Filter holders and continuous air monitors (CAMs) are used extensively in the nuclear industry. It is important to minimize leakage in these devices and in recognition of this consideration, a limit on leakage for sampling systems is specified in ANSI/HPS N13.1-1999; however the protocol given in the standard is really germane to measurement of significant leakage, e.g., several percent of the sampling flow rate. In the present study, a technique for quantifying leakage was developed and that approach was used to measure the sealing integrity of a CAM and two kinds of filter holders. The methodology involves use of sulfur hexafluoride as a tracer gas with the device being tested operated under dynamic flow conditions. The leak rates in these devices were determined in the pressure range from 2.49 kPa (10 In. H2O) vacuum to 2.49 kPa (10 In. H2O) pressure at a typical flow rate of 56.6 L/min (2 cfm). For the two filter holders, the leak rates were less than 0.007% of the nominal flow rate. The leak rate in the CAM was less than 0.2% of the nominal flow rate. These values are well within the limit prescribed in the ANSI standard, which is 5% of the nominal flow rate. Therefore the limit listed in the ANSI standard should be reconsidered as lower values can be achieved, and the methodology presented herein can be used to quantify lower leakage values in sample collectors and analyzers. A theoretical analysis was also done to determine the nature of flow through the leaks and the amount of flow contribution by the different possible mechanisms of flow through leaks.

This dissertation deals with the development of a model-based diagnostic system for air brake systems that are widely used in commercial vehicles, such as trucks, tractor-trailers, buses, etc. The performance of these brake systems is sensitive to maintenance and hence they require frequent inspections. Current inspection techniques require an inspector to go underneath a vehicle to check the brake system for possible faults, such as leaks, worn brake pads, out-of-adjustment of push rods, etc. Such inspections are time consuming, labor intensive and difficult to perform on vehicles with a low ground clearance. In this context, the development of an onboard/ handheld diagnostic tool for air brakes would be of significant value. Such a tool would automate the brake inspection process, thereby reducing the inspection time and improving the safety of operation of commercial vehicles. In this dissertation, diagnostic schemes are developed to automatically detect two important and prevalent faults that can occur in air brake systems – leaks and out-of-adjustment of push rods. These diagnostic schemes are developed based on a nonlinear model for the pneumatic subsystem of the air brake system that correlates the pressure transients in the brake chamber with the supply pressure to the treadle valve and the displacement of the treadle valve plunger. These diagnostic schemes have been corroborated with data obtained from the experimental facility at Texas A&M University and the results are presented. The response of the pneumatic subsystem of the air brake system is such that it can be classified as what is known as a “Sequential Hybrid System”. In this dissertation, the term “hybrid systems” is used to denote those systems whose mathematical representation involves a finite set of governing ordinary differential equations corresponding to a finite set of modes of operation. The problem of estimating the push rod stroke is posed as a parameter estimation problem and a transition detection problem involving the hybrid model of the pneumatic subsystem of the air brake system. Also, parameter estimation schemes for a class of sequential hybrid systems are developed. The efficacy of these schemes is illustrated with some examples.

Leakages in the district heating networks is a current and growing problem. To find the leakages today many district heating companies uses manual techniques that are both time consuming and insecure, the methods can leave a lot of leakages in older pipes undiscovered for a very long time. These undetected leakages costs the district heating companies a lot of money and can even be fatal. It is therefor of great importance that the leakages is found in time, thus the methods for leak detection needs to be improved. The main purpose of this thesis was to investigate the ability to use thermal images to automatically search for leakages in district heating systems. To investigate this aerial thermal images from 2013 were collected. Image analysis was performed using ArcGIS and ENVI. This included, among other things, image preprocessing such as to define the projection of the images and unsupervised isodata classification to find potential leakages in the thermal images. This automatic analysis resulted in many false alarms. One example were false alarms caused by vegetation, since vegetation absorbs heat during the day it appears warmer than the surroundings at night. To deal with this problem an unsupervised classification algorithm, isodata, was used again to classify the vegetational areas and the non-vegetational. This algorithm decreased the number of false alarms drastic and thereby increased the usability of the algorithm. Other false alarm that has not been automatically rejected in this thesis were for example false alarms caused by heat leaking from buildings. One way to map such false alarms could be to analyse the shape and the linearisation of the potential leakages close to buildings. This would hugely increase the accuracy of the used algorithm. The provided thermal images used in this thesis consisted of several confirmed leakages. All these confirmed leakages was found by the used algorithm. Although, the accuracy of the used algorithm could be discussed since many false alarms were generated. Nevertheless, to reject false alarms are much less time consuming than manual leak detection for an entire city. Thereby the conclusion that an automatic leak detection in district heating networks is possible, furthermore a leak detection tool like this would be usable for the district heating companies. The evaluations from several different district heating experts who are using Digpro's district heating application, dpHeating, today shows that a leak detection tool using thermal images would be a useful addition in dpHeating.

Large graph-based datasets are common to many applications because of the additional structure provided to data by graphs. Patterns extracted from graphs must adhere to these structural properties, making them a more complex class of patterns to identify. The role of graph mining is to efficiently extract these patterns and quantify their significance. In this thesis, we focus on two application domains and demonstrate the design of graph mining algorithms in these domains. First, we investigate the use of graph grammar mining as a tool for diagnosing potential memory leaks from Java heap dumps. Memory leaks occur when memory that is no longer in use fails to be reclaimed, resulting in significant slowdowns, exhaustion of available storage, and eventually application crashes. Analyzing the heap dump of a program is a common strategy used in memory leak diagnosis, but our work is the first to employ a graph mining approach to the problem. Memory leaks accumulate in the heap as classes of subgraphs and the allocation paths from which they emanate can be explored to contextualize the leak source. We show that it suffices to mine the dominator tree of the heap dump, which is significantly smaller than the underlying graph. We demonstrate several synthetic as well as real-world examples of heap dumps for which our approach provides more insight into the problem than state-of-the-art tools such as Eclipse's MAT. Second, we study the problem of multipartite graph clustering as an approach to database summarization on an integrated biological database. Construction of such databases has become a common theme in biological research, where heterogeneous data is consolidated into a single, centralized repository that provides a structured forum for data analysis. We present an efficient approximation algorithm for identifying clusters that form multipartite cliques spanning multiple database tables. We show that our algorithm computes a lossless compression of the database by summarizing it into a reduced set of biologically meaningful clusters. Our algorithm is applied to data from C. elegans, but we note its applicability to general relational databases. / Master of Science

This thesis is focused on the application of cross-correlation technique for leak detection and location in medium density polyethylene (MDPE) pipes. A leaking water pipe generates noise that depends primarily on water pressure, pipe characteristics and the leak size and shape. This noise, commonly called leak signals, can be used for the purpose of leak detection and leak location in MDPE pipes. A correlation technique is typically employed to detect, position and characterise these water leaks and is proved to be very efficient for metallic pipes. However, the same is not true for MDPE pipes where the attenuation rate with distance of the leak/source signal is very high, and the generated leak signals are of low frequency and narrow bandwidth. In order to locate leak with good accuracy in MDPE pipes, the correlation process relies on the estimation of speed of leak signals in water/pipe and the time delay between leak signals measured at two locations. For time delay estimation, a correlation function is used. Its accuracy depends upon the sharpness of the correlation peak, type and positioning of sensor, and the processing of signals obtained, which in turn further depends upon the characteristics of leak signals. In MDPE pipes, leak signals are of low frequency and narrow bandwidth; however, their frequency response is not well characterised. Therefore, this thesis presents an analytical model to explain the acoustic characteristics of leak signals in MDPE pipes. The model is used to study the effects of the cut-off frequencies of low, high and band pass digital filters and the selection of acoustic/vibration sensors for the correlation technique. It detailed the importance of the cut-off frequency of the high pass filter and the insensitivity of the correlation function to the cut off frequency of the low pass filter.

A ocorrência de elevados índices de perdas por vazamentos em sistemas de abastecimento de água é frequentemente ligada às inúmeras quebras de tubulações originadas em decorrência de elevados níveis de pressão atuantes. O controle efetivo de tais perdas requer a detecção e localização dos vazamentos para uma rápida reparação do sistema. Neste sentido, a consideração de análises hidráulicas no escoamento transitório tem se revelado especialmente útil aos propósitos de calibração e detecção de vazamentos. Tal análise pode revelar substancial quantidade de informações sobre as propriedades físicas e o nível de integridade do sistema, pois as ondas de pressão resultantes são afetadas pelos diversos dispositivos e fenômenos, incluindo os vazamentos. Assim, o presente trabalho visa o estudo dos transitórios hidráulicos para a calibração e detecção de vazamentos em modelos de sistemas de distribuição de água. Para tanto, são utilizados dados de redes hipotéticas e de laboratório, e modelos inversos resolvidos por métodos de busca global e local. Devido o emprego de tubos plásticos no circuito de laboratório, o clássico modelo da coluna elástica demonstrou-se ineficiente na reprodução do comportamento hidráulico de tal sistema. Resultados satisfatórios foram obtidos somente com um modelo hidráulico que considere o comportamento viscoelástico dos materiais dos tubos do circuito experimental. / The occurrence of large leakage losses in water supply systems has been frequently linked with pipe breaks resulting from high pressures levels in pipes. Efficient location of leakages is required in order to effectively control water losses and quickly repair the system. Analysis of hydraulic transients has been particularly useful for calibration and leak detection purposes. System observation for such analysis can reveal a substantial amount of information concerning physical properties and the integrity of the system, since water hammer waves are affected by different features and phenomena, including leaks. Thus, this research focuses on hydraulic transients for leak detection and calibration of water distribution system models. These objectives are achieved using data obtained from experiments performed on an experimental facility and numerical experiments on hypothetical networks. Inverse methods were based on both global and local search methods. Classic water hammer theory proved to be imprecise in describing the observed behavior of the hydraulic system composed of plastic pipes. Satisfactorily results were obtained with a hydraulic transient solver considering viscoelastic behavior of the pipe material.

O presente trabalho tem como objetivo principal o desenvolvimento de um sistema de identificação do surgimento de vazamentos (rupturas) em dutos, através da análise do sinal de sensores de pressão de resposta rápida (frequência de corte superior a 1 kHz). O reconhecimento do sinal de vazamento se realiza através de uma rede neural artificial feed-foward do tipo Perceptron Multi Camadas, previamente treinada. Neste trabalho, a implementação para tal operação foi feita off-line, mas devido ao baixo custo computacional pode ser facilmente implementada em eletrônica embarcada, em tempo real (on-line). Os resultados experimentais foram obtidos no oleoduto piloto do NETeF - Núcleo de Engenharia Térmica e Fluidos da USP - Universidade de São Paulo, com uma seção de testes com 1500 metros e diâmetro de 51,2 mm. Especificamente, os resultados foram obtidos com escoamento monofásico de água. Os resultados mostram-se promissores, visto que o sistema de redes neurais artificiais foi capaz de discriminar 2 universos linearmente separáveis, para sinais de vazamento e de não vazamento, para diversas vazões e localizações de vazamentos simulados. / The present dissertation deals with the development of a system to identify abrupt leaks (ruptures) in pipelines, by analyzing the signal of fast response pressure sensors (cutoff frequency over then 1kHz). The recognition of the leak signal is established by an artificial neural network feed-forward Perceptron Multi Layer, previously trained. In the present work the implementation was performed off-line, but due to low computational costs, the neural network can be easily implemented in real time embedded electronics (online). The experimental results were obtained in a 1500 meter-long and 51.2 millimeter-diameter pilot pipeline at the Center of Thermal Engineering and Fluids. Specifically, the results were obtained with single-phase flow of water. The results have proven to be promising, as the trained neural network was capable of classifying the 2 types of signals into 2 linearly separable regions, for leakage signals and no leakage signals, for various flow rates and locations of simulated leaks.

Soft robots and particularly inflatable robots are of interest because they are lightweight, compact, robust to impact, and can interact with humans and their environment relatively safely compared to rigid and heavy traditional robots. Improved safety is due to their low mass that results in low-energy collisions and their compliant, soft construction. Inflatable robots (which are a type of soft robot) are also robust to impact and have a high torque to weight ratio. As a result inflatable robots may be used for many applications such as space exploration, search and rescue, and human-robot interaction. One of the potential problems with inflatable or pneumatically actuated robots is air leaking from the structural or actuation chambers. In this thesis methods are demonstrated to detect leaks in the structural and actuation chambers of inflatable and pneumatically actuated robots. It is then demonstrated that leaks can be slowed by lowering a target pressure which affects joint stiffness to prolong the life of the system. To demonstrate the effects of lowering the target pressure it is first shown that there exists a trade-off between the commanded target pressures at steady-state and the steady-state error at the robot end effector under normal operation. It is then shown that lowering the target pressure (which is related to stiffness) can extend the operational life of the system when compressed air is a limited resource. For actuator leaks a lower target pressure for the leaking joint is used to demonstrate the trade-off between slowing the leak rate and system performance. For structural leaks a novel control algorithm is demonstrated to lower target pressure as much as possible to slow the leak while maintaining a user specified level of accuracy. The method developed for structural leaks extends the operational life of the robot. Long-term error during operation is decreased by as much as 50% of the steady-state error at the end effector when compared to performance during a leak without the control algorithm. For actuation leaks in a joint with a high-torque load the possibility of a 30% increase in operation time while only increasing steady-state error by 2 cm on average is demonstrated. For a joint with a low-torque load it is shown that up to a 300% increase in operation time with less than 1 cm increased steady-state error is possible. The work presented in this thesis demonstrates that varying stiffness may be used to extend the operational life of a robot when a leak has occurred. The work discussed here could be used to extend the available operation time of pneumatic robots. The methods and principles presented here could also be adapted for use on other types of robots to preserve limited system resources (e.g., electrical power) and extend their operation time.

Advancement in infrared imaging technology has allowed the thermal imaging to detect and visualize several gases, mostly hydrocarbon gases. In addition, infrared cameras could potentially be used as a non-contact temperature measurement for gas and vapor. However, current application of infrared imaging techniques for gas measurements are still limited due to several uncertainties in their performance parameters. The aim of this research work was to determine the key factors in the application of infrared imaging technology for gas visualization and a non-contact temperature measurement. Furthermore, the concentration profile and emission rate of the gas are predicted by combining the application of the infrared imaging method with gas dispersion modeling. In this research, infrared cameras have been used to visualize liquefied natural gas (LNG) plumes from LNG spills on water. The analyses of the thermograms showed that the apparent temperatures were different from the thermocouple measurement which occurred due to the assumption of that the object emissivity was always equal to unity. The emissivity for pure methane gas and a mixture of methane and atmospheric gases were then evaluated in order to obtain the actual temperature distribution of the gas cloud. The results showed that by including the emissivity value of the gas, the temperature profile of the dispersed gas obtained from a thermal imaging measurement was in good agreement with the measurement using the thermocouples. Furthermore, the temperature distribution of the gas was compared to the concentration of a dispersed LNG vapor cloud to obtain a correlation between the temperature and the concentration of the cloud. Other application of infrared imaging technique was also conducted for leak detection of natural gas from a pipeline. The capability of an infrared camera to detect a fugitive gas leak was combined with the simulation of vapor discharge and dispersion in order to obtain a correlation between the emission rates and the sizes of the gas plume to the minimum detectable concentration. The relationship of the methane gas cloud size to the gas emission rate was highly dependent to the prevailing atmospheric condition. The results showed that the correlation were best to predict the emission rate less than 0.2 kg/s. At higher emission rate, the increase in gas release rate did not change the size of the cloud significantly.

The main frame of the distributed fiber optic leak detection system adopted the hybrid Mach-Zehnder & Sagnac interferomtric. We use the sensing fiber of In-Line frame to detect leak physical field. We can measure the position of the leak physical field through our sensing system and signal process system. In the cause of improving detective ability of leak detection system, we modify three elements of the system, including (1) the choice of the acoustic response of sensing fiber, (2) modification of the PZT phase modulator, and (3) modification of the PGC demodulator. The frame of our experiment is composed of the distributed fiber optic leak detection system and leak system of the fluid pipes. In which leak system of fluid pipes is designed the leaky frame of high-pressure fluid pipes. The main of experiment introduce the leak detection system to measure the leak acoustics of the fluid pipes. Then we can discuss the experimental result. The measurable minimum range of our distributed fiber optic leak detection system is3.3x10^-4(rad/¡ÔHz), and the dynamic range is above 75 dB. The dynamic range of this system can improve the original system to above 15 dB.