Дисертації з теми "Industrial plant monitoring"

Em países em desenvolvimento significantes fontes de poluição do ar podem ocorrer em áreas que não possuem uma qualificada estrutura de medição dos contaminantes. Neste contexto, a simplificação dos métodos de medição de partículas no ambiente, tais como impactador portátil e a acumulação de elementos traço em cascas de árvores podem fornecer informações na determinação da área de influência da fonte emissora de poluição. Neste estudo foram combinadas medidas de acumulação dos elementos traço em cascas de árvores e de partículas finas (diâmetro aerodinâmico inferior a 2,5 m) em filtros para avaliar os possíveis efeitos sobre a saúde da população das emissões de uma indústria de xisto operando em São Mateus do Sul, PR. As análises foram realizadas pela técnica de fluorescência de raios X por dispersão de energia (EDXRF) para determinação dos elementos Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, S, Si, V e Zn nas cascas de árvores e Fe, S e Si no material particulado PM2,5. Dados de saúde da população estudada foram coletados nos prontuários médicos dos pacientes no posto de saúde local. Mapas de distribuição das concentrações dos elementos foram obtidos. Estes mapas foram utilizados para identificar hot spots de poluição, para estimar a mobilidade dos elementos Fe, S e Si presentes no ar, bem como para correlacionar as concentrações destes elementos com dados da saúde da população local. O programa geoestatístico SURFER 8.0 (Golden software Surfer) e o modelo de atenuação foram utilizados nos tratamentos de dados e os softwares STATISTIC 8.0 e SPSS 13.0 utilizados nos testes estatísticos. Os resultados obtidos indicam significante associação entre morbidade respiratória e as emissões industriais. Estes resultados mostram que as emissões da indústria de xisto afetam a saúde dos habitantes da cidade de São Mateus do Sul. Isto também foi demonstrado nas medições das concentrações dos elementos no PM2,5 e na acumulação de elementos traço nas cascas de árvores. A análise fatorial e a análise descritiva, feitas a partir das concentrações determinadas nas cascas de árvores, considerando a direção dos ventos a partir da indústria de xisto sugerem que Fe, S e Si podem ser usados como marcadores da poluição desta indústria. A combinação da caracterização espacial da poluição e dados clínicos mostrou que os efeitos adversos foram significativos (p = 0, 042, ANOVA) para a população com mais de 38 anos. A partir dos resultados obtidos, também podemos concluir que a utilização de cascas de árvores como bioindicador é uma estratégia adequada em estudos sobre impacto ambiental em regiões sem rede convencional de monitoramento da poluição atmosférica
In developing countries significant sources of air pollution may go undetected in areas that do not have qualified structure to measure air contaminants. In this context, simplified methods of measuring ambient particles, such as portable impactors and trace elements accumulate in tree barks, may provide information to identify areas influenced by source emissions. In this study, simplified methods to measure trace elements in tree barks and in fine particles in filters to evaluate the possible health effects of the emissions of a shale oil plant operating in São Mateus do Sul (Paraná, Brazil) were used. These analyses were carried out by energy dispersive X ray fluorescence spectrometry (EDXRF) to determine concentrations of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, S, Si, V and Zn in tree bark and Fe, S and Si in particulate matter PM2.5. Health data of respiratory diseases of the studied population was obtained from the patient files from the local public health center. The resulting data were evaluated obtaining element concentration distribution maps. These maps were also used to identify hot spots, to estimate element mobility of Fe, S and Si present in the air, as well as, to correlate element concentrations found with health data of the local population. The SURFER geo-statistical software (Golden software Surfer) and the attenuation model of concentration were used to treat these results. For statistical tests, STATISTICÒ 8.0 software and SPSS 13.0 was used. Results obtained indicated significant associations between respiratory morbidity and industrial emissions. Thus the emissions from the shale oil industry affect the health of inhabitants of the city of São Mateus do Sul. This was also demonstrated by measurements of element concentrations in PM2.5 and the accumulation of trace elements in tree barks. Factor analysis and the descriptive analysis (ANOVA) of element concentrations in tree barks downwind of the shale plant suggest that Fe, S and Si may be used as tracers of shale industry pollution. The combination of spatial characterization of pollution and clinical data revealed that adverse effects were significant (p = 0.042, ANOVA) for the population older than 38 years. From the results obtained it was also concluded that the use of tree bark as a bioindicator is an adequate strategy in environmental impact studies in those areas with no conventional network of air pollution monitoring

La Biorobotica è un nuovo approccio nella realizzazione di robot che unisce diverse discipline come Robotica e Scienze Naturali. Il concetto di Biorobotica è stato identificato per molti anni come ispirazione dal mondo animale. In questa tesi, questo paradigma è stato esteso per la prima volta al mondo vegetale. Le piante sono un organismo affascinante con inaspettate capacità. Sono organismi dinamici e altamente sensibili, in grado di esplorare il terreno alla ricerca di nutrienti e di valutare con precisione la loro situazione per una gestione ottimale delle risorse. L'obiettivo di questa tesi è di contribuire alla realizzazione di un robot ispirato alle piante, un plantoide. Il robot plantoide comprende sistemi di radici e rami e deve essere in grado di monitorare l'ambiente sia in aria sia nel sottosuolo. Questi robot ispirati alle piante saranno utilizzati per applicazioni specifiche, come il monitoraggio in situ di parametri chimici, la ricerca di acqua in agricoltura, l'ancoraggio e per la comprensione scientifica delle capacità e comportamenti delle piante stesse mediante la costruzione di modelli fisici. In questa tesi sono stati affrontati diversi aspetti di questa innovativa piattaforma robotica: prima di tutto, lo studio delle piante, le caratteristiche e le tecnologie che consentono di progettare e sviluppare il sistema robotico. Il sistema proposto può essere facilmente suddiviso in due sezioni principali, la parte aerea e la parte radicale (che sta nel sottosuolo). Per la parte che si trova nel sottosuolo, l'attività è stata incentrata sulla realizzazione di un sistema meccatronico miniaturizzato che imita il comportamento dell’apice radicale della pianta. Le piante mostrano una peculiare direzione crescita in risposta a stimoli esterni, come la luce (phototropism), la gravità (gravitropism), il tatto (thigmotropism) o il gradiente di umidità (hydrotropism). I tropismsi spesso interagiscono tra loro, e la crescita finale della pianta è influenzata da tali interazioni. Al fine di imitare le potenti prestazioni del sistema radicale delle piante, un nuovo attuatore è stato proposto. Questo attuatore è basato sul principio osmotico (attuatore osmotico) e, diversamente dagli attuatori allo stato dell’arte basati sul principio osmotico, è stato progettato in modo da avere una reazione reversibile. Questo attuatore permette di eseguire l'allungamento e il direzionamento dell’ apice radicale, generando elevate forze con un basso consumo di energia (con movimenti nella scala temporale della pianta). Studi teorici su questo attuatore mostrano interessanti prestazioni in termini di pressione di attuazione (superiore a 20 atm), con potenza nell'ordine di alcuni mW e con tempi di attuazione nell’ordine delle ore. L’apice radicale robotico è stato progettato per essere dotato di sensori (gravità e umidità) per imitare le capacità di analisi delle piante, e con l’attuatore osmotico per guidare la crescita nella direzione corretta. Un microcontrollore integrato controlla il comportamento e il direzionamento sulla base delle informazioni provenienti dai sensori. Riguardo la parte aerea, l'attività in questa tesi è stata incentrata sulla realizzazione di una sorta di modulo di monitoraggio ambientale, al fine di imitare l'elevata capacità sensoristica delle piante. Questa parte è stata progettata e realizzata in un modo più tradizionale, senza tentare di imitare completamente il comportamento delle piante, ma prendendo ispirazione dalle caratteristiche fondamentali (recupero dell’energia, ampia capacità di monitoraggio e comunicazione). Al fine di integrare una vasta quantità di sensori, è stata sviluppata un’innovativa interfaccia che garantisce il condizionamento di sensori, con capacità plug-and-play e basso consumo energetico. Diversi aspetti del plantoid non sono ancora stati affrontati e saranno parte dei lavori futuri. In particolare, il meccanismo di crescita delle radici (alcune possibili soluzioni sono state proposte e spiegate in questa tesi) e l'integrazione di sensori chimici nell’apice radicale.
Biorobotics is a novel approach in the realization of robot that merges different disciplines as Robotic and Natural Science. The concept of biorobotics has been identified for many years as inspiration from the animal world. In this thesis this paradigm has been extended for the first time to the plant world. Plants are an amazing organism with unexpected capabilities. They are dynamic and highly sensitive organisms, actively and competitively foraging for limited resources both above and below ground, and they are also organisms which accurately compute their circumstances, use sophisticated cost–benefit analysis, and take defined actions to mitigate and control diverse environmental insults. The objective of this thesis is to contribute to the realization of a robot inspired to plants, a plantoid. The plantoid robot includes root and shoot systems and should be able to explore and monitoring the environment both in the air and underground. These plant-inspired robots will be used for specific applications, such as in situ monitoring analysis and chemical detections, water searching in agriculture, anchoring capabilities and for scientific understanding of the plant capabilities/behaviours themselves by building a physical models. The scientific work performed in this thesis addressed different aspects of this innovative robotic platform development: first of all, the study of the plants‟ characteristics and the enabling technologies in order to design and to develop the overall plantoid system. The proposed system can be easily sub-divided in two major sections, the aerial part and the subsoil part. About the subsoil part, the activity focused on the realization of a miniaturized mechatronic system that imitates the behaviour of the plant radical apex. Plants show a peculiar directional growth in response to external stimulations, such as light (phototropism), gravity (gravitropism), touch (thigmotropism) or water/humidity gradient (hydrotropism). Tropisms frequently interact between and among each other, and the final grown form of the plant is influenced by such interactions. In order to imitate the powerful performances of the plant root system, a novel actuator has been proposed. This actuator is based on the osmotic principle (osmotic actuator) and, differently by the state-of-the-art actuators based on the osmotic principle, it has been designed in order to have a reversible reaction. This actuator permits to perform the elongation and the typical steering capabilities of the root apex, generating high forces with low power consumption (in the time scale of the plant). Theoretical studies on this actuator show interesting performances in terms of actuation pressure (more than 20 atm) with power in the order of some mW and with actuation in the hours scale time. The robotic root apex was designed to be equipped with sensors (gravity and moisture) to imitate the plants sensing characteristics, and with the novel osmotic actuator to drive the growth in the correct direction. An embedded microcontroller implements the basic root behaviour on the basis of the information coming from the sensors. About the aerial part the activity in this thesis was focused on the realization of a sort of environmental monitoring module in order to imitate the high sensing capabilities of the plants. This part has been designed and realized in a more traditional way, without attempt to imitate completely the plant behaviour but taking inspiration from the fundamental characteristics (energy scavenging, wide sensing capabilities and communication). In order to integrate a wide amount of sensors an innovative interface board that guarantees the conditioning of the sensor, with plug-and-play capabilities and low power consumption, was developed. Several aspects of the plantoid system are not faced yet and they will be part of the future works. In particular, the growing mechanism of the roots (some possible solutions are proposed and explained in this thesis) and the integration of chemical sensors in the root apex.

L'objectif principal de cette thèse est de développer un algorithme dynamique de partitionnement de données (classification non supervisée ou " clustering " en anglais) qui ne se limite pas à des concepts statiques et qui peut gérer des distributions qui évoluent au fil du temps. Cet algorithme peut être utilisé dans les systèmes de surveillance du processus, mais son application ne se limite pas à ceux-ci. Les contributions de cette thèse peuvent être présentées en trois groupes: 1. Contributions au partitionnement dynamique de données en utilisant : un algorithme de partitionnement dynamique basé à la fois sur la distance et la densité des échantillons est présenté. Cet algorithme ne fait aucune hypothèse sur la linéarité ni la convexité des groupes qu'il analyse. Ces clusters, qui peuvent avoir des densités différentes, peuvent également se chevaucher. L'algorithme développé fonctionne en ligne et fusionne les étapes d'apprentissage et de reconnaissance, ce qui permet de détecter et de caractériser de nouveaux comportements en continu tout en reconnaissant l'état courant du système. 2. Contributions à l'extraction de caractéristiques : une nouvelle approche permettant d'extraire des caractéristiques dynamiques est présentée. Cette approche, basée sur une approximation polynomiale par morceaux, permet de représenter des comportements dynamiques sans perdre les informations relatives à la magnitude et en réduisant simultanément la sensibilité de l'algorithme au bruit dans les signaux analysés. 3. Contributions à la modélisation de systèmes à événements discrets évolutifs a partir des résultats du clustering : les résultats de l'algorithme de partitionnement sont utilisés comme base pour l'élaboration d'un modèle à événements discrets du processus. Ce modèle adaptatif offre une représentation du comportement du processus de haut niveau sous la forme d'un automate dont les états représentent les états du processus appris par le partitionnement jusqu'à l'instant courant et les transitions expriment l'atteignabilité des états
The main objective of this thesis is to propose a dynamic clustering algorithm that can handle not only dynamic data but also evolving distributions. This algorithm is particularly fitted for the monitoring of processes generating massive data streams, but its application is not limited to this domain. The main contributions of this thesis are: 1. Contribution to dynamic clustering by the proposal of an approach that uses distance- and density-based analyses to cluster non-linear, non-convex, overlapped data distributions with varied densities. This algorithm, that works in an online fashion, fusions the learning and lassification stages allowing to continuously detect and characterize new concepts and at the same time classifying the input samples, i.e. which means recognizing the current state of the system in a supervision application. 2. Contribution to feature extraction by the proposal of a novel approach to extract dynamic features. This approach ,based on piece-polynomial approximation, allows to represent dynamic behaviors without losing magnitude related information and to reduce at the same time the algorithm sensitivity to noise corrupting the signals. 3. Contribution to automatic discrete event modeling for evolving systems by exploiting informations brought by the clustering. The generated model is presented as a timed automaton that provides a high-level representation of the behavior of the process. The latter is adaptive in the sense that its construction is elaborated following the discovery of new concepts by the clustering algorithm

Magíster en Minería. Ingeniero Civil de Minas
El diseño de taludes es una tarea crítica en proyectos de minería a cielo abierto. Generalmente, planificadores y diseñadores buscan operar en paredes tan empinadas como sea posible para optimizar la cantidad de mineral extraído y reducir el lastre. Sin embargo, esto conlleva una disminución en la estabilidad del talud. De este modo, se requiere una gestión adecuada del talud para permitir a los planificadores y operadores realizar su trabajo con seguridad. Una de las principales variables que debe ser manejada adecuadamente en minas a cielo abierto es la presión de poros que se genera detrás de los taludes ya que esta presión disminuye la resistencia al corte del suelo. Para controlar la influencia de la presión de poros se han desarrollado distintos tipos de instrumentos para monitorear presión de agua en minas y usar los datos obtenidos como input en la toma de decisiones. Entre los instrumentos desarrollados para monitorear presión de agua subterránea están los piezómetros, que se han convertido en tecnologías establecidas en proyectos civiles y mineros. Existen distintos tipos de piezómetros y entre ellos la tecnología más aceptada para realizar monitoreo de agua en minas es la de Vibrating Wire Piezometer (VWP). En esta tesis se desarrollaron lineamientos para seleccionar instrumentación basada en las características de una mina. Utilizando estos lineamientos se seleccionaros dos tecnologías para ser comparadas, los VWP y los Networked Smart Markers (NSM). Esta comparación involucra el desarrollo de un proyecto minero teórico que incluye empinar una pared potencialmente inestable de la mina como contexto para el uso de los instrumentos. Posteriormente, se desarrollaron lineamientos para integrar un programa de monitoreo al plan minero. Para comparar dichas tecnologías, se proponen dos programas de monitoreo equivalentes y se consideran los costos de los equipos para ser instalados en los años 3 y 13 del plan minero. Un análisis de pits anidados reveló que el VAN del proyecto aumenta a medida que la pared se empina, de este modo, el parámetro de control en la comparación es cuál programa es más barato al tomar en cuenta el ingreso extra y una tasa de descuento del 8% para calcular el VAN. Los resultados de esta comparación mostraron que el uso de VWP es más barato que el uso de NSM (600,015.5[US$] versus 766,142.5[US$]). Sin embargo, esta diferencia en costo es pequeña considerando la escala del proyecto (0.39% de la inversión), además empinar la pared generó 42,420,000[US$] extra al VAN original del proyecto, lo que hace que ambas alternativas sean factibles para llevar a cabo el monitoreo propuesto. Los NSM sin embargo poseen una ventaja para realizar mediciones multipunto ya que permiten un mayor número de puntos de muestreo en un mismo pozo.
Slope design is one of the most critical tasks in open pit mine projects. Generally, mine planners and slope designers aim to operate on walls as steep as possible to optimize the amount of ore retrieved from the mine while reducing the extracted waste. However, this approach also involves a reduction in overall slope stability. Consequently, a proper management of slope stability is required to assist mine planners and operators to perform their work safely. One of the main variables that need to be properly managed in open pit mines is the pore water pressure generated behind the slopes, as this pressure decreases the ground s shear strength. To manage the influence of pore water pressure, several geotechnical instruments have been developed over the years to monitor pore water pressure and to use the data to make proper decisions. Piezometers are devices developed to monitor groundwater pressure that have become established technologies to measure pore water pressure in civil and mining projects. There are different types of piezometers with varying characteristics. The most accepted sensing technology for pore pressure monitoring in mines is the Vibrating Wire Piezometers (VWP). This thesis developed guidelines for the selection of instrumentation given the characteristics of a mine site. Using those guidelines, Vibrating Wire Piezometers and the emergent technology of Networked Smart Markers (NSM) were selected to be compared. For this comparison, a theoretical mine project, that included the steepening of a potentially unstable wall, was developed as context for instrumentation use. Subsequently, guidelines for the integration of a pore water pressure monitoring program into the mine plan were developed. To compare the selected technologies, two equivalent monitoring programs were proposed considering the current installation costs of the devices and installations in years 3 and 13 of the mine life. A nested pit analysis revealed that the NPV of the project increases when the wall gets steeper, therefore, the parameter of interest is which program is less expensive compared to the extra income, considering a discount rate of 8% to calculate the NPV of the project. The results of this comparison showed that the use of Vibrating Wire Piezometers was less expensive than the NSMs (600,015.5[US$] against 766,142.5[US$]). However, this difference in cost is small in terms of the scale of this project (0.39% of the investment) and the steepening of the wall generated 42,420,000[US$] extra to the NPV of the original project, thus, making both alternatives feasible to perform the proposed monitoring. NSMs are, however, more suitable to perform multi-point readings as they allow a higher number of measurement points in a single borehole.

A crescente demanda pela melhoria operacional dos processos aliada ao desenvolvimento da tecnologia da informação tornam a utilização de controladores preditivos baseados em modelos (MPC) uma prática comum na indústria. Estes controladores estimam, a partir dos dados de planta e de um modelo do processo, uma sequência de ações de controle que levam as variáveis ao valor desejado de forma otimizada. Dessa forma, dentre os parâmetros de configuração de um MPC, a baixa qualidade do modelo é, indiscutivelmente, a mais importante fonte de degradação de seu desempenho. Este trabalho propõe uma série de metodologias para a avaliação da qualidade do modelo do controlador preditivo, as quais consideram sua velocidade em malha fechada. Tais metodologias são baseadas na filtragem dos erros de simulação a partir função nominal de sensibilidade, e possuem a capacidade de informar o impacto dos problemas de modelagem no desempenho do sistema, além de localizar as variáveis controladas que estão com tais problemas e se os mesmos são provenientes de uma discrepância no modelo ou de um distúrbio não medido. As técnicas ainda possuem a vantagem de serem independentes do setpoint, o que as torna flexível de também serem utilizadas em controladores nos quais as variáveis são controladas por faixas. A abordagem proposta foi testada em dois estudos de caso simulados, sendo eles: a Fracionadora de Óleo Pesado da Shell e a Planta de Quatro tanques Cilíndricos. As técnicas também foram avaliadas em dados de processo da Unidade de Coqueamento Retardado de uma refinaria. Os resultados indicam que as mesmas apresentam resultados coerentes, corroborando seu elevado potencial de aplicação industrial.
The growing demand for operational improvement and the development of information technology make the use of model predictive controllers (MPCs) a common practice in industry. This kind of controller uses past plant data and a process model to estimate a sequence of control actions to lead the variables to a desired value following an optimal policy. Thus, the model quality is the most important source of MPC performance degradation. This work proposes a series of methods to investigate the controller model quality taking into account its closed loop performance. The methods are based on filtering the simulation errors using the nominal sensitivity function. They are capable detect the impact of modeling problems in the controller performance, and also to locate the controlled variables that have such problems and if it is caused by a model-plant mismatch or unmeasured disturbance. The techniques have the advantage to be setpoint independent, making them flexible to be also used in MPCs with controlled variables working by range. The proposed approach was tested in two simulated case studies The Shell Heavy Oil Fractionator Process and The Quadruple-tanks Process. The methods are also evaluated in process data of the Delayed Coking Unit of a Brazilian refinery. Results indicate that the method is technically coherent and has high potential of industrial application.

Resumo: Na indústria moderna, a precisão e o custo são fundamentais para a qualidade do produto e competitividade no mercado. Desenvolver sistemas mais velozes, dinâmicos e autoajustáveis aplicando técnicas de controle é um objetivo dos pesquisadores de todas as áreas da engenharia. A retificação de materiais é um sistema complexo que possui muitas variáveis relacionadas, principalmente por possuir múltiplas arestas de corte associado a altas velocidades e potências de retificação. Para aumentar o domínio sobre o processo, sinais de emissão acústica e de potência de acionamento do rebolo têm sido monitorados em várias pesquisas. Nesse trabalho foram realizadas experiências utilizando a retificação plana tangencial com o aço ABNT 1020 e rebolo de óxido de alumínio, onde foi determinado a ocorrência e o início da queima através da variação da profundidade de corte, tendo-se o cuidado de manter os outros parâmetros constantes, inclusive a superfície de corte do rebolo através da operação de dressagem. Os sinais de emissão acústica e de potência elétrica foram adquiridos durante uma passada do rebolo sobre a peça, numa taxa de 2.5 milhões de amostras por segundo, e pro cessados através de um ferramental matemático, onde foram propostos outros parâmetros, para a análise da ocorrência da queima. Observou-se também a detecção do início da queima, onde o parâmetro proposto VARPO obteve bons resultados. Paralelamente foi realizado um estudo sobre os microcontroladores, onde foram inseridos os cálculos de detecção da queima do processo de retificação num PIC18F452, mostrando a viabilidade de um monitoramento.
Abstract: In modern industry, the accuracy and cost are extremely important to the quality of product and market competition. The development of faster dynamic and robust systems by applying control techniques is the goal of researchers of all engineering areas. The grinding process is a complex system which contains many related variables mainly because its multiple cutting edges associated with high speed and power. In order to improve the knowledge on the process, acoustic emission and power signals have been monitored in several research investigations. In this work, surface grinding tests with ABNT 1020 steel and aluminum oxide grinding wheel were carried out in which the burning occurrence as well as the onset of it were studied. This was done by varying the depth of cut and maintaining the other grinding parameters constant, including the grinding wheel surface through the dressing operation. Acoustic emission and electrical power signals were acquired during a single grinding pass of the grinding wheel over the work-piece at 2.5 million of samples per second rate. The signals were digitally processed through many statistic algorithms among which new parameters for burn detection have been proposed. Also, the onset of burning occurrence was observed and remarkably detected for the proposed parameter dubbed VARPO. In addition, a study on microcontrollers was performed, and the implementation of the algorithms previously mentioned were carried out into the microcontroller PIC18F452, showing the monitoring feasibility.
Orientador: Paulo Roberto de Aguiar
Coorientador: Eduardo Carlos Bianchi
Banca: Paulo José Amaral Serni
Banca: Leonardo Roberto da Silva
Mestre

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Na indústria moderna, a precisão e o custo são fundamentais para a qualidade do produto e competitividade no mercado. Desenvolver sistemas mais velozes, dinâmicos e autoajustáveis aplicando técnicas de controle é um objetivo dos pesquisadores de todas as áreas da engenharia. A retificação de materiais é um sistema complexo que possui muitas variáveis relacionadas, principalmente por possuir múltiplas arestas de corte associado a altas velocidades e potências de retificação. Para aumentar o domínio sobre o processo, sinais de emissão acústica e de potência de acionamento do rebolo têm sido monitorados em várias pesquisas. Nesse trabalho foram realizadas experiências utilizando a retificação plana tangencial com o aço ABNT 1020 e rebolo de óxido de alumínio, onde foi determinado a ocorrência e o início da queima através da variação da profundidade de corte, tendo-se o cuidado de manter os outros parâmetros constantes, inclusive a superfície de corte do rebolo através da operação de dressagem. Os sinais de emissão acústica e de potência elétrica foram adquiridos durante uma passada do rebolo sobre a peça, numa taxa de 2.5 milhões de amostras por segundo, e pro cessados através de um ferramental matemático, onde foram propostos outros parâmetros, para a análise da ocorrência da queima. Observou-se também a detecção do início da queima, onde o parâmetro proposto VARPO obteve bons resultados. Paralelamente foi realizado um estudo sobre os microcontroladores, onde foram inseridos os cálculos de detecção da queima do processo de retificação num PIC18F452, mostrando a viabilidade de um monitoramento.
In modern industry, the accuracy and cost are extremely important to the quality of product and market competition. The development of faster dynamic and robust systems by applying control techniques is the goal of researchers of all engineering areas. The grinding process is a complex system which contains many related variables mainly because its multiple cutting edges associated with high speed and power. In order to improve the knowledge on the process, acoustic emission and power signals have been monitored in several research investigations. In this work, surface grinding tests with ABNT 1020 steel and aluminum oxide grinding wheel were carried out in which the burning occurrence as well as the onset of it were studied. This was done by varying the depth of cut and maintaining the other grinding parameters constant, including the grinding wheel surface through the dressing operation. Acoustic emission and electrical power signals were acquired during a single grinding pass of the grinding wheel over the work-piece at 2.5 million of samples per second rate. The signals were digitally processed through many statistic algorithms among which new parameters for burn detection have been proposed. Also, the onset of burning occurrence was observed and remarkably detected for the proposed parameter dubbed VARPO. In addition, a study on microcontrollers was performed, and the implementation of the algorithms previously mentioned were carried out into the microcontroller PIC18F452, showing the monitoring feasibility.

Ensuring reliability and robustness of operation is one of the main concerns in industrial anufacturing processes , dueto the ever-increasing demand for improvements over the cost and quality ofthe processes outcome. In this regard , a deviation from the nominal operating behaviours implies a divergence from the optimal condition specification, anda misalignment from the nominal product quality, causing a critica! loss of potential earnings . lndeed, since a decade ago, the industrial sector has been carried out a significant effort
Asegurar la fiabilidad y la robustez es uno de los principales objetivos en la monitorización de los procesos industriales, ya que estos cada vez se encuentran sometidos a demandas de producción más elevadas a la vez que se deben bajar costes de fabricación manteniendo la calidad del producto final. En este sentido, una desviación de la operación del proceso implica una divergencia de los parámetros óptimos preestablecidos, lo que conlleva a una desviación respecto la calidad nominal del producto final, causando así un rechazo de dicho producto y una perdida en costes para la empresa. De hecho, tanto es así, que desde hace más de una década el sector industrial ha dedicado un esfuerzo considerable a la implantación de metodologías de monitorización inteligente. Dichos métodos son capaces extraer información respecto a la condición de las diferentes maquinarias y procesos involucrados en el proceso de fabricación. No obstante, esta información extraída corresponde al estado actual del proceso. Por lo que obtener información respecto a la condición futura de dicho proceso representa una mejora significativa para poder ganar tiempo de respuesta para la detección y corrección de desviaciones en la operación de dicho proceso. Por lo tanto, la combinación del conocimiento futuro del comportamiento del proceso con la consecuente evaluación de la condición del mismo, es un objetivo a cumplir para la definición de las nuevas generaciones de sistemas de monitorización de procesos industriales. En este sentido, la presente tesis tiene como objetivo la propuesta de metodologías para evaluar la condición, actual y futura, de procesos industriales. Dicha metodología debe estimar la condición de forma fiable y con una alta resolución. Por lo tanto, en esta tesis se pretende extraer la información de la condición futura a partir de un modelado, basado en series temporales, de las señales críticas del proceso, para después, en base a enfoques no lineales de preservación de la topología, fusionar dichas señales proyectadas a futuro para conocer la condición. El rendimiento y la bondad de las metodologías propuestas en la tesis han sido validadas mediante su aplicación en un proceso industrial real, concretamente, con datos de una planta de fabricación de alambrón de cobre.

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Tese (Doutoramento)
IPEN/T
Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP

Fontes de poluição atmosférica têm aumentado em países em desenvolvimento, tornando extremamente difícil o acesso aos efeitos da poluição atmosférica na saúde pública. Bioensaios com plantas têm sido extensivamente utilizados para monitorar a poluição atmosférica em áreas desprovidas de sistemas de monitoramento da qualidade do ar convencionais pela sua simplicidade, baixo custo e alta sensibilidade. O presente estudo visa caracterizar a distribuição espacial da concentração de poluentes no entorno de indústrias através de evidências de toxicidade celular e acúmulo foliar utilizando planta local (Catharanthus roseus (L.) G. Don). O abortamento polínico foi quantificado em microscópio óptico (400x). O acúmulo de elementos traços foi avaliado em EDXRF (Energy Dispersive X-Ray Fluorescence). Os resultados obtidos para a área de estudo 1 mostram que a taxa de abortamento polínico é maior quanto mais próximo da indústria (p=0,047). Para o acúmulo foliar, foram encontrados os elementos S, Fe e Na que se relacionam com produtos de combustão; processo industrial; e aerossol marinho. Para a área de estudo 2, a taxa de abortamento polínico aumenta com a proximidade da área de alto tráfego veicular assim como a concentração dos elementos Al, Cu, S e Zn nas folhas pela Análise de Regressão Linear. Este estudo mostra que as áreas no entorno de fontes emissoras de poluição têm alta concentração de elementos - traço e dano celular o que indica riscos à saúde da população local. Nossos resultados reforçam que o uso de metodologias alternativas e simples como testes de abortamento polínico e bioacumulação em folhas são apropriados para caracterizar gradientes de concentração em áreas desprovidas de sistema de monitoramento da qualidade do ar, em escalas maiores do que as já estudadas. A combinação de técnicas de biomonitoramento e geoprocessamento pode ser utilizada para monitoramento ambiental em áreas com tecnologia limitada
Developing countries are experiencing increases in air pollution sources, making assessment of air pollution impact on human health extremely difficult. Plant bioassays have been widely employed to monitor air pollution in areas devoid of conventional air pollution monitoring systems because of their simplicity, low cost and high sensitivity. The aim of this study was to determine the area of influence of industries using local flora (Catharanthus roseus (L.) G. Don). Abortive pollen tests and the accumulation of toxic elements in leaves were used to detect possible risks to health of the local population. Abortive grains were evaluated through the use of a microscope under 400-fold magnification. The trace elements accumulation was evaluated by using EDXRF (Energy Dispersive X-Ray Fluorescence). Results for study site 1 shown that the closer the distance from the industry, the higher the pollen abortion rate (p=0,047). For bioaccumulation test, S, Fe and Na were associated to combustion of fossil fuels, industrial process and marine aerosol. For study site 2, the closer the distance from the major source of traffic, the higher the pollen abortion rate. The same behavior was observed for Al, Cu, S and Zn concentrations in Linear Regression Analyses. The distribution of element concentrations was elaborated in maps with the obtained results. This work showed that the areas surrounding the emission sources had a higher concentration of toxic elements, leading to greater biological damage, which indicates health risks to the local population. Our results reinforce that the use of alternative and simple methods such as pollen abortion rates and bioaccumulation in leaves are appropriate for characterizing air quality gradients in areas devoid of conventional air pollution monitoring systems, even at greater scales than have been tested before. The association of this technique and geographic information system can be used for environmental screening in areas with limited technology

碩士
朝陽科技大學
環境工程與管理系碩士班
95
Grey model (GM) and artificial neural network (ANN) were employed to predict suspended solids (SSeff), chemical oxygen demand (CODeff) and pHeff in the effluent from conventional activated process of an industrial wastewater treatment plant using simple online monitoring parameters (pH in the equalization pond effluent; pH, temperature, and dissolved oxygen in the aeration tank). The results indicated that the minimum mean absolute percentage errors of 20.79 %, 6.09 % and 0.71 % for SSeff, CODeff and pHeff could be achieved using different types of GMs. GM only required a small amount of data (at least 4 data) and the prediction results were even better than those of ANN. According to the results, the online monitoring parameters could be applied on the prediction of effluent quality. It also revealed that GM could predict the industrial effluent variation as its effluent data was insufficient.

Power conservation has become a high priority to South African industries due to recent environmental assessments and electricity price hikes. This research aims to demonstrate to Industry the many simple and cost effective ways to increase their industrial efficiency with simple modifications, as well as making them more aware of common assembly errors that significantly increase power consumption. This has been accomplished with the design, construction and testing of a test rig capable of producing the desired test results which simulate Industry usage. A test rig was required to test certain energy efficient equipment. This dissertation contains an explanation of the tests required, as well as how they were conducted. These test requirements directed the design outcomes of the test rig. Due to the variety of equipment to be tested, and the accuracy required, the test rig had to be fully adjustable. The design process is explained in this dissertation, along with relevant theory with regard to the testing procedures. The testing procedures were designed to be as accurate as possible. The setup equipment and procedure is briefly explained to ensure an understanding of the capabilities of the test rig. This dissertation contains the results obtained from testing a variety of couplings, belts and motors under different conditions. The results obtained show the difference between the efficiency of a standard motor and that of a high efficiency motor. The efficiency comparison of the Poly V TM, Poly Chain® and SPB V-belts showed very distinct advantages and disadvantages of each belt. The coupling testing was conducted under conditions of misalignment, and resulted in distinct differences in the efficiencies of each coupling at different degrees of misalignments. The couplings tested were the Fenaflex®, the Quick-Flex®, and the Fenagrid® coupling. All results obtained were analyzed and discussed in the relevant sections. The results obtained showed that the high efficiency motor is significantly more efficient than the standard motor at full load, although at low loading, the motor efficiencies were very similar. The coupling tests showed the negative effects misalignment has on the efficiency of the Quick-Flex® and Fenagrid® coupling as well as the capability of the Fenaflex® coupling to withstand the effects of large misalignments without significant efficiency loss. v The belt testing revealed the advantages and disadvantages of each type of belt used. This showed that although the synchronous belt did not lose efficiency with decreased tension, it became unstable, and was difficult to keep on the pulley if not aligned correctly. The V-belts can handle low tension well. Prolonged use of the belts can cause them to stretch, lowering the tension into a “danger zone” that will cause the belts to slip. This slip can damage the belt and pulley. At the lower tension of the V-belt, although the efficiency increases slightly, the vibration of the slack side of the belt is significant, and can be dangerous as the belt could jump off the pulley. The Poly V TM belt has some of the advantages of the V-belt, except that it is unable to maintain its friction at low tension, as the belt width prevents it from being wedged into the grooves like the V-belt. The fluid coupling tests showed that the shock loading on a high inertia system can be significantly reduced with the aid of a fluid coupling. The reduced shock loading can reduce energy consumption, and increase the life of electric motors and the equipment that they drive by preventing excessive overloading.
Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2011.

博士
國立臺灣大學
職業醫學與工業衛生研究所
101
Science industrial park in Taiwan accommodates high-tech industries, including semiconductor and opticelectronic manufacturing industries. Emitted air pollutants from these industries resulted in special and complicated scenario of ambient air quality. This study was conducted in a semiconductor manufacturing plant to explore the monitoring strategy and to evaluate its efficacy by examining chemical composition, emissions, and charactistics of the emitted air pollutants around indoor and ourdoor environments. There were two parts in this study: (1) to explore the strategy of continuous monitoring and its impact in the investigation of odor episode, emission sources and distribution of air pollutants by examining the occurrence and accumulation of air pollutants in a semiconductor plant using Fourier transform infrared (FTIR) spectrometers, (2) to explore a monitoring strategy for affecting factors of a general indoor environment by examining the relationship of indoor water-damaged environment with student absences rate of an affiliated kindergarten of a seminconductor plant, located in an envelop building equipped with mechanical ventilation. The first part included two studies. Study I employed three Fourier transform infrared (FTIR) spectrometers to synchronously characterize air pollutants and emission sources in a semiconductor plant. Based on the 736 consecutive five-minute monitoring records in three consecutive days, some detectable chemicals, inclduding ammonia, ozone, butyl acetate, and propylene glycol monomethyl ether acetate (PGMEA), presented with concentrations exceeding their respective odor thresholds and resulted in an combined total odor rate of 43.9%. Results of logistic regression analysis indicated that the FTIR’s monitoring showed higher efficacy as south wind prevailing with odds ratio of 3.8 (95% confidence interval (CI): 2.9-5.0) as compared to other wind directions. Additionally, distance between the monitoring path and the emission source is another factor influencing the efficacy of FTIR performance. The closest monitoring path, 30 m from the emission source, in the down-wind direction of emission source showed the highest efficacy in detecting odorous samples with OR of 5.1 (95% CI: 3.6-7.2). These findings illustrated the importance of meteorological factors and location of monitoring path on the FTIR monitoring performance. Such monitoring performance might also be counfounded by the properties of the emission sources. For instance, among the high-tech industries, pollutants were usually ejected from multi-stacks in a plant along with different ejection flow velocities, producing different landing distance for the plume of emitted air pollutants and therefore biasing the performance of FTIR monitoring with single path. In conclusion, traditional single FTIR monitoring path is not capable in monitoring common multiple emission sources. Synchronous FTIR monitorings with multiple paths, dispatched either in two dimensions or even three dimensions, are recommended for investigation on relatively complicated episodes in high-tech industry parks or any other industrial zone with densely erected stacks to enhance the efficacy of FTIR monitoring. Study II in the first part of the present study was conducted to explore the emission of air pollutants and their concentration fluctuations around the indoor and outdoor environmens of a semiconductor manaufactrure plant using four-consective-day monitoring data synchronously collected by three FTIR spectrometers. Based on a total of 1,032 continuous five-minute interval records, the percentages for indoor/outdoor concentration ratio higher than 1.0 ranged from 62.2% to 73.1% for carbon tetrafluoride, nitrous oxide, carbon monoxide, and methane, indicating indoor concentrations usually hihger than outdoor ones for these chemicsls. And, it was observed that the relationship between indoor and outdoor chemical concentrations dynamically changed from the temporary point of view. Regression analysis showed that, at relatively low level, the highest nitrous oxide concentration was present in the sub Fab, followed by the outdoor MAU, and then by the Fab, implying the original emission sources was in the sub Fab of the indoor environment and these chemicals might be able to accumulate in the outdoor environment. In contrast, results of regression analysis indicated that, at relatively high level, the indoor chemical concentrations measured in Fab or sub Fab were generally greater than the outdoor chemical concentration measured at the MAU. This situation could be attributed to the generation of chemical pollutants in indoor environment and 80% returned air from the sub Fab was used in the ventilation system, resulting in low ventilation efficacy for the indoor air pollutants and increased airborne chemical concentrations accordingly. It was demonstrated that, in the science industrial park with densely distributed fixed pollutant sources, synchronous multiple FTIR monitoring paths for continuous monitoring on the relationship between indoor and outdoor chemical cocentrations were effective measures in the monitoring of pollutant emission and dispersion. This method provided the high-tech manufacturing facilities, which are extremely sensitive to airborne molecular contaminants, a reliable measurement and monitoring method for indoor and outdoor pollutants. The second part of this study, i.e., Study III, was conducted to explore the impact of a water-damaged indoor environment on children’s weekly absences resulting from upper respiratory infection in a kindergarten. Twenty-six and 27 children were recruited from water-damaged and non-water-damaged classrooms, respectively, in the same building, and were followed up during the study period of 42 weeks. Weekly absence rates were computed from daily absence records. The weekly absence rate was significantly higher for children in the water-damaged classroom, 2.99%, than that for those in the non-water-damaged classroom, 1.28%. Results of the generalized estimating equation model (GEE) indicated that the weekly absence rate of K-6 was slightly higher than K-5 (OR=2.02 / 95% CI: 0.99-4.11, P=0.054). After adjusting for gender and age, the odds ratio for absence was 2.45 (95% CI: 1.15－5.24, p<0.05) for the children in the water-damaged classroom. Additionally, fungal concentration was significantly higher in the water-damaged classroom (993 CFU/m3) than in the non-water damaged classroom (404 CFU/m3). The water-damaged issue in the air-conditioned building is hard to be identified by measuring humidity. It is tentatively concluded that the fungal concentration is a better indicator than humidity for early-stage water damage in the indoor environment. Fungal concentration is of greater importantance and effectiveness as humidity is not an appropriate indicator for water-damage in a well air-conditioned indoor envirionment.

碩士
國立彰化師範大學
工業教育與技術學系
96
This study aimed to design a program for school-based graphical monitoring and control sensor curriculum in industrial high school, and to be referred by industrial high schools. According to the results of this curriculum program, the researcher offers some concrete suggestions to the administrative authorities of educational institutions and schools, as well as to be used for further studies. In order to accomplish the aim mentioned above, two different research methods were used in this study: literature reviews and expert consultations. Some of the main subjects were designed according to the data collected through literature reviews. They were the structure of the curriculum, the teaching goal of practical training classes, and the course syllabus. The programs were evaluated, checked and revised during expert consultations in order to make sure they were well-designed. The results of the research shown as follows: 1.The pattern of school-based curriculum emphasizes the function of analysis, and then confirms the goal and the structure of the program. Furthermore, it should aim at the outcome of evaluation and the revision of feedback. It should also completely correspond with the process: to plan, to design, to put into practice, and to evaluate. The plan of graphical monitoring and control sensor curriculum should base on the educational development policy and the economic trend. The content of the curriculum should not only meet the industrial needs but also tally with the school-based principle. In addition, it should also promote students with abilities in actual practice. 2.Graphical monitoring and control sensor curriculum includes different parts as follows: switch, photo-sensor, temperature sensor, pressure sensor and other sensors. The teaching goal is also necessary to help students develop the correct professional ethics and sense of responsibility. 3.The plan of graphical monitoring and control sensor curriculum includes some practical training subjects. The subjects are basic electricity theory practice, electronics practice, electronic instrument practice, digital logic practice, electronic circuits practice, micro processor practice, sensors practice, computer graphic practice, and Graphical monitoring and control sensor practice. 4.The practice of graphical monitoring and control sensor curriculum should take some main objects into consideration. First, what each school has. Second, faculty and equipment. Finally, the coordination and flexibility of class arrangement. The ideal process of this curriculum should correspond to the students' ability and focus on the knowledge that will enable them to learn something.

Il ruolo fondamentale che la manutenzione gioca nei costi di esercizio e nella produttività degli impianti industriali ha portato le aziende e i ricercatori a spostare il loro interesse su questo tema. L'ultima frontiera dell'innovazione in campo manutentivo, resa possibile anche dall'avvento della quarta rivoluzione industriale che promuove la sensorizzazione e l’interconnessione di tutti i macchinari di impianto, è la manutenzione predittiva. Essa mira ad ottenere una previsione accurata della vita utile dei componenti degli impianti industriali al fine di ottimizzare la schedulazione degli interventi sul campo. Lo studio parte da una accurata revisione della letteratura scientifica di settore riguardante le tecniche diagnostiche e prognostiche applicate a componenti di impianti industriali, necessaria alla comprensione dei diversi modelli sviluppati in funzione della tipologia di componente e modo di guasto in analisi. Successivamente ho spostato l’attenzione sul concetto di manutenzione 4.0 al fine di mappare tutte le caratteristiche associate al paradigma dell'Industria 4.0 e le loro possibili applicazioni alla manutenzione. Lo studio condotto ha portato poi alla progettazione, sviluppo e validazione delle metodologie necessarie all’applicazione in real-time di modelli diagnostici e prognostici avanzati, sia statistici che machine learning, necessari all’implementazione sul campo di un sistema di manutenzione predittiva. Grazie all’applicazione delle metodologie proposte ad un caso studio è stato possibile non solo validare i modelli proposti ma anche definire l’architettura informatica necessaria alla loro corretta implementazione sul sistema distribuito di controllo (Distributed Control System - DCS) di impianto in funzione della tipologia del componente e del guasto in analisi. I modelli testati e validati hanno mostrato elevate prestazioni diagnostiche soprattutto per quanto riguarda i modelli ML che sfruttano le Support Vector Machine (SVM). In definitiva, questo lavoro di tesi mostra nel dettaglio tutti i passaggi necessari allo sviluppo di un sistema di manutenzione predittiva efficace in impianto: partendo dall’analisi dei modi di guasto e dalla sensorizzazione dei componenti, passando poi allo sviluppo dei modelli diagnostici e prognostici real-time fino alla costruzione dell’interfaccia di visualizzazione dei risultati delle analisi svolte, analizzando anche l’architettura informatica necessaria al suo corretto funzionamento. The fundamental role that maintenance plays in the operating costs and productivity of industrial plants has led companies and researchers to shift their interest in this issue. The last frontier of innovation in the maintenance field, made possible also by the advent of the fourth industrial revolution which promotes the sensorisation and interconnection of all plant machinery, is predictive maintenance. It aims to obtain an accurate forecast of the useful life of the industrial plants’ components in order to optimise the scheduling of interventions in the field. The study starts from an accurate review of the scientific literature concerning the diagnostic and prognostic techniques applied to industrial plant components, necessary to understand the different models developed according to the type of component and failure mode under analysis. Subsequently I shifted the focus to the maintenance 4.0 concept in order to map all the characteristics associated with the Industry 4.0 paradigm and their possible applications to maintenance operations. The study then led to the design, development and validation of the methodologies necessary for the real-time application of advanced diagnostic and prognostic models, both statistical and machine learning, necessary for the field implementation of a predictive maintenance system. Thanks to the application of the proposed methodologies to a case study, it was possible not only to validate the proposed models but also to define the IT architecture necessary for their correct implementation on the plant's Distributed Control System (DCS) according to the type of component and the fault under analysis. The tested and validated models showed high diagnostic performance, especially regarding the Support Vector Machine (SVM) Machine Learning models. Ultimately, this thesis shows in detail all the steps necessary for the development of an effective predictive maintenance system in the plant: starting from the analysis of failure modes and component sensorisation, then moving on to the development of real-time diagnostic and prognostic models up to the build-up of the interface for visualising the results of the analyses carried out, also analysing the IT architecture necessary for its correct operation.

Dissertação de mestrado integrado em Engenharia Civil
Uma empresa de construção civil deve possuir um Plano de Qualidade que possa ser implementado a toda a sua estrutura, que deve partir da vontade da administração e ser aceite por todos os colaboradores. Nesse plano incluir-se um Plano de Monitorização e Medição que é um processo de previsão, acompanhamento e registo dos trabalhos a executar, e será um instrumento obrigatório de trabalho para a equipa técnica da obra. Deverá ser encarado como uma ferramenta que visa obter uma maior qualidade bem como também permitir um maior controlo nas operações. O acesso às novas tecnologias e de informação, sobretudo com os meios informáticos, deverá ser associado ao Plano, para assim facilitar a divulgação e simplificar a utilização. Ao longo da execução dos trabalhos da empreitada, será demonstrado que um bom Plano de Monitorização e Medição melhora a qualidade construtiva, proporciona o cumprimento de prazos, evidencia todas as opções tomadas, contribui para uma construção em segurança e, sobretudo, beneficia a empresa construtora não somente ao nível financeiro, mas também a outros níveis. O diretor de obra será um elemento importante para atingir os objetivos propostos, por isso os seus atributos bem como a sua inserção nesse sistema é um ponto chave. O plano de Monitorização e Medição, sendo inserido num plano de qualidade, deverá ser um dispositivo evolutivo, capaz de ser melhorado, de ser complementado e sobretudo de ser adaptável a cada obra. Os resultados obtidos na obra que serviu de base a este trabalho foram muito positivos, testemunhado pela própria administração da empresa construtora que assegurou a sua utilização em obras futuras.
A construction company must have a Quality Plan that can be implemented throughout its structure, which must start from the will of the administration and be accepted by all employees. In this plan include a Monitoring and Measurement Plan which is a process of forecasting, monitoring and recording the work to be performed, and will be a mandatory instrument of work for the technical team of the work. It should be seen as a tool for higher quality as well as greater control over operations. Access to new technologies and information, especially with information technology, should be linked to the Plan, so as to facilitate the dissemination and simplification of use. During the execution of the works, it will be demonstrated that a good Monitoring and Measurement Plan improves the constructive quality, provides deadlines compliance, shows all the options taken, contributes to a safe construction and mainly benefits the construction company not only financially but also at other levels. The work director will be an important element to achieve the proposed objectives, so their attributes as their insertion in this system is a key point. The Monitoring and Measurement plan, being inserted in a quality plan, should be an evolutionary device, capable of being improved, of being complemented and above all of being adaptable to each work. The results obtained in the work that served as basis for this work were very positive, witnessed by the management of the construction company that ensured its use in future works.

Orientação: Susana Marta Lopes Almeida ; co-orientação: Jorge Costa
Esta tese de mestrado teve como principal objectivo estudar a distribuição de elementos químicos presentes na atmosfera de uma zona industrial no norte de Espanha – Gijón, Astúrias - através da técnica de biomonitorização, na qual se utilizaram líquenes como biomonitores. Líquenes epífitas Parmelia sulcata foram retirados de oliveiras de uma zona rural portuguesa não poluída - Montargil. Estes foram transplantados para Gijón e colocados numa grelha de 18km por 20km, envolvendo uma área industrial constituída por uma cimenteira, uma siderurgia e uma indústria termoeléctrica. O período de exposição foi de 5 meses, entre Abril e Setembro de 2010. A caracterização elementar das amostras foi efectuada através da técnica Análise Instrumental de Activação Neutrónica (INAA) identificando-se assim o Al, As, Br, Cl, Cu, Fe, I, La, Na, Sb, Sc, Sm, V e Zn. Para determinar as respectivas concentrações recorreu-se ao método k0. Posteriormente estudou-se a distribuição espacial dos elementos analisados através de um programa de modelação de sistema de informação geográfica (SIG), o ArcGIS 10. Os resultados do presente estudo demonstraram que existem elementos com uma distribuição similar e que estão associados a um mesmo tipo de fonte. Assim, identificaram-se três principais fontes de emissão: o solo (identificado pelos elementos Al, La, Sc e Sm); o mar (identificado pelo Br, Cl, I e Na) e fontes antropogénicas (associadas ao As, Cu, Fe, Sb, V e Zn).
The main purpose of this master thesis was to combine biomonitoring techniques with geographic information systems (GIS) in order to assess the impact of an industrial area from the North of Spain onto the air quality. Samples of the epiphytic lichen Parmelia sulcata were collected from olive trees in an unpolluted Portuguese rural area (Montargil, Portugal) and transplanted to the north of Spain, in a grid of 18 km per 20 km, having an industrial area at its center: a cement mill, a power plant and a steelwork. Lichens were exposed during 5 months, starting in April and ending in September 2010. After exposure the technique Instrumental Neutron Activation Analysis, using the k0 methodology, was used to determine the concentrations of the elements Al, As, Br, Cl, Cu, Fe, I, La, Na, Sb, Sc, Sm, V and Zn. The spatial distribution pattern of the elements concentrations was modelled using the programme ArcGIS 10. Results showed that some elements presented a similar spatial distribution. Three main types of patterns were identified indicating the existence of three principal types of sources: the soil identified by the elements Al, La, Sc and Sm; the sea identified by Br, Cl, I and Na, and the anthropogenic sources associated with As, Cu, Fe, Sb, V and Zn.

Orientação: Susana Marta Lopes Almeida ; co-orientação: Jorge Costa
Esta tese de mestrado teve como principal objectivo estudar a distribuição de elementos químicos presentes na atmosfera de uma zona industrial no norte de Espanha – Gijón, Astúrias - através da técnica de biomonitorização, na qual se utilizaram líquenes como biomonitores. Líquenes epífitas Parmelia sulcata foram retirados de oliveiras de uma zona rural portuguesa não poluída - Montargil. Estes foram transplantados para Gijón e colocados numa grelha de 18km por 20km, envolvendo uma área industrial constituída por uma cimenteira, uma siderurgia e uma indústria termoeléctrica. O período de exposição foi de 5 meses, entre Abril e Setembro de 2010. A caracterização elementar das amostras foi efectuada através da técnica Análise Instrumental de Activação Neutrónica (INAA) identificando-se assim o Al, As, Br, Cl, Cu, Fe, I, La, Na, Sb, Sc, Sm, V e Zn. Para determinar as respectivas concentrações recorreu-se ao método k0. Posteriormente estudou-se a distribuição espacial dos elementos analisados através de um programa de modelação de sistema de informação geográfica (SIG), o ArcGIS 10. Os resultados do presente estudo demonstraram que existem elementos com uma distribuição similar e que estão associados a um mesmo tipo de fonte. Assim, identificaram-se três principais fontes de emissão: o solo (identificado pelos elementos Al, La, Sc e Sm); o mar (identificado pelo Br, Cl, I e Na) e fontes antropogénicas (associadas ao As, Cu, Fe, Sb, V e Zn).
The main purpose of this master thesis was to combine biomonitoring techniques with geographic information systems (GIS) in order to assess the impact of an industrial area from the North of Spain onto the air quality. Samples of the epiphytic lichen Parmelia sulcata were collected from olive trees in an unpolluted Portuguese rural area (Montargil, Portugal) and transplanted to the north of Spain, in a grid of 18 km per 20 km, having an industrial area at its center: a cement mill, a power plant and a steelwork. Lichens were exposed during 5 months, starting in April and ending in September 2010. After exposure the technique Instrumental Neutron Activation Analysis, using the k0 methodology, was used to determine the concentrations of the elements Al, As, Br, Cl, Cu, Fe, I, La, Na, Sb, Sc, Sm, V and Zn. The spatial distribution pattern of the elements concentrations was modelled using the programme ArcGIS 10. Results showed that some elements presented a similar spatial distribution. Three main types of patterns were identified indicating the existence of three principal types of sources: the soil identified by the elements Al, La, Sc and Sm; the sea identified by Br, Cl, I and Na, and the anthropogenic sources associated with As, Cu, Fe, Sb, V and Zn.

Healthy vegetation are essential not just for environmental sustainability but also for the development of sustainable and liveable cities. It is undeniable that human activities are altering the vegetation landscape, with harmful implications for the climate. As a result, autonomous detection, health evaluation, and continual monitoring of the plants are required to ensure environmental sustainability. This thesis presents research on autonomous vegetation management using recent advances in deep learning. Currently, most towns do not have a system in place for detection and continual vegetation monitoring. On the one hand, a lack of public knowledge and political will could be a factor; on the other hand, no efficient and cost-effective technique of monitoring vegetation health has been established. Individual plants health condition data is essential since urban trees often develop as stand-alone objects. Manual annotation of these individual trees is a time-consuming, expensive, and inefficient operation that is normally done in person. As a result, skilled manual annotation cannot cover broad areas, and the data they create is out of date. However, autonomous vegetation management poses a number of challenges due to its multidisciplinary nature. It includes automated detection, health assessment, and monitoring of vegetation and trees by integrating techniques from computer vision, machine learning, and remote sensing. Other challenges include a lack of analysis-ready data and imaging diversity, as well as dealing with their dependence on weather variability. With a core focus on automation of vegetation management using deep learning and transfer learning, this thesis contributes novel techniques for Multi-view vegetation detection, robust calculation of vegetation index, and real- time vegetation health assessment using deep convolutional neural networks (CNNs) and deep learning frameworks. The thesis focuses on four general aspects: a) training CNN with possibly inaccurate labels and noisy image dataset; b) deriving semantic vegetation segmentation from the ordinal information contained in the image; c) retrieving semantic vegetation indexes from street-level imagery; and d) developing a vegetation health assessment and monitoring system. Firstly, it is essential to detect and segment the vegetation, and then calculate the pixel value of the semantic vegetation index. However, because the images in multi- sensory data are not identical, all image datasets must be registered before being fed into the model training. The dataset used for vegetation detection and segmentation was acquired from multi-sensors. The whole dataset was multi-temporal based; therefore, it was registered using deep affine features through a convolutional neural network. Secondly, after preparing the dataset, vegetation was segmented by using Deep CNN, a fully convolutional network, and U-net. Although the vegetation index interprets the health of a particular area’s vegetation when assessing small and large vegetation (trees, shrubs, grass, etc.), the health of large plants, such as trees, is determined by steam. In contrast, small plants’ leaves are evaluated to decide whether they are healthy or unhealthy. Therefore, initially, small plant health was assessed through their leaves by training a deep neural network and integrating that trained model into an internet of things (IoT) device such as AWS DeepLens. Another deep CNN was trained to assess the health of large plants and trees like Eucalyptus. This one could also tell which trees were healthy and which ones were unhealthy, as well as their geo-location. Thus, we may ultimately analyse the vegetation’s health in terms of the vegetation index throughout time on the basis of a semantic-based vegetation index and compute the index in a time-series fashion. This thesis shows that computer vision, deep learning and remote sensing approaches can be used to process street-level imagery in different places and cities, to help manage urban forests in new ways, such as biomass-surveillance and remote vegetation monitoring.