Fault Diagnosis Of Sensor And Actuator Faults In Multi-Zone Hvac Systems

Globally, the buildings sector accounts for 30% of the energy consumption and more than 55% of the electricity demand. Specifically, the Heating, Ventilation, and Air Conditioning (HVAC) system is the most extensively operated component and it is responsible alone for 40% of the final building energy usage. HVAC systems are used to provide healthy and comfortable indoor conditions, and their main objective is to maintain the thermal comfort of occupants with minimum energy usage. HVAC systems include a considerable number of sensors, controlled actuators, and other components. They are at risk of malfunctioning or failure resulting in reduced efficiency, potential interference with the execution of supervision schemes, and equipment deterioration. Hence, Fault Diagnosis (FD) of HVAC systems is essential to improve their reliability, efficiency, and performance, and to provide preventive maintenance. In this thesis work, two neural network-based methods are proposed for sensor and actuator faults in a 3-zone HVAC system. For sensor faults, an online semi-supervised sensor data validation and fault diagnosis method using an Auto-Associative Neural Network (AANN) is developed. The method is based on the implementation of Nonlinear Principal Component Analysis (NPCA) using a Back-Propagation Neural Network (BPNN) and it demonstrates notable capability in sensor fault and inaccuracy correction, measurement noise reduction, missing sensor data replacement, and in both single and multiple sensor faults diagnosis. In addition, a novel on-line supervised multi-model approach for actuator fault diagnosis using Convolutional Neural Networks (CNNs) is developed for single actuator faults. It is based a data transformation in which the 1-dimensional data are configured into a 2-dimensional representation without the use of advanced signal processing techniques. The CNN-based actuator fault diagnosis approach demonstrates improved performance capability compared with the commonly used Machine Learning-based algorithms (i.e., Support Vector Machine and standard Neural Networks). The presented schemes are compared with other commonly used HVAC fault diagnosis methods for benchmarking and they are proven to be superior, effective, accurate, and reliable. The proposed approaches can be applied to large-scale buildings with additional zones

More on the holographic Ricci dark energy model: smoothing Rips through interaction effects?

The background cosmological dynamics of the late Universe is analysed on the framework of a dark energy model described by an holographic Ricci dark energy component. Several kind of interactions between the dark energy and the dark matter components are considered herein. We solve the background cosmological dynamics for the different choices of interactions with the aim to analyse not only the current evolution of the universe but also its asymptotic behaviour and, in particular, possible future singularities removal. We show that in most of the cases, the Big Rip singularity, a finger print of this model in absence of an interaction between the dark sectors, is substituted by a de Sitter or a Minkowski state. Most importantly, we found two new {\textit{ future}} bouncing solutions leading to two possible asymptotic behaviours, we named Little Bang and Little Sibling of the Big Bang. At a Little Bang, as the size of the universe shrinks to zero in an infinite cosmic time, the Hubble rate and its cosmic time derivative blow up. In addition, at a Little sibling of the Big Bang, as the size of the universe shrinks to zero in an infinite cosmic time, the Hubble rate blows up but its cosmic time derivative is finite. These two abrupt events can happen as well in the past.Comment: 10 pages, Shortened and improved versio

The Soft-Path Approach for Sustainable Water Management: An Analysis of Its Suitability in Abu Dhabi

In Abu Dhabi, rapid population growth, exponential changes in lifestyle, steady depletion of natural resources, and increased reliance on desalinated water require stringent water regulation regime to secure a sustainable water future. The government of Abu Dhabi, in an attempt to regulate water usage, introduced or increased water tariff, in 2015, but did not achieve much success in reducing water use. The purpose of this research is to analyze a possible alternative approach to sustainable water governance in Abu Dhabi – (the ‘soft-path approach’). This thesis outlines the water situation and need for sustainable water management in Abu Dhabi, discusses the theoretical basis and importance of the ‘soft-path approach’ in water management, and analyzes the applicability and institutional capability of the ‘soft-path approach’ in Abu Dhabi. The work is based on a comprehensive study of the relevant government documents, academic literature, and the evaluation of responses from several key personnel in the water sector in Abu Dhabi. The study reveals that Abu Dhabi water sector has embraced different aspects of the four principles of the ‘soft-path approach’ to water management. But it notes some deficiencies in the six dimensions of institutional capacity in implementing ‘the soft path’ in Abu Dhabi and provides recommendations

Birth weight pattern and factors affecting birth weight in urban areas of South-Western Ethiopia

Abstract: A community-based cross-sectional study of birth-weight was carried out in 30 villages of Jimma Zone, to determine the pattern of birth weight, its relationship with ante-natal care, and the influencing factors in birth-weight. A total of 537 mother-newborn pairs were included in the study revealing an overall low birth weight rate of 10.6%. About 72% of the mothers were booked for ante-natal care during the current pregnancy, and 332 (86%) of the deliveries were attended by trained personnel, including trained traditional birth attendants. Mean birth-weight for both sexes was 3,202 grams; and there was no statistically significant difference between the sexes (P>0.05). Higher mean birth weight was observed for newborns whose mothers attended ante-natal clinic and whose births were attended by trained personnel than those mothers without ante-natal care and unattended by trained personnel (P<0.05). Low birth weight was associated with being single, poor, without ante-natal care and not attended by trained personnel during delivery. Efforts to increase the utilization of ante-natal care services is recommended to minimize the risk of low birth-weight as it will help the timely correction of factors predicting low birth weight. [Ethiop. J. Health Dev. 1998;12(1):33-37

Virtual networks for exchanging information and biomaterials: future directions

Clinical and research networks for rare conditions are increasingly common nowadays. Given the rarity of many such conditions, there is a need to cover more conditions, yet there is also a need to sustain and improve the quality and effectiveness of existing networks. This review will discuss the qualities that are required by a virtual network using some international clinical and research networks that are currently active in the field of rare endocrine conditions affecting sex and adrenal development as exemplars