Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures

Struct Health Monit 18(2):347–375 Entezami A, Shariatmadar H (2019) Structural health monitoring by a new hybrid feature extraction and dynamic time warping methods under ambient vibration and non-stationary signals. Measurement ...

Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures

This book conducts effective research on data-driven Structural Health Monitoring (SHM), and accordingly presents many novel feature extraction methods by time series analysis and signal processing, to extract reliable damage sensitive features from vibration responses. In this regard, some limitations of time series modeling are dealt with. For decision-making, innovative distance-based novelty detection techniques are presented to detect, locate, and quantify different damage scenarios. The performance of the presented methods is demonstrated via laboratory and full-scale structures along with several comparative studies. The main target audience of the book includes scholars, graduate students working on SHM via statistical pattern recognition in terms of feature extraction and classification for damage diagnosis under environmental and operational variations; it would also be beneficial for practicing engineers whose work involves these topics.

European Workshop on Structural Health Monitoring

On the contrary, a data-based SHM strategy only uses raw vibration measurements for statistical pattern recognition [4,11–14]. ... Time series modeling is a powerful tool for feature extraction from any kind of time-domain vibration ...

European Workshop on Structural Health Monitoring

This volume gathers the latest advances, innovations, and applications in the field of structural health monitoring (SHM) and more broadly in the fields of smart materials and intelligent systems. The volume covers highly diverse topics, including signal processing, smart sensors, autonomous systems, remote sensing and support, UAV platforms for SHM, Internet of Things, Industry 4.0, and SHM for civil structures and infrastructures. The contributions, which are published after a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists. The contents of this volume reflect the outcomes of the activities of EWSHM (European Workshop on Structural Health Monitoring) in 2020.

Intelligent Sensor Networks

On the generalized distance in statistics. ... A comparison of local damage detection algorithms based on statistical processing of vibration measurements. ... Application of time series analysis for bridge monitoring.

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts.

Real Time Structural Health Monitoring of Vibrating Systems

Owing to the capability of SSA to decompose, separate and reconstruct any time series its application is as diverse as from ... In multivariate analysis the use of Mahalanobis distance (MD) as a statistical measure has found numerous ...

Real Time Structural Health Monitoring of Vibrating Systems

Targeted at researchers and practitioners in the field of science and engineering, the book provides an introduction to real time structural health monitoring. Most work to date is based on algorithms that require windowing of the accumulated data, this work presents a coherent transition from the traditional batch mode practice to a recently developed array of recursive approaches. The book mainly focuses on the theoretical development and engineering applications of algorithms that are based on first order perturbation (FOP) techniques. The development of real time algorithms aimed at identifying the structural systems and the inflicted damage, online, through theoretical approaches paves the way for an in-depth understanding of the discussed topics. It then continues to demonstrate the solution to a class of inverse dynamic problems through numerically simulated systems. Extensive theoretical derivations supported by mathematical formulations, pivoted around the simple concepts of eigenspace updates, forms the key cornerstone of the book. The output response streaming in real time from multi degree of freedom systems provide key information about the system’s health that is subsequently utilized to identify the modal parameters and the damage, in real time. Damage indicators connotative of the nature, instant and location of damage, identified in a single framework are developed in the light of real time damage case studies. Backed by a comprehensive assortment of experimental test-beds, this book includes demonstrations to emulate real life damage scenarios under controlled laboratory conditions. Applicability of the proposed recursive methods towards practical problems demonstrate their robustness as viable candidates for real time structural health monitoring.

Structural Sensing Health Monitoring and Performance Evaluation

(6.43) If p = 1, the Minkowski distance becomes the city block or Manhattan metric and measures distances along the ... of a steel frame in the laboratory by calculating the Mahalanobis distance on time series statistical features [71].

Structural Sensing  Health Monitoring  and Performance Evaluation

Structural health monitoring (SHM) uses one or more in situ sensing systems placed in or around a structure, providing real-time evaluation of its performance and ultimately preventing structural failure. Although most commonly used in civil engineering, such as in roads, bridges, and dams, SHM is now finding applications in other engineering environments, such as naval and aerospace engineering. Written by a highly respected expert in the field, Structural Sensing, Health Monitoring, and Performance Evaluation provides the first comprehensive coverage of SHM. The text begins with a review of the various types of sensors currently used in SHM, including point sensors and noncontact systems. Subsequent chapters explain the processing and interpretation of data from a number of sensors working in parallel. After considering issues related to the structures themselves, the author surveys the design of a tailor-made SHM system. He also presents a collection of case studies, many of which are drawn from his own experiences. Exploring the power of sensors, this book shows how SHM technologies can be applied to a variety of structures and systems, including multistory buildings, offshore wind energy plants, and ecological systems.

Smart Sensors for Structural Health Monitoring

Feng, D.; Feng, M.Q. Computer vision for SHM of civil infrastructure: From dynamic response measurement to damage detection—A ... [CrossRef] Omenzetter, P.; Brownjohn, J.M.W. Application of time series analysis for bridge monitoring.

Smart Sensors for Structural Health Monitoring

Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).

Structural Health Monitoring

Figure 7.2 Measured mode shape and a quadratic approximation obtained by a leastsquares fit to the measured data. The approaches to quantifying the ... As an example, a 1024point acceleration time series may be collected from a sensor.

Structural Health Monitoring

Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process in detail with further insight provided via numerical and experimental studies of laboratory test specimens and in-situ structures. This paradigm provides a comprehensive framework for developing SHM solutions. Structural Health Monitoring: A Machine Learning Perspective makes extensive use of the authors’ detailed surveys of the technical literature, the experience they have gained from teaching numerous courses on this subject, and the results of performing numerous analytical and experimental structural health monitoring studies. Considers structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm Emphasises an integrated approach to the development of structural health monitoring solutions by coupling the measurement hardware portion of the problem directly with the data interrogation algorithms Benefits from extensive use of the authors’ detailed surveys of 800 papers in the technical literature and the experience they have gained from teaching numerous short courses on this subject.

Structural Dynamics Volume 3

CONCLUDING REMARKS In this study, a time series analysis methodology is presented for damage detection using ambient ... Sohn, H., J.A. Czarnecki, and C.R. Farrar, Structural Health Monitoring Using Statistical Process Control.

Structural Dynamics  Volume 3

This the fifth volume of five from the 28th IMAC on Structural Dynamics and Renewable Energy, 2010,, brings together 146 chapters on Structural Dynamics. It presents early findings from experimental and computational investigations of on a wide range of area within Structural Dynamics, including studies such as Simulation and Validation of ODS Measurements made Using a Continuous SLDV Method on a Beam Excited by a Pseudo Random Signal, Comparison of Image Based, Laser, and Accelerometer Measurements, Modal Parameter Estimation Using Acoustic Modal Analysis, Mitigation of Vortex-induced Vibrations in Long-span Bridges, and Vibration and Acoustic Analysis of Brake Pads for Quality Control.

Topics on the Dynamics of Civil Structures Volume 1

Proceedings of the 30th IMAC, A Conference on Structural Dynamics, 2012 J.M. Caicedo, F.N. Catbas, A. Cunha, V. Racic, ... Gul M, Catbas FN (2009) Statistical pattern recognition for structural health monitoring using time series ...

Topics on the Dynamics of Civil Structures  Volume 1

Topics on the Dynamics of Civil Structures, Volume 1, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the first volume of six from the Conference, brings together 45 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Human Induced Vibrations Bridge Dynamics Operational Modal Analysis Experimental Techniques and Modeling for Civil Structures System Identification for Civil Structures Method and Technologies for Bridge Monitoring Damage Detection for Civil Structures Structural Modeling Vibration Control Method and Approaches for Civil Structures Modal Testing of Civil Structures

Structural Health Monitoring Based on Data Science Techniques

... detection in railway bridge vibration response from traffic-induced excitation, applying time-series analysis and ... The strategy consists of fusing sets of acceleration measurements to improve sensitivity and combines: (i) CWT and ...

Structural Health Monitoring Based on Data Science Techniques


Journal of Dynamic Systems Measurement and Control

Structural Health Monitoring Using Statistical Pattern Recognition Techniques This paper casts structural health ... based on time series analysis are applied to fiber optic strain gauge data obtained from two different structural ...

Journal of Dynamic Systems  Measurement  and Control


Innovation Communication and Engineering

ARMA modelled time-series classification for structural health monitoring of civil infrastructure. Mechanical Systems and Signal Processing ... Parameter estimation for multiple-input multiple-output modal analysis of large structures.

Innovation  Communication and Engineering

This volume represents the proceedings of the 2013 International Conference on Innovation, Communication and Engineering (ICICE 2013). This conference was organized by the China University of Petroleum (Huadong/East China) and the Taiwanese Institute of Knowledge Innovation, and was held in Qingdao, Shandong, P.R. China, October 26 - November 1, 2013. The conference received 653 submitted papers from 10 countries, of which 214 papers were selected by the committees to be presented at ICICE 2013. The conference provided a unified communication platform for researchers in a wide range of fields from information technology, communication science, and applied mathematics, to computer science, advanced material science, design and engineering. This volume enables interdisciplinary collaboration between science and engineering technologists in academia and industry as well as networking internationally. Consists of a book of abstracts (260 pp.) and a USB flash card with full papers (912 pp.).

Optical Sensors for Structural Health Monitoring

In Proceedings of the 26th International Conference on Very Large Data Bases, VLDB 2000, Cairo, Egypt, 10–14 September 2000. 22. Liu, L.; Li, W.; Jia, H. Method of time series similarity measurement based on dynamic time warping.

Optical Sensors for Structural Health Monitoring

The evolution and need for the preservation and maintenance of existing structures, recent or historical, has fostered research in the area of structural monitoring, translated into the development of new techniques, equipment and sensors. Early detection of damage and accurate assessment of structural safety requires monitoring systems, the data from which can be used to calibrate numerical models for structural analysis and to assess safety. Data are obtained under real-time conditions, considering a group of parameters related to structural properties, such as stresses, accelerations, deformations and displacements. The analysis of structural properties is particularly relevant when the structure is subjected to extreme events (earthquakes, wind, fire and explosions, among others) or repeated loads (road/rail/air traffic, vibrations induced by equipment and machines), since they affect the structural integrity and put the users at risk. In order to prevent the severe damage and eventual collapse of structures, and consequent human, material and economic losses, the implementation of monitoring systems becomes a valuable tool for today's society. Monitoring of structures is becoming increasingly important, not only as preventive action, but also due to actual economic and sustainability concerns, to ensure a safer and more comfortable built environment.

Robust Monitoring Diagnostic Methods and Tools for Engineered Systems

To overcome the issues from visual inspections, vibrationbased structural health monitoring (SHM) has seen substantial ... Time series analysis is used to analyze time dependent data sets to understand their statistical characteristics.

Robust Monitoring  Diagnostic Methods and Tools for Engineered Systems


Sensor Technologies for Civil Infrastructures

Volume 2: Applications in Structural Health Monitoring Jerome P. Lynch, Hoon Sohn, Ming L. Wang ... analysis include time/frequency domain representations, scatter plots, histograms, heatmaps, distance measures, and statistical measures ...

Sensor Technologies for Civil Infrastructures

Sensor Technologies for Civil Infrastructure, Volume 2: Applications in Structural Health Monitoring, Second Edition, provides an overview of sensor applications and a new section on future and emerging technologies. Part one is made up of case studies in assessing and monitoring specific structures such as bridges, towers, buildings, dams, tunnels, pipelines, and roads. The new edition also includes sensing solutions for assessing and monitoring of naval systems. Part two reviews emerging technologies for sensing and data analysis including diagnostic solutions for assessing and monitoring sensors, unmanned aerial systems, and UAV application in post-hazard event reconnaissance and site assessment. Includes case studies in assessing structures such as bridges, buildings, super-tall towers, dams, tunnels, wind turbines, railroad tracks, nuclear power plants, offshore structures, naval systems, levees, and pipelines Reviews future and emerging technologies and techniques including unmanned aerial systems, LIDAR, and ultrasonic and infrared sensing Describes latest emerging techniques in data analysis such as diagnostic solutions for assessing and monitoring sensors and big data analysis

Civil Structural Health Monitoring

PS are slightly affected by temporal and geometric decorrelation as is the case of points lying on buildings, poles, ... the same scattering mechanism: In these conditions statistical analysis can be used to reduce noise effects.

Civil Structural Health Monitoring

This volume gathers the latest advances and innovations in the field of structural health monitoring, as presented at the 8th Civil Structural Health Monitoring Workshop (CSHM-8), held on March 31–April 2, 2021. It discusses emerging challenges in civil SHM and more broadly in the fields of smart materials and intelligent systems for civil engineering applications. The contributions cover a diverse range of topics, including applications of SHM to civil structures and infrastructures, innovative sensing solutions for SHM, data-driven damage detection techniques, nonlinear systems and analysis techniques, influence of environmental and operational conditions, aging structures and infrastructures in hazardous environments, and SHM in earthquake prone regions. Selected by means of a rigorous peer-review process, they will spur novel research directions and foster future multidisciplinary collaborations.

Advances in Condition Monitoring and Structural Health Monitoring

In order to process this quantity, automatic algorithms to help analyzing time series of images have to be developed. Thus, CD algorithms have been thoroughly investigated in the recent literature [1]. In that context, statistical based ...

Advances in Condition Monitoring and Structural Health Monitoring

This book comprises the selected contributions from the 2nd World Congress on Condition Monitoring (WCCM 2019), held in Singapore in December 2019. The contents focus on digitalisation for condition monitoring with the emergence of the fourth industrial revolution (Industry 4.0) and the Industrial Internet-of-Things (IIoT). The book covers latest research findings in the areas of condition monitoring, structural health monitoring, and non-destructive testing which are relevant for many sectors including aerospace, automotive, civil, oil and gas, marine, and manufacturing industries. Different monitoring systems and non-destructive testing methods are discussed to avoid failures, increase lifespans, and reduce maintenance costs of equipment and machinery. The broad scope of the contents will make this book interesting for academics and professionals working in the areas of non-destructive evaluation and condition monitoring.

Structural Health Monitoring

The results show that KL divergence and B-distance are similar in measuring MDGMM migration distance. ... The whole method is a datadriven based probability and statistics method, with no mechanical models of damage and structure needed ...

Structural Health Monitoring

The book presents recent advances regarding the inspection and monitoring of engineering structures; including bridges, buildings, aircraft and space structures, nuclear reactors and defense platforms. Among the techniques covered are UAV photogrammetry, strain monitoring, infrared detection, acoustic emission testing, residual stress measurements, fiber optical sensing, thermographic inspection, vibration analysis, piezoelectric sensing and ultrasonic testing. Keywords: Bridges, Buildings, Aircraft Structures, Space Structures, Nuclear Reactors, Defense Platforms, UAV Photogrammetry, Strain Monitoring, Infrared Detection, Acoustic Emission Testing, Residual Stress Measurements, Fiber Optical Sensing, Thermographic Inspection, Vibration Analysis, Piezoelectric Sensing, Ultrasonic Testing, Impact Damage, Anaerobic Reactor Performance, Geomembranes, Ossointegrated Implants, Fatigue Crack Growth, Accelerometer, Nonlinear Cable Bracing, Timber Utility Poles, Steel Pipes, Loosened Bolts on Pipes, IMU-based Motion Capture, CFRP Composites, Maglev Guideway Girder, Cable-Pylon Anchorage, Deep Learning Techniques.

Integrative Oncology

More information on these measures can be obtained in Nair ... Statistical damage detection using time series analysis on a structural health monitoring benchmark problem , Proceedings of 9th International Conference on Application of ...

Integrative Oncology

Integrative Oncology explores a comprehensive, evidence-based approach to cancer care that addresses all individuals involved in the process, and can include the use of complementary and alternative medicine (CAM) therapies alongside conventional modalities such as chemotherapy, surgery, and radiation therapy. The number of integrative care programs is increasing worldwide and this book forms a foundation text for all who want to learn more about this growing field. This guide provides a thoughtful and generous perspective on integrative care, an outstanding overview of the exciting clinical opportunities these techniques can offer, and a guide to the new territories that all oncologists and CAM practitioners need to explore and understand.

Structural Health Monitoring of Large Civil Engineering Structures

Novelty detection involves the identification of any deviations in measured data, by comparing with data measured under normal ... Statistical process control provides a framework for monitoring the distribution of the features and for ...

Structural Health Monitoring of Large Civil Engineering Structures

The book will provide a critical review of key developments in the structural health monitoring technologies applied to civil engineering structures. It covers all aspects required for such monitoring in the field, including sensors and networks, data acquisition and processing, damage detection techniques and damage prognostics techniques. A number of case studies, showing how the techniques can be applied to large civil engineering structures are included.