Biodiversity and resilience of ecosystem functions

Accelerating rates of environmental change and the continued loss of global biodiversity threaten functions and services delivered by ecosystems. Much ecosystem monitoring and management is focused on the provision of ecosystem functions and services under current environmental conditions, yet this could lead to inappropriate management guidance and undervaluation of the importance of biodiversity. The maintenance of ecosystem functions and services under substantial predicted future environmental change (i.e., their ‘resilience’) is crucial. Here we identify a range of mechanisms underpinning the resilience of ecosystem functions across three ecological scales. Although potentially less important in the short term, biodiversity, encompassing variation from within species to across landscapes, may be crucial for the longer-term resilience of ecosystem functions and the services that they underpin.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Detecting Plants on Railway Embankments

This paper investigates problems concerning vegetation along railways and proposes automatic means of detecting ground vegetation. Digital images of railway embankments have been acquired and used for the purpose. The current work mainly proposes two algorithms to be able to achieve automation. Initially a vegetation detection algorithm has been investigated for the purpose of detecting vegetation. Further a rail detection algorithm that is capable of identifying the rails and eventually the valid sampling area has been investigated. Results achieved in the current work report satisfactory (qualitative) detection rates.

Effective Data Management Enables Intelligent Utility Management

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Análise de confiabilidade de uma bomba centrífuga: aplicação na injeção de água para recuperação de petróleo

The oil industry`s need to produce with maximum efficiency, not to mention the safety and the environment aspects, encourages the optimization of processes. It makes them look for a level of excellence in acquisition of equipment, ensuring the quality without prejudice security of facilities and peoples. Knowing the reliability of equipment and that this stands for a system is fundamental to the production strategy to seeks the maximum return on investment. The reliability analysis techniques have been increasingly applied in the industry as strategy for predicting failures likelihood ensuring the integrity of processes. Some reliability theories underlie the decisions to use stochastic calculations to estimate equipment failure. This dissertation proposes two techniques associating qualitative (through expertise opinion) and quantitative data (European North Sea oil companies fault database, Ored) applied on centrifugal pump to water injection system for secondary oil recovery on two scenarios. The data were processed in reliability commercial software. As a result of hybridization, it was possible to determine the pump life cycle and what impact on production if it fails. The technique guides the best maintenance policy - important tool for strategic decisions on asset management.

A New Approach for Real Time Fault Diagnosis in Induction Motors Based on Vibration Measurement

Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

Automatic dimming multi-lamp fluorescent management system with active input power factor corrector stage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of an instrumentation system embedded on FPGA for real time measurement of mechanical vibrations in rotating machinery

The real-time monitoring of events in an industrial plant is vital, to monitor the actual conditions of operation of the machinery responsible for the manufacturing process. A predictive maintenance program includes condition monitoring of the rotating machinery, to anticipate possible conditions of failure. To increase the operational reliability it is thus necessary an efficient tool to analyze and monitor the equipments, in real-time, and enabling the detection of e.g. incipient faults in bearings. To fulfill these requirements some innovations have become frequent, namely the inclusion of vibration sensors or stator current sensors. These innovations enable the development of new design methodologies that take into account the ease of future modifications, upgrades, and replacement of the monitored machine, as well as expansion of the monitoring system. This paper presents the development, implementation and testing of an instrument for vibration monitoring, as a possible solution to embed in industrial environment. The digital control system is based on an FPGA, and its configuration with an open hardware design tool is described. Special focus is given to the area of fault detection in rolling bearings. © 2012 IEEE.

The North-South dimension of the environmental and cleaner technology industries

Includes bibliography

Implementação de técnicas de processamento de sinais para o monitoramento da condição de mancais de rolamento

Pós-graduação em Engenharia Mecânica - FEG

Desenvolvimento de um sistema de instrumentação de medição de vibração mecânica em máquina rotativas, em tempo real, embarcado em FPGA

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Foraminíferos em testemunho do manguezal do Canal de Bertioga (SP): padrões de estrutura de comunidades aplicáveis em reconstruções paleoambientais

Nowadays, there is a search for knowledgment that could be applied in the solution of the problems caused by petrolific activities involving the environment, like the biodiversity preservation and the ecosystems monitoring and management. Foraminifera (Protista) are used as an important tool to the environment characterizarion, because they answer quickly to the fisic-quimic variations and indicate local alterations. The goal of this job is to create models of foraminiferal communities composition through the screening of subsuperficial samples obtained from a core collect from Bertioga Channel, Baixada Santista (SP), trying to understand the influence of the environmental variations along the time upon the indicator species presence, as well as making paleoenvironmentals reconstructions of the area. A 80 cm-core was removed in the outer edge of marsh adjacent to Bertioga Channel, not far from the confluence with the Itapanhaú River. There are presented in abundance, equitability, diversity and species richness obtained in nine samples along the sediment. The lower part of the core is compound by calcareous species (rotalideos and miliolideos) with domain Ammonia (Biofacies 1) and the intermediate and upper parts contain mainly agglutinated species (Biofacies 2 and 3, which is dominated by species of Ammotium). The qualitative and quantitative study of the microfauna of foraminifera present in the core reveals that in recent decades the sampling area passed from a condition of infra-marginal strip under significant coastal marine influence for the condition of inter-coastal swamp covered with mangrove vegetation. This change indicates that the site has undergone a process of sediment progradation, a phenomenon that may have been timely, localized, or a reflection of a relative fall in sea level at the regional level

Ingegneria di Manutenzione

Lo scopo di questa tesi di dottorato di ricerca consiste nel fornire la giusta collocazione della manutenzione fra le discipline dell'ingegneria, raccogliendo e formalizzando le metodologie di analisi di affidabilità e di pianificazione degli interventi all'interno di un unico processo di progettazione e di controllo. In linea di principio, un processo di analisi dei guasti e di programmazione della manutenzione deve essere in grado di fornire chiare e sicure risposte ai seguenti interrogativi: Quali sono le funzioni richieste e con quali criteri di prestazioni il sistema è chiamato ad assolverle? Qual'è l'andamento della disponibilità del sistema in funzione del tempo? Quanti guasti e di quale tipo si possono verificare durante la vita del sistema? Quali possono essere le conseguenze che ledono la sicurezza e la protezione ambientale? Quanti pezzi di ricambio sono necessari? Che tipo di interventi di manutenzione preventiva risultano tecnicamente fattibili? A quali scadenze devono essere programmati? A quanto ammonta la previsione del costo di esercizio del sistema? Quante squadre di manutenzione devono essere assegnate al sistema? Come deve essere organizzata la logistica di manutenzione? Con quali tecniche si prevede di riconoscere i guasti e quali procedure devono essere attivate per farvi fronte? E' possibile implementare tecniche di `condition monitoring' delle macchine? Su quali tempi di preavviso sui guasti si può contare? In tal senso, la manutenzione necessita delle tecniche e degli opportuni strumenti che siano in grado di misurarne l'efficacia e l'efficienza. L'efficacia in primo luogo, in quanto l'obiettivo principe consiste nel garantire che il sistema oggetto di studio continui a svolgere le proprie funzioni nei limiti di prestazioni accettabili, secondo le specifiche richieste degli utilizzatori. L'efficienza in secondo luogo, ma non per questo di minore importanza, in quanto perseguendo l'obiettivo di cui sopra, occorre impegnare il minimo di risorse possibili, organizzando con razionalità il supporto logistico del sistema al fine di raggiungere i massimi livelli di rendimento di gestione. La migliore strategia di manutenzione può essere pianificata, a priori, solo se si è in grado di prevedere con la necessaria precisione l'evoluzione del sistema nel suo contesto operativo futuro. E' allora possibile formulare un modello matematico del sistema, studiarne la dinamica ed osservare le reazioni alla simulazione di eventuali stimoli esterni. I metodi ed i modelli noti dell'ingegneria dei sistemi possono essere molto utili per la risoluzione di casi semplici, ma sovente richiedono la formulazione di ipotesi troppo restrittive che aumentano in modo inaccettabile la distanza del modello dalla realtà. Una strada alternativa ed affascinante, che ho percorso con entusiasmo durante questi tre anni di studi e ricerca, consiste nella simulazione numerica della vita del sistema, utilizzando il metodo Monte Carlo per la gestione dei processi stocastici di guasto e per l'esecuzione degli interventi di manutenzione. Ho quindi messo a punto il codice di simulazione RAMSES, perseguendo l'idea di costruire uno strumento di misura dell'efficacia e dell'efficienza di una politica di manutenzione simulata al calcolatore. Nella tesi si presentano i concetti di base dell'ingegneria dei sistemi applicata al caso della manutenzione e si introduce il formalismo della Reliability Centred Maintenance come miglior guida nella pianificazione delle schede di manutenzione. Si introducono le nozioni di base per fornire una struttura solida e corretta alla simulazione numerica dei sistemi riparabili e si presenta il codice RAMSES corredando le informazioni tecniche con i dovuti esempi ed applicazioni pratiche. Si conclude il lavoro, infine, con la presentazione di un modello di massima verosimiglianza particolarmente utile per le analisi dei dati sperimentali di guasto dei componenti.