"Detección de fallas de sensado en convertidores CA/CC para micro-redes híbridas usando análisis de componentes principales (PCA)"

El presente trabajo académico de investigación propone un método basado en Análisis de Componentes Principales (PCA) para la detección de fallas en sensores relacionado con control local de conversores de voltaje CA/CC en una Micro-red (MR) con posibilidad de acoplamiento a la red. Con el fin de conseguir lo antes mencionado se realiza una simulación de una Micro-red con variedad de cargas (lineales y no lineales) y generadores tanto convencionales como renovables, así como elementos de almacenamiento que en conjunto poseen sistemas de CC y CA con sus respectivos conversores. Los investigadores proponen dos escenarios de falla y un escenario de operación normal que sirve de referencia para llevar a cabo los análisis mencionados. Como resultado de lo antes mencionado se ha implementado un algoritmo que a partir de los componentes principales de las clases mencionados calcula diferencias entre los espacios obtenidos a partir de un total de 195 variables recolectadas en todas las barras del sistema, además del sensado para control local. Las observaciones obtenidas son alrededor de 145000 tomas de valores.The present academic research work proposes a method based on Principal Component Analysis (PCA) for the detection of failures in sensors related to local control of AC / DC voltage converters in a micro-grid (MR) with the possibility of coupling to the net. In order to achieve the aforementioned, a simulation of a micro-grid is carried out with a variety of loads (linear and nonlinear) and both conventional and renewable generators, as well as storage elements that together have DC and AC systems with their respective converters. The researchers propose two failure scenarios and a normal operating scenario that serves as a reference to carry out the aforementioned analyzes. As a result of the aforementioned, an algorithm has been implemented that, based on the main components of the mentioned cases, calculates differences between the spaces obtained from a total of 195 variables collected in all the bars of the system, in addition to the sensing for local control. The observations obtained are around 145000 value takes

Electrical and Computer Engineering Annual Report 2017

Early Career Awards Faculty Directory Faculty Highlights Special Report: Mobility at Michigan Tech Faculty Publications Staff Profile & Directory Graduate Student Research Accelerated Master\u27s Degree Graduate Student Awards & Degrees Undergraduate Highlights Senior Design Enterprise Undergraduate Student Awards & Advisory Grants & Contracts Departmental Statistics A Pioneer\u27s Storyhttps://digitalcommons.mtu.edu/ece-annualreports/1001/thumbnail.jp

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

DC Power Line Communication (PLC) on 868 MHz and 2.4 GHz Wired RF Transceivers

Efficient management through monitoring of Li-ion batteries is critical to the progress of electro-mobility and energy storage globally, since the technology can be hazardous if pushed beyond its safety boundaries. Battery management systems (BMSs) are being actively improved to reduce size, weight, and cost while increasing their capabilities. Using power line communication, wireless monitoring, or hybrid data links are one of the most advanced research directions today. In this work, we propose the use of radio frequency (RF) transceivers as a communication unit that can deliver both wired and wireless services, through their superior analog and digital signal processing capability compared to PLC technology. To validate our approach computational simulation and empirical evaluation was conducted to examine the possibility of using RF transceivers on a direct current (DC) bus for wired BMS. A key advantage of this study is that it proposes a flexible and tested system for communication across a variety of network scenarios, where wireless data links over disrupted connections may be enabled by using this technology in short-range wired modes. This investigation demonstrates that the IEEE 802.15.4-compliant transceivers with operating frequencies of 868 MHz and 2.4 GHz can establish stable data links on a DC bus via capacitive coupling at high data rates

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

IoT in smart communities, technologies and applications.

Internet of Things is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The Internet of Things (IoT) for Smart Cities has many different domains and draws upon various underlying systems for its operation, in this work, we provide a holistic coverage of the Internet of Things in Smart Cities by discussing the fundamental components that make up the IoT Smart City landscape, the technologies that enable these domains to exist, the most prevalent practices and techniques which are used in these domains as well as the challenges that deployment of IoT systems for smart cities encounter and which need to be addressed for ubiquitous use of smart city applications. It also presents a coverage of optimization methods and applications from a smart city perspective enabled by the Internet of Things. Towards this end, a mapping is provided for the most encountered applications of computational optimization within IoT smart cities for five popular optimization methods, ant colony optimization, genetic algorithm, particle swarm optimization, artificial bee colony optimization and differential evolution. For each application identified, the algorithms used, objectives considered, the nature of the formulation and constraints taken in to account have been specified and discussed. Lastly, the data setup used by each covered work is also mentioned and directions for future work have been identified. Within the smart health domain of IoT smart cities, human activity recognition has been a key study topic in the development of cyber physical systems and assisted living applications. In particular, inertial sensor based systems have become increasingly popular because they do not restrict users’ movement and are also relatively simple to implement compared to other approaches. Fall detection is one of the most important tasks in human activity recognition. With an increasingly aging world population and an inclination by the elderly to live alone, the need to incorporate dependable fall detection schemes in smart devices such as phones, watches has gained momentum. Therefore, differentiating between falls and activities of daily living (ADLs) has been the focus of researchers in recent years with very good results. However, one aspect within fall detection that has not been investigated much is direction and severity aware fall detection. Since a fall detection system aims to detect falls in people and notify medical personnel, it could be of added value to health professionals tending to a patient suffering from a fall to know the nature of the accident. In this regard, as a case study for smart health, four different experiments have been conducted for the task of fall detection with direction and severity consideration on two publicly available datasets. These four experiments not only tackle the problem on an increasingly complicated level (the first one considers a fall only scenario and the other two a combined activity of daily living and fall scenario) but also present methodologies which outperform the state of the art techniques as discussed. Lastly, future recommendations have also been provided for researchers