Modulating function based fault diagnosis using the parity space method

A model-based method for the detection and estimation of faults in dynamic systems is proposed. The method is based on the combination of the parity space approach and the modulating function framework for estimation. The parity space method is employed as an efficient geometric procedure determining null subspaces for annihilating unknown terms and formulating residuals. With the modulating functions technique the dynamic relation from output differentiation is reformulated as an algebraic expression. This substantially reduces the noise sensitivity of the output derivatives required. The design allows for the robust fault detection and isolation also for some nonlinear systems. The robustness of the approach is demonstrated on a nonlinear model of a four-tank process

Efecto de las condiciones de almacenamiento refrigerado sobre el estrés oxidativo en raquis de uva de mesa, cv. Red Globe

Indexación: Web of Science; ScieloTable grape (Vitis vinifera L.) quality includes the condition of both the berries and the rachis. In the present report, physiological parameters of Red Globe rachises from fully elongated inflorescences (RFEI) and from mature clusters were studied after storage at 0 or 20 °C for different durations. To understand changes in rachis physiology as a result of changes in temperature conditions and storage time, the activities of superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) were measured. In addition, hydrogen peroxide content, membrane lipoperoxidation (TBARS), total phenolic compounds and antioxidant capacity (FRAP) were assayed. TBARS was higher in mature rachises than in RFEI. This parameter remained constant throughout storage, indicating a change presumably associated with ontogeny or senescence processes. Short-term storage (096 h) increased SOD, CAT and APX activities in RFEI, while in mature rachises, no changes were observed in enzyme activities or in hydrogen peroxide content. Longer cold storage (25 or 53 days at 0 °C) of mature rachises reduced CAT activity, but SOD and APX activities did not change under these conditions. At 0 h, the FRAP and total phenolic contents of mature rachises were three and 20 times higher than in immature rachises, respectively.La calidad de uva de mesa (Vitis vinifera L.) involucra tanto la condición de bayas y el raquis. En el presente trabajo, los parámetros fisiológicos de raquis de 'Red Globe' de inflorescencias completamente elongadas (RFEI) y de racimos maduros fueron estudiados después de almacenamientos por diferentes tiempos a 0 ó 20 °C. Para entender los cambios en la fisiología del raquis debido a variaciones de temperatura y condiciones de almacenamiento, se midieron las actividades de superoxido dismutasa (SOD), catalasa (CAT), ascorbato peroxidasa (APX). Además fueron analizados el contenido de peróxido de hidrógeno, lipoperoxidación de membranas (TBARS), compuestos fenólicos totales y capacidad antioxidante (FRAP). TBARS de los raquis maduros a la cosecha fue mayor que el de inflorescencias completamente elongadas (RFEI). Este parámetro permaneció constante a través del almacenamiento, indicando cambios presuntamente asociados a ontogenia o procesos de senescencia. Almacenamiento cortos (0-96h) incrementaron la actividad de SOD, CAT y APX en RFEI, sin embargo no se observaron cambios en la actividad de estas enzimas o contenido de peróxido de hidrogeno en raquis maduros. Almacenamiento refrigerado prolongado (25 ó 30 días 0 °C) de raquis maduros redujo la actividad de CAT, pero SOD y APX no mostraron cambios bajo estas condiciones. A 0 h el contenido de FRAP y fenólicos totales de raquis maduros fueron tres y 20 veces mayores que en raquis inmaduro respectivamente.http://ref.scielo.org/m3mg4

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

Structural diagnosis for distributed systems

The recent development of technological systems implies a high complexity of behaviors for today’s systems. An answer to the increased systems’ complexity is to look at them as a multitude of heterogeneous subsystems and develop distributed techniques to control and manage them. This raises a number of problems. Firstly, as the size and number of components increase, so does the number of fault occurrences that may drive the system to undergo critical failures. Fault detection and isolation (FDI), maintenance and repair are an increasing part of the operational every day’s tasks and they impact drastically the total cost of final products. This thesis focuses on fault detection and isolation. Among the different methods to generate diagnosis tests by taking advantage of analytical redundancy, this thesis adopts the so-called parity space approach based on analytical redundancy relations (ARRs). Given a model of the system in the form of a set of differential equations, ARRs are relations that are obtained from the model by eliminating non measured variables. This can be performed in an analytical framework using elimination theory but another way of doing this is to use structural analysis. Structural analysis is based on a structural abstraction of the model that only retains a representation of which variables are involved in which equations. Despite the rusticity of the abstract model, structural analysis provides a set of powerful tools, relying on graph theory, to analyze and infer information about the system. Interestingly, it applies indifferently to linear or nonlinear systems. The goal of this thesis is to develop effective techniques based on structural analysis for diagnosis of distributed continuous systems. In this framework, the system is decomposed into a set of subsystems according to functional, geographical or privacy constraints. The thesis is organized in two parts, highlighting the redundancies that are built into the global structural model and that can be used to generate diagnosis tests starting from the redundancies existing in the subsystem’s models and formulating and solving the optimization problem linked to the choice of a subset of diagnosis tests at the subsystems level that can lead to a set of diagnosis tests achieving maximum diagnosability for the global system. The first part takes benefit of the concept of Fault-Driven Minimal Structurally Overdetermined Set (FMSO set) that is introduced in the thesis. An FMSO set determines a subset of equations of the model with minimal redundancy from which an ARR sensitive to a set of faults can be obtained. Two solutions for generating FMSOs for the global system are presented, in a decentralized framework with supervisors at each level of a hierarchy and in a totally distributed framework. These are based on the properties of the FMSO sets for the subsystems in relation to those of the global system derived in the thesis. The second part formulates the optimization problem in a heuristic search framework and proposes three solutions based on iterating an A* algorithm combined with a function able to assess whether a global FMSO set can be achieved from the selected local FMSO sets. The concepts introduced in the thesis and the results are applied to the case study of a Reverse Osmosis Desalination Plant and a Spacecraft Attitude Determination and Control System of a Low Earth-Orbit Satellite.Tesi

Soft sensor design for restricted variable sampling time

Difficult-to-obtain variables in industrial applications have led to the rise of soft sensors, which use prior system information and measurements to estimate these difficult-to-obtain variables. In real systems, the measurements that need to be estimated by a soft sensor are often infrequently measured or delayed. Sometimes, these delays and sampling time are variable in time. Though there are papers considering soft sensors in the presence of time delays and different sampling times, the variation of those parameters has not been considered when evaluating the adequacy of the soft sensors. Therefore, this paper will evaluate the impact of such variations for a data-driven soft sensor and propose modifications of the soft sensor that increase its robustness. The reliability of its estimate will be shown using the Bauer-Premaratne-Durán Theorem. Furthermore, the soft sensor will be simulated applying it to a continuous stirred tank reactor. Simulation showed that the modified soft sensor gives good estimates, whereas the traditional soft sensor gives an unstable estimate

Water network benchmarks for structural analysis algorithms in fault diagnosis

International audienceThis paper proposes a set of network benchmarks for diagnostic driven algorithms based on structural analysis. These have been made available in a public repository for use of all the DX community

Water network benchmarks for structural analysis algorithms in fault diagnosis

International audienceThis paper proposes a set of network benchmarks for diagnostic driven algorithms based on structural analysis. These have been made available in a public repository for use of all the DX community

Water network benchmarks for structural analysis algorithms in fault diagnosis

International audienceThis paper proposes a set of network benchmarks for diagnostic driven algorithms based on structural analysis. These have been made available in a public repository for use of all the DX community

Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant

Currently, the use of industrial seawater reverse osmosis desalination (ISROD) plants has increased in popularity in light of the growing global demand for freshwater. In ISROD plants, any fault in the components of their control systems can lead to a plant malfunction, and this condition can originate safety risks, energy waste, as well as affect the quality of freshwater. This paper addresses the design of a fault detection and isolation (FDI) system based on a structural analysis approach for an ISROD plant located in Lima (Peru). Structural analysis allows obtaining a plant model, which is useful to generate diagnostic tests. Here, diagnostic tests via fault-driven minimal structurally overdetermined (FMSO) sets are computed, and then, binary integer linear programming (BILP) is used to select the FMSO sets that guarantee isolation. Simulations shows that all the faults of interest (sensors and actuators faults) are detected and isolated according to the proposed design

Distributed Fault Detection and Isolation Approach for Oil Pipelines

Fault detection and isolation (FDI) in oil pipeline systems (OPS) is a very critical issue because faults in these systems such as leaks or equipment malfunctions may cause significant safety accidents and economic losses. These are the challenging factors, along with the environmental regulations for developing efficient FDI approaches for OPS. This paper proposes a model-based distributed FDI approach, which uses a structural model of the system in conjunction with algorithms to generate diagnostic tests that may be implemented in local diagnosers along the OPS. The proposed approach allows detection and isolation of faults in pipeline sections (pipeline segments), pump stations, as well as process control equipment. In this way, simulation of the obtained diagnostic tests in a benchmark application shows that all faults of interest (pipeline segment faults and sensor faults) are detected and isolated