural Health monitoring
Smart Structures and Materials 2004: Smart Structures and Integrated Systems, 2004Co-Authors: Amanda C. Rutherford, Gyu Hae Park, H. Sohn, Charles R FarrarAbstract:The impedance-based Structural Health monitoring technique, which utilizes electromechanical coupling properties of piezoelectric materials, has shown feasibility for use in a variety of Structural Health monitoring applications. Relying on high frequency local excitations (typically>20 kHz), this technique is very sensitive to minor changes in Structural integrity in the near field of piezoelectric sensors. Several damage sensitive features have been identified and used coupled with the impedance methods. Most of these methods are, however, limited to linearity assumptions of a structure. This paper presents the use of experimentally identified nonlinear features, combined with impedance methods, for Structural Health monitoring. Their applicability to for damage detection in various frequency ranges is demonstrated using actual impedance signals measured from a portal frame structure. The performance of the nonlinear feature is compared with those of conventional impedance methods. This paper reinforces the utility of nonlinear features in Structural Health monitoring and suggests that their varying sensitivity in different frequency ranges may be leveraged for certain applications.
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Integrated Structural Health monitoring
Proceedings of the SPIE - The International Society for Optical Engineering, 2001Co-Authors: Charles R Farrar, M L Fugate, H. Sohn, Joseph J CzarneckiAbstract:Structural Health monitoring is the implementation of a damage detection strategy for aerospace, civil and mechanical engineering infrastructure. Typical damage experienced by this infrastructure might be the development of fatigue cracks, degradation of Structural connections, or bearing wear in rotating machinery. The goal of the research effort reported herein is to develop a robust and cost-effective Structural Health monitoring solution by integrating and extending technologies from various engineering and information technology disciplines. It is the author's opinion that all Structural Health monitoring systems must be application specific. Therefore, a specific application, monitoring welded moment resisting steel frame connections in structures subjected to seismic excitation, is described along with the motivation for choosing this application. The Structural Health monitoring solution for this application will integrate Structural dynamics, wireless data acquisition, local actuation, micro-electromechanical systems (MEMS) technology, and statistical pattern recognition algorithms. The proposed system is based on an assessment of the deficiencies associated with many current Structural Health monitoring technologies including past efforts by the authors. This paper provides an example of the integrated approach to Structural Health monitoring being undertaken at Los Alamos National Laboratory and summarizes progress to date on various aspects of the technology development
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Structural Health Monitoring of Welded Connections
The First International Conference on Steel & Composite Structures, Pusan, Korea, June 14-16, 2001, 2001Co-Authors: H. Sohn, M L Fugate, Charles R Farrar, Joseph J CzarneckiAbstract:Structural Health monitoring is the implementation of a damage detection strategy for aerospace, civil and mechanical engineering infrastructure. Typical damage experienced by this infrastructure might be the development of fatigue cracks, degradation of Structural connections, or bearing wear in rotating machinery. The goal of the research effort reported herein is to develop a robust and cost-effective monitoring system for welded beam-column connections in a moment resisting frame structure. The Structural Health monitoring solution for this application will integrate Structural dynamics, wireless data acquisition, local actuation, micro-electromechanical systems (MEMS) technology, and statistical pattern recognition algorithms. This paper provides an example of the integrated approach to Structural Health monitoring being undertaken at Los Alamos National Laboratory and summarizes progress to date on various aspects of the technology development.
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Structural Health MONITORING AT LOS
13th International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2000), 2000Co-Authors: Charles R Farrar, H. Sohn, Scott W. Doebling, Los AlamosAbstract:Structural Health monitoring (SHM) is the implementation of a damage detection strategy for aerospace, civil and mechanical engineering infrastructures. Typical damage experienced by these infrastructures might be the development of fatigue cracks, degradation of Structural connections, or bearing wear in rotating machinery. Engineers at Los Alamos National Laboratory (LANL) have been actively involved in SHM research for many years. These activities have been supported by internal research funds, direct programmatic efforts, partnerships with industry, and external work for other nondefense organizations. This paper will summarize past and current SHM projects at LANL. The primary result of this work is the development of LANL’s statistical pattern recognition paradigm for Structural Health monitoring. This paradigm will be described in detail. The paper concludes discussing the future directions for this technology that are currently being explored at LANL.
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Pattern Recognition for Structural Health Monitoring
Structural Health Monitoring, 2000Co-Authors: Charles R Farrar, H. SohnAbstract:The process of implementing a damage detection strategy for engineering systems is often referred to as Structural Health monitoring. Vibration-based damage detection is a tool that is receiving considerable attention from the research community for such monitoring. Recent research has recognized that the process of vibration-based Structural Health monitoring is fundamentally one of statistical pattern recognition and this paradigm is described in detail. This process is composed of four portions: (1) Operational evaluation; (2) Data acquisition and cleansing; (3) Feature selection and data compression, and (4) Statistical model development for feature discrimination. A general discussion of each portion of the process is presented.
Michael D. Todd - One of the best experts on this subject based on the ideXlab platform.
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Sensing Network Paradigms for Structural Health Monitoring
Structural Control & Health Monitoring, 2020Co-Authors: Charles R Farrar, Gyu Hae Park, Michael D. ToddAbstract:The process of Structural Health monitoring (SHM) requires an integrated paradigm of networked sensing and actuation, data interrogation (signal processing and feature extraction), and statistical assessment (classification of damage existence, location, and/or type) that treats Structural Health assessments in a systematic way. An appropriate sensor network is always required in observing the Structural system behaviour in such a way that suitable signal processing and damage-sensitive feature extraction on the measured data can be performed efficiently. Consequently, several sensing network paradigms for SHM have emerged in the past, and this chapter is intended to provide an overview of these paradigms. Various parameters of SHM sensing systems that must be considered in its design and subsequent field deployment are also summarized.
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Active-sensing platform for Structural Health monitoring: Development and deployment
Structural Health Monitoring-an International Journal, 2016Co-Authors: Stuart G. Taylor, Gyu Hae Park, Kevin M. Farinholt, E Y Raby, Michael D. ToddAbstract:Embedded sensing for Structural Health monitoring is a rapidly expanding field, propelled by algorithmic advances in Structural Health monitoring and the ever-shrinking size and cost of electronic hardware necessary for its implementation. Although commercial systems are available to perform the relevant tasks, they are usually bulky and/or expensive because of their high degree of general utility to a wider range of applications. As a result, multiple separate devices may be required in order to obtain the same results that could be obtained with a Structural Health monitoring–specific device. This work presents the development and deployment of a versatile, Wireless Active-Sensing Platform, designed for the particular needs of embedded sensing for multi-scale Structural Health monitoring. The Wireless Active-Sensing Platform combines a conventional data acquisition ability to record voltage output (e.g. from strain or acceleration transducers) with ultrasonic guided wave-based active-sensing, and a seam...
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Active-sensing platform for Structural Health monitoring: Development and deployment
Structural Health Monitoring, 2016Co-Authors: Stuart G. Taylor, Gyu Hae Park, Kevin M. Farinholt, E Y Raby, Michael D. ToddAbstract:Embedded sensing for Structural Health monitoring is a rapidly expanding field, propelled by algorithmic advances in Structural Health monitoring and the ever-shrinking size and cost of electronic hardware necessary for its implementation. Although commercial systems are available to perform the relevant tasks, they are usually bulky and/or expensive because of their high degree of general utility to a wider range of applications. As a result, multiple separate devices may be required in order to obtain the same results that could be obtained with a Structural Health monitoring-specific device. This work presents the development and deployment of a versatile, Wireless Active-Sensing Platform, designed for the particular needs of embedded sensing for multi-scale Structural Health monitoring. The Wireless Active-Sensing Platform combines a conventional data acquisition ability to record voltage output (e.g. from strain or acceleration transducers) with ultrasonic guided wave-based active-sensing, and a seamlessly integrated impedance measurement mode, enabling impedance-based Structural Health monitoring and piezoelectric sensor diagnostics to reduce the potential for false positives in damage identification. The motivation, capabilities, and hardware design for the Wireless Active-Sensing Platform are reviewed, and three deployment examples are presented, each demonstrating an important aspect of embedded sensing for Structural Health monitoring.
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Sensing network paradigms for Structural Health monitoring
Lecture Notes in Electrical Engineering, 2011Co-Authors: Charles R Farrar, Gyu Hae Park, Michael D. ToddAbstract:The process of Structural Health monitoring (SHM) requires an integrated paradigm of networked sensing and actuation, data interrogation (signal processing and feature extraction), and statistical assessment (classification of damage existence, location, and/or type) that treats Structural Health assessments in a systematic way. An appropriate sensor network is always required in observing the Structural system behaviour in such a way that suitable signal processing and damage-sensitive feature extraction on the measured data can be performed efficiently. Consequently, several sensing network paradigms for SHM have emerged in the past, and this chapter is intended to provide an overview of these paradigms. Various parameters of SHM sensing systems that must be considered in its design and subsequent field deployment are also summarized. © 2011 Springer-Verlag Berlin Heidelberg.
Kai Yuen Wong - One of the best experts on this subject based on the ideXlab platform.
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Structural Health monitoring of cable-supported bridges in Hong Kong
Structural Health Monitoring of Civil Infrastructure Systems, 2020Co-Authors: Kai Yuen Wong, Y.q. NiAbstract:Abstract: Structural Health monitoring in bridge engineering is the tracing of the Structural conditions of the bridge based on four major categories of physical quantities, namely: environmental loads and status, operation loads, bridge features and bridge responses by reliable on-structure instrumentation system and effective evaluation tools. In the past decade, Structural Health monitoring system has been adopted to monitor and evaluate the Structural Health conditions of cable-supported bridges in Hong Kong. The Structural Health monitoring in Hong Kong is carried out by wind and Structural Health monitoring system (WASHMS). The WASHMS is devised based on modular architecture and is currently composed of six modules, namely: Module 1 – Sensory system, Module 2 – Data acquisition and transmission system, Module 3 – Data processing and control system, Module 4 – Structural Health evaluation system, Module 5 – Structural Health data management system, and Module 6 – Inspection and maintenance system. This chapter introduces the functional and operational requirements of each modular system and tabulates the details of physical quantities required for monitoring and evaluation. Graphical outputs of some typical monitoring results from WASHMS are presented for the demonstration of WASHMS operation. Examples of WASHMS applications are also quoted.
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Structural Health monitoring of cable-supported bridges in Hong Kong
Structural Health Monitoring of Civil Infrastructure Systems, 2009Co-Authors: Kai Yuen Wong, Y.q. NiAbstract:Structural Health monitoring in bridge engineering is the tracing of the Structural conditions of the bridge based on four major categories of physical quantities, namely: environmental loads and status, operation loads, bridge features and bridge responses by reliable on-structure instrumentation system and effective evaluation tools. In the past decade, Structural Health monitoring system has been adopted to monitor and evaluate the Structural Health conditions of cable-supported bridges in Hong Kong. The Structural Health monitoring in Hong Kong is carried out by wind and Structural Health monitoring system (WASHMS). The WASHMS is devised based on modular architecture and is currently composed of six modules, namely:. Module 1 - Sensory system,Module 2 - Data acquisition and transmission system,Module 3 - Data processing and control system,Module 4 - Structural Health evaluation system,Module 5 - Structural Health data management system, andModule 6 - inspection and maintenance system.This chapter introduces the functional and operational requirements of each modular system and tabulates the details of physical quantities required for monitoring and evaluation. Graphical outputs of some typical monitoring results from WASHMS are presented for the demonstration of WASHMS operation. Examples of WASHMS applications are also quoted. © 2009 Woodhead Publishing Limited All rights reserved.
