Detection of buried pipes using a shear wave ground surface vibration technique

A major UK initiative, entitled 'Mapping the Underworld', is seeking to address the serious social, environmental and economic consequences arising from an inability to locate the buried utility service infrastructure without resorting to extensive excavations. Mapping the Underworld aims to develop and prove the efficacy of a multi-sensor device for accurate remote buried utility service detection, location and, where possible, identification. One of the technologies to be incorporated in the device is low-frequency vibro-acoustics, and the application of this technology for detecting buried infrastructure is currently being investigated. Here, a shear wave ground vibration technique for detecting buried pipes is described. For this technique, shear waves are generated at the ground surface, and the resulting ground surface vibrations measured, using geophones, along a line traversing the anticipated run of the pipe. Measurements were made at a test site with a single pressurized polyethylene mains water pipe. Time-extended signals were employed to generate the illuminating wave. Cross-correlation functions between the measured ground velocities and a reference measurement adjacent to the excitation were then calculated and summed using a stacking method to generate a cross-sectional image of the ground. The wide cross-correlation peaks caused by high ground attenuation were partially compensated for by using a generalized cross-correlation function called the smoothed coherence transform. To mitigate the effects of other potential sources of vibration in the vicinity, the excitation signal was used as an additional reference when calculating the generalized cross-correlation functions. For two out of three tests, the pipe was detected, indicating that this technique will be a valuable addition to the Mapping the Underworld armoury.

Classificação de sinais acústicos utilizando a transformada wavelet discreta e a decomposição de modo empírico: aplicações na área de alimentos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Momentos nulos e regularidade wavelet na detecção de falhas em sinais

Pós-graduação em Engenharia Elétrica - FEIS

Classificação de níveis de desgaste de dressadores de ponta única utilizando sinais de emissão acústica e redes neurais artificiais

Pós-graduação em Engenharia Elétrica - FEB

Análise de multirresolução baseada em polinômio potência de Sigmóide - Wavelet

Pós-graduação em Ciência da Computação - IBILCE

Monitoramento da dressagem na retificação através do sinal puro de emissão acústica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Bancada multifuncional para simulação de mecanismos de falhas em máquinas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudos de imagens provenientes de membranas de borracha natural com aditivos metálicos utilizando técnicas de Fourier, Gabor e Wavelets

Pós-graduação em Ciência e Tecnologia de Materiais - FC

Um método não-limiar para redução de ruído em sinais de voz no domínio wavelet

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A tool for controlling accelerometers. Secondary calibration data

Vibration monitoring requires acceleration transducers capable of providing data with high precision. Accelerometers are the most frequently used vibration transducers. Their calibration plays an important role in measuring vibrations and is a key component in ensuring the integrity of the vibration measurement. For managing secondary calibration data of accelerometers, a database computer system was implemented. The implementation of this software has been an important step forward in providing a wide range of analysis and display tools. This paper reviews the main concepts involving accelerometer secondary calibration and describes the tool developed and the methods used in its development. (C) 2013 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Rotor Failure Diagnosis of Induction Motors by Wavelet Transform and Fourier Transform in Function of the Load

This paper presents two diagnostic methods for the online detection of broken bars in induction motors with squirrel-cage type rotors. The wavelet representation of a function is a new technique. Wavelet transform of a function is the improved version of Fourier transform. Fourier transform is a powerful tool for analyzing the components of a stationary signal. But it is failed for analyzing the non-stationary signal whereas wavelet transform allows the components of a non-stationary signal to be analyzed. In this paper, our main goal is to find out the advantages of wavelet transform compared to Fourier transform in rotor failure diagnosis of induction motors.

Investigação de técnicas para o acompanhamento do desgaste de um par engrenado utilizando tribologia e análise da resposta dinâmica processada via função densidade probabilidade Beta

Pós-graduação em Engenharia Mecânica - FEIS

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Procedure e strumenti innovativi per lo sfruttamento sostenibile delle risorse minerarie

L'approvvigionamento di risorse minerali e la tutela dell'ambiente sono spesso considerate attività contrapposte ed inconciliabili, ma in realtà rappresentano due necessità imprescindibili per le società moderne. Le georisorse, in quanto non rinnovabili, devono essere valorizzate in maniera efficiente, adoperando strumenti che garantiscano la sostenibilità ambientale, sociale ed economica degli interventi estrattivi. La necessità di tutelare il territorio e migliorare la qualità della vita delle comunità locali impone alla Pubblica Amministrazione di implementare misure per la riqualificazione di aree degradate, ma fino ai primi anni '90 la normativa di settore non prevedeva strumenti a tal proposito, e ciò ha portato alla proliferazione di siti estrattivi dismessi e abbandonati senza interventi di recupero ambientale. Il presente lavoro di ricerca fornisce contributi innovativi alla pianificazione e progettazione sostenibile delle attività estrattive, attraverso l'adozione di un approccio multidisciplinare alla trattazione del tema e l'utilizzo esperto dei Sistemi Informativi Geografici, in particolare GRASS GIS. A seguito di una approfondita analisi in merito agli strumenti e le procedure adottate nella pianificazione delle Attività Estrattive in Italia, sono stati sviluppati un metodo di indagine ed un sistema esperto per la previsione ed il controllo delle vibrazioni indotte nel terreno da volate in cava a cielo aperto, che consentono di ottimizzare la progettazione della volata e del sistema di monitoraggio delle vibrazioni grazie a specifici strumenti operativi implementati in GRASS GIS. A supporto di una più efficace programmazione di interventi di riqualificazione territoriale, è stata messa a punto una procedura per la selezione di siti dismessi e di potenziali interventi di riqualificazione, che ottimizza le attività di pianificazione individuando interventi caratterizzati da elevata sostenibilità ambientale, economica e sociale. I risultati ottenuti dimostrano la necessità di un approccio esperto alla pianificazione ed alla progettazione delle attività estrattive, incrementandone la sostenibilità attraverso l'adozione di strumenti operativi più efficienti.