Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Salford postgraduate annual research conference (SPARC) 2012 proceedings

These proceedings bring together a selection of papers from the 2012 Salford Postgraduate Annual Research Conference (SPARC). They reflect the breadth and diversity of research interests showcased at the conference, at which over 130 researchers from Salford, the North West and other UK universities presented their work. 21 papers are collated here from the humanities, arts, social sciences, health, engineering, environment and life sciences, built environment and business

Between Scylla and Charybdis: Environmental governance and illegibility in the American West

In The Odyssey, Odysseus and his crew must navigate the Strait of Messina between two great hazards: the six-headed monster Scylla on one side, and the whirlpool Charybdis on the other. This conceit here guides a critical engagement with scientific knowledge and state power, grounded in the positionality and practices of government agents charged with the management of controversial species and processes in the American West. Based in ethnographic and archival research on wolf-livestock conflict and public lands grazing in Central Idaho, I relate how agents with the U.S. Forest Service and Idaho Department of Fish and Game navigate conditions not of their own choosing. Sailing the “choppy seas” of complex systems and multiple-use mandates, with the “whirlpool” of cuts to capacity on one side and the “monster” of political controversy and litigation on the other, agents appear to collect less or more ambiguous information on their charges, resulting in a partial “blindness” or illegibility. Although a rational adaptation to unrealistic expectations, this ignorance is not bliss but rather symptom and source of dysfunction, limiting agents’ ability to carry out monitoring, collaboration, and effectively conduct on-the-ground management. Understanding patterns of illegibility requires that we attend both to broader contextual pressures and situated motivations. In so doing, we might account for the seeming disconnect between agencies’ stated aims and practices, complicate traditional assumptions of evidence-based scientific management and analyses of bureaucratic rationality and state power, and make sense of the apparent dysfunction around environmental governance in the American West today

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

SciTech News Volume 71, No. 2 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division 9 Aerospace Section of the Engineering Division 12 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 14 Reviews Sci-Tech Book News Reviews 16 Advertisements IEEE

Internet of Things in Water Management and Treatment

The goal of the water security IoT chapter is to present a comprehensive and integrated IoT based approach to environmental quality and monitoring by generating new knowledge and innovative approaches that focus on sustainable resource management. Mainly, this chapter focuses on IoT applications in wastewater and stormwater, and the human and environmental consequences of water contaminants and their treatment. The IoT applications using sensors for sewer and stormwater monitoring across networked landscapes, water quality assessment, treatment, and sustainable management are introduced. The studies of rate limitations in biophysical and geochemical processes that support the ecosystem services related to water quality are presented. The applications of IoT solutions based on these discoveries are also discussed

A Primer for Monitoring Water Funds

This document is intended to assist people working on Water Funds to understand their information needs and become familiar with the strengths and weaknesses of various monitoring approaches. This primer is not intended to make people monitoring experts, but rather to help them become familiar with and conversant in the major issues so they can communicate effectively with experts to design a scientifically defensible monitoring program.The document highlights the critical information needs common to Water Fund projects and summarizes issues and steps to address in developing a Water Fund monitoring program. It explains key concepts and challenges; suggests monitoring parameters and an array of sampling designs to consider as a starting-point; and provides suggestions for further reading, links to helpful resources,and an annotated bibliography of studies on the impacts that result from activities commonly implemented in Water Fund projects

Low-cost sensors technologies for monitoring sustainability and safety issues in mining activities: advances, gaps, and future directions in the digitalization for smart mining

Nowadays, monitoring aspects related to sustainability and safety in mining activities worldwide are a priority, to mitigate socio-environmental impacts, promote efficient use of water, reduce carbon footprint, use renewable energies, reduce mine waste, and minimize the risks of accidents and fatalities. In this context, the implementation of sensor technologies is an attractive alternative for the mining industry in the current digitalization context. To have a digital mine, sensors are essential and form the basis of Industry 4.0, and to allow a more accelerated, reliable, and massive digital transformation, low-cost sensor technology solutions may help to achieve these goals. This article focuses on studying the state of the art of implementing low-cost sensor technologies to monitor sustainability and safety aspects in mining activities, through the review of scientific literature. The methodology applied in this article was carried out by means of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and generating science mapping. For this, a methodological procedure of three steps was implemented: (i) Bibliometric analysis as a quantitative method, (ii) Systematic review of literature as a qualitative method, and (iii) Mixed review as a method to integrate the findings found in (i) and (ii). Finally, according to the results obtained, the main advances, gaps, and future directions in the implementation of low-cost sensor technologies for use in smart mining are exposed. Digital transformation aspects for data measurement with low-cost sensors by real-time monitoring, use of wireless network systems, artificial intelligence, machine learning, digital twins, and the Internet of Things, among other technologies of the Industry 4.0 era are discussed.The authors are indebted to the projects PID2021-126405OB-C31 and PID2021-126405OB-C32 funded by FEDER funds—A Way to Make Europe and Spanish Ministry of Economy and Competitiveness MICIN/AEI/10.13039/501100011033/. The financial support of the Research Department of the Catholic University of Temuco and the Civil Engineering Department of the University of Castilla-La Mancha is also appreciated.Peer ReviewedPostprint (published version