Anpassung der Teileitermethode auf 3-D-Freileitungsmodelle zur Berechnung der induktiven Beeinflussung

Bei Montagearbeiten auf Freileitungsmasten in der Nähe von unter Spannung stehenden Leitern stellen die dabei auftretende induktive und kapazitive Beeinflussung durch elektrische und magnetische Felder eine Gefährdung für das Montagepersonal dar. Es wird eine Methode vorgestellt, mit der die Beeinflussung bei beliebig angeordneten Leiterstrukturen berechnet werden kann. Aus dem Berechnungsbeispiel wird deutlich, dass sich das vorgestellte Verfahren für die Berechnung von induzierten Spannungen von Hochspannungsfreileitungen eignet. Mit dem Modell kann der Einfluss von Erdungsmaßnahmen, Seilzugreihenfolge, Seilzugrichtung auf induzierte Spannungen (fließende Ströme) untersucht werden. Durch die Möglichkeit zur Berechnung der Berührungsspannung während des Seilzuges liefert das vorgestellte Berechnungsverfahren einen Beitrag zum Bewerten von möglichen Gefährdungspotenzialen beim Freileitungsbau oder anderen Montagearbeiten. Des Weiteren kann mit der 3-D-Teilleitermethode eine Vielzahl von andern Anwendungen berechnet werden, da durch die Möglichkeit des punktuellen sehr genauen Diskretisierens eine hohe Genauigkeit bei gleichzeitig überschaubarem Berechnungsaufwand möglich ist. Mögliche Anwendungsgebiete sind z.B. die Berechnung der Beeinflussung von Telekommunikationsanlagen oder die von Berechnung Stromwärmeverlusten durch Erdungsanlagen

A Tuned-RF Duty-Cycled Wake-Up Receiver with −90 dBm Sensitivity

A novel wake-up receiver for wireless sensor networks is introduced. It operates with a modified medium access protocol (MAC), allowing low-energy consumption and practical latency. The ultra-low-power wake-up receiver operates with enhanced duty-cycled listening. The analysis of energy models of the duty-cycle-based communication is presented. All the WuRx blocks are studied to obey the duty-cycle operation. For a mean interval time for the data exchange cycle between a transmitter and a receiver over 1.7 s and a 64-bit wake-up packet detection latency of 32 ms, the average power consumption of the wake-up receiver (WuRx) reaches down to 3 μ W . It also features scalable addressing of more than 512 bit at a data rate of 128 k bit / s −1. At a wake-up packet error rate of 10 − 2 , the detection sensitivity reaches a minimum of − 90 dBm . The combination of the MAC protocol and the WuRx eases the adoption of different kinds of wireless sensor networks. In low traffic communication, the WuRx dramatically saves more energy than that of a network that is implementing conventional duty-cycling. In this work, a prototype was realized to evaluate the intended performance

Design and Implementation of Low Noise Amplifier Operating at 868 MHz for Duty Cycled Wake-Up Receiver Front-End

The integration of wireless communication, e.g., in real- or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, quality of service, and reliability. The improvement of wireless sensor networks (WSN) performance starts by enhancing the capabilities of each sensor node. To minimize latencies without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works since they can be always-on or power-gated with short latencies by a power consumption in the range of some microwatts. Compared to standard receiver technologies, they are usually characterized by drawbacks in terms of sensitivity. To overcome the limitation of the sensitivity of WuRxs, a design of a low noise amplifier (LNA) with several design specifications is required. The challenging task of the LNA design is to provide equitable trade-off performances such as gain, power consumption, the noise figure, stability, linearity, and impedance matching. The design of fast settling LNA for a duty-cycled WuRx front-end operating at a 868 MHz frequency band is investigated in this work. The paper details the trade-offs between design challenges and illustrates practical considerations for the simulation and implementation of a radio frequency (RF) circuit. The implemented LNA competes with many commercialized designs where it reaches single-stage 12 dB gain at a 1.8 V voltage supply and consumes only a 1.6 mA current. The obtained results could be made tunable by working with off-the-shelf components for different wake-up based application exigencies

Limitation of Deep-Learning Algorithm for Prediction of Power Consumption

In recent years, electricity consumption has become high due to the use of several domestic applications in the house. On the other hand, there is a trend of using renewable energy in many houses, such as solar energy, energy-storage systems and electric vehicles. For this reason, forecasting household electricity consumption is essential for managing and planning energy use. Forecasting power consumption is a difficult time-series-forecasting task. Additionally, the electrical load has irregular trend elements, which makes it very difficult to predict the demand for electrical energy using simple forecasting techniques. Therefore, several researchers have worked on intelligent algorithms such as machine-learning and deep-learning algorithms to find a solution for this problem. In this work, we demonstrate that deep-learning algorithms are not always reliable and accurate in predicting power consumption

Wake-Up Receiver-Based Routing for Clustered Multihop Wireless Sensor Networks

The Wireless Sensor Network (WSN) is one of the most promising solutions for the supervision of multiple phenomena and for the digitisation of the Internet of Things (IoT). The Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained networks. This technology allows energy-autonomous on-demand communication for continuous monitoring instead of the conventional radio. The routing process is one of the most energy and time-consuming processes in WSNs. It is, hence, crucial to conceive an energy-efficient routing process. In this paper, we propose a novel Wake-up Receiver-based routing protocol called Clustered WuRx based on Multicast wake-up (CWM), which ensures energy optimisation and time-efficiency at the same time for indoor scenarios. In our proposed approach, the network is divided into clusters. Each Fog Node maintains the routes from each node in its cluster to it. When a sink requires information from a given node, it’s corresponding Fog Node uses a multicast wake-up mechanism to wake up the intended node and all the intermediate nodes that will be used in the routing process simultaneously. Measurement results demonstrate that our proposed approach exhibits higher energy efficiency and has drastic performance improvements in the delivery delay compared with other routing protocols

Analytical and Experimental Performance Analysis of Enhanced Wake-Up Receivers Based on Low-Power Base-Band Amplifiers

With the introduction of Internet of Things (IoT) technology in several sectors, wireless, reliable, and energy-saving communication in distributed sensor networks are more important than ever. Thereby, wake-up technologies are becoming increasingly important as they significantly contribute to reducing the energy consumption of wireless sensor nodes. In an indoor environment, the use of wireless sensors, in general, is more challenging due to signal fading and reflections and needs, therefore, to be critically investigated. This paper discusses the performance analysis of wakeup receiver (WuRx) architectures based on two low frequency (LF) amplifier approaches with regard to sensitivity, power consumption, and package error rate (PER). Factors that affect systems were compared and analyzed by analytical modeling, simulation results, and experimental studies with both architectures. The developedWuRx operates in the 868MHz band using on-off-keying (OOK) signals while supporting address detection to wake up only the targeted network node. By using an indoor setup, the signal strength and PER of received signal strength indicator (RSSI) in different rooms and distances were determined to build a wireless sensor network. The results show a wake-up packets (WuPts) detection probability of about 90% for an interior distance of up to 34 m

Multivariable Adaptive Neural Control Based on Multimodel Emulator for Nonlinear Square MIMO Systems

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