Model-based fault diagnosis via structural analysis of a reverse osmosis plant

Water desalination is one approach to force water scarcity. One of the processes used for desalination is reverse osmosis. Like other systems, a reverse osmosis plant is susceptible to faults. A fault can lead to a loss of efficiency, or if the fault is severe to a total breakdown. Appropriate measures can minimize the impact of faults, but this requires in time fault detection. The following thesis shows a proposal for an online fault diagnosis system of a reverse osmosis plant. For the model-based approach, a mathematical model of a reverse osmosis plant has been developed. The model contains a new approach for modeling the interaction between the high-pressure pump, the brine valve, and the membrane module. Furthermore, six faults considered for fault diagnosis have been modeled. Two of the faults are plant faults: The leakage of the feed stream and membrane fouling. The other four faults are sensor or actuator malfunctions. The fault diagnosis system is developed via structural analysis, a graph-based approach to determine a mathematical model’s overdetermined systems of equations. With the structural analysis, 73 fault-driven minimal structurally overdetermined (FMSO) sets have been determined. The results show that all six faults are detectable. However, two faults are not isolable. Five of the FMSO sets have been chosen to deduce the residuals used for online fault detection and isolation. The simulations demonstrate that the calculated residuals are appropriate to detect and isolate the faults. If one assumes that only the considered faults occur, it is possible to determine some faults’ magnitude

Leakage Assessment in Fault Attacks: A Deep Learning Perspective

Generic vulnerability assessment of cipher implementations against fault attacks (FA) is a largely unexplored research area to date. Security assessment against FA is particularly important in the context of FA countermeasures because, on several occasions, countermeasures fail to fulfil their sole purpose of preventing FA due to flawed design or implementation. In this paper, we propose a generic, simulation-based, statistical yes/no experiment for evaluating fault-assisted information leakage based on the principle of non-interference. The proposed exper- iment is oblivious to the structure of countermeasure/cipher under test and detects fault-induced leakage solely by observing the ciphertext dis- tributions. Unlike a recently proposed approach that utilizes t-test and its higher-order variants for detecting leakage at different moments of ciphertext distributions, in this work, we present a Deep Learning (DL) based leakage detection test. Our DL-based detection test is not specific to only moment-based leakages and thus can expose leakages in several cases where t-test based technique demands a prohibitively large number of ciphertexts. We also present a systematic approach to interpret the leakages from DL models. Apart from improving the leak- age detection test, we explore two generalizations of the leakage assess- ment experiment itself – one for evaluating against the Statistical ineffec- tive fault model (SIFA), and another for assessing fault-induced leakages originating from “non-cryptographic” peripheral components of a secu- rity module. Finally, we present techniques for efficiently covering the fault space of a block cipher by exploiting logic-level and cipher-level fault equivalences. The efficacy of DL-based leakage detection, as well as the proposed generalizations, has been evaluated on a rich test-suite of hardened implementations from several countermeasure classes, includ- ing open-source SIFA countermeasures and a hardware security module called Secured-Hardware-Extension (SHE)

Diagnosis, treatment, and effects of the crisis in Greece : a “Special Case” or a “Test Case”?

Syftet med detta examensarbete är att undersöka specialpedagogers/speciallärares uppfattningar om sin yrkesroll, elever de möter och det specialpedagogiska verksamhetsområdet i grundskolan. Syftet är även att studera vad begreppet en skola för alla innebär för specialpedagogerna/speciallärarna. Vår metod är kvalitativa intervjuer med sju verksamma speciallärare/specialpedagoger. Vårt resultat belyser vi utifrån en litteraturöversikt och tre perspektiv inom det specialpedagogiska området. Det som har framkommit i vår studie genom resultatet och analysen är att speciallärarna/specialpedagogerna har en mångsidig yrkesroll och att de ser en tydlig skillnad mellan deras yrkesroll och en så kallad vanlig lärarroll. Den vanligaste arbetsformen informanterna har är undervisning i liten grupp, men det förekommer också andra arbetssätt, exempelvis handledning och testarbete. Oavsett vilken utbildning våra informanter har, finns det ingen klar skillnad mellan deras arbetsuppgifter. Eleverna våra informanter möter har endera någon form av diagnos eller har skolsvårigheter av en eller flera anledningar. Elevernas syn på att de får särskilt stöd är enligt informanterna både positiv och negativ. Specialpedagogerna/speciallärarna anser att dagens skola inte är en skola för alla, med ett undantag. De uttrycker att en skola för alla innebär en skola där alla elever trivs och får ta del av skolans resurser, samt har en miljö som passar alla barn. Anledningen till att dagens skola inte är en skola för alla är att skolan inte tar vara på elevernas förmågor och att lärarna inte hinner se och hjälpa alla barn. Detta beror på att skolans resurser inte är tillräckliga. I den slutliga diskussionsdelen har vi kommit fram till att de tre specialpedagogiska perspektiven förekommer i dagens skola. Vi har också bildat oss en egen uppfattning om vad en skola för alla innebär

Enhancing fuel cell lifetime performance through effective health management

Hydrogen fuel cells, and notably the polymer electrolyte fuel cell (PEFC), present an important opportunity to reduce greenhouse gas emissions within a range of sectors of society, particularly for transportation and portable products. Despite several decades of research and development, there exist three main hurdles to full commercialisation; namely infrastructure, costs, and durability. This thesis considers the latter of these. The lifetime target for an automotive fuel cell power plant is to survive 5000 hours of usage before significant performance loss; current demonstration projects have only accomplished half of this target, often due to PEFC stack component degradation. Health management techniques have been identified as an opportunity to overcome the durability limitations. By monitoring the PEFC for faulty operation, it is hoped that control actions can be made to restore or maintain performance, and achieve the desired lifetime durability. This thesis presents fault detection and diagnosis approaches with the goal of isolating a range of component degradation modes from within the PEFC construction. Fault detection is achieved through residual analysis against an electrochemical model of healthy stack condition. An expert knowledge-based diagnostic approach is developed for fault isolation. This analysis is enabled through fuzzy logic calculations, which allows for computational reasoning against linguistic terminology and expert understanding of degradation phenomena. An experimental test bench has been utilised to test the health management processes, and demonstrate functionality. Through different steady-state and dynamic loading conditions, including a simulation of automotive application, diagnosis results can be observed for PEFC degradation cases. This research contributes to the areas of reliability analysis and health management of PEFC fuel cells. Established PEFC models have been updated to represent more accurately an application PEFC. The fuzzy logic knowledge-based diagnostic is the greatest novel contribution, with no examples of this application in the literature

A Strategic Digital Transformation for the Water Industry

This book is a compilation of the knowledge shared and generated so far in the IWA Digital Water Programme. It is an insightful collection of white papers covering best practices, linking academic and industrial studies/insights with applications to give real-world examples of digital transformation. These White Papers are designed to help utilities, water professionals and all those interested in water management and stewardship issues to better understand the opportunities of digital technologies. This book covers a plethora of topics including: Instrumentation and data generation Artificial intelligence and digital twins The digital transformation and public health Mapping the digital transformation journey into the future With these topics, the aim is to present an all-encompassing reference for practitioners to use in their day-to-day activities. Through the Digital Water Programme, the IWA leverages its worldwide member expertise to guide a new generation of water and wastewater utilities on their digital journey towards the uptake of digital technologies and their integration into water services

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Gas Turbines

This book is intended to provide valuable information for the analysis and design of various gas turbine engines for different applications. The target audience for this book is design, maintenance, materials, aerospace and mechanical engineers. The design and maintenance engineers in the gas turbine and aircraft industry will benefit immensely from the integration and system discussions in the book. The chapters are of high relevance and interest to manufacturers, researchers and academicians as well

A Strategic Digital Transformation for the Water Industry

This book is a compilation of the knowledge shared and generated so far in the IWA Digital Water Programme. It is an insightful collection of white papers covering best practices, linking academic and industrial studies/insights with applications to give real-world examples of digital transformation. These White Papers are designed to help utilities, water professionals and all those interested in water management and stewardship issues to better understand the opportunities of digital technologies. This book covers a plethora of topics including: Instrumentation and data generation Artificial intelligence and digital twins The digital transformation and public health Mapping the digital transformation journey into the future With these topics, the aim is to present an all-encompassing reference for practitioners to use in their day-to-day activities. Through the Digital Water Programme, the IWA leverages its worldwide member expertise to guide a new generation of water and wastewater utilities on their digital journey towards the uptake of digital technologies and their integration into water services