5,228 research outputs found

    Energy Harvesting Based Wireless Sensor Nodes for The Monitoring Temperature of Gearbox

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    Temperatures are effective indicators of the health of many ma-chines such as the wind turbine gearboxes, bearings, engines, etc. This paper pre-sents a novel wireless temperature sensor node powered by a thermal harvester for monitoring the status of gearboxes. A thermoelectric generator module (TEG) is optimized to harvest the electrical power from a heat source such as the gear-box undergoing such monitoring. The power generation from this method is ob-tained based on temperature gradients emanated by sandwiching the TEG be-tween the two aluminum plates. One plate is exposed to the heat source and has the role of a heat collector, whereas the other plate, mounted with a low profile heat-sink, acts as a heat spreader. The harvested power is then used to power a wireless temperature node for condition monitoring, resulting in a powerless and wireless monitoring system. To evaluate the system, an industrial gearbox is monitored by the designed temperature node. The node is fabricated using a TEG module; an LTC3108 DC-DC converter for boosting the voltage, a super-capacitor for energy storage and a CC2650 sensor tag for measuring the temperature of the gearbox. The temper-ature data is transferred via the Bluetooth Low Energy and then monitored using portable monitoring devices, such as a mobile phones. The results obtained show the system can provide a continuous monitoring of the temperature information

    A Survey of Multi-Source Energy Harvesting Systems

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    Energy harvesting allows low-power embedded devices to be powered from naturally-ocurring or unwanted environmental energy (e.g. light, vibration, or temperature difference). While a number of systems incorporating energy harvesters are now available commercially, they are specific to certain types of energy source. Energy availability can be a temporal as well as spatial effect. To address this issue, ‘hybrid’ energy harvesting systems combine multiple harvesters on the same platform, but the design of these systems is not straightforward. This paper surveys their design, including trade-offs affecting their efficiency, applicability, and ease of deployment. This survey, and the taxonomy of multi-source energy harvesting systems that it presents, will be of benefit to designers of future systems. Furthermore, we identify and comment upon the current and future research directions in this field

    In-Network Distributed Solar Current Prediction

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    Long-term sensor network deployments demand careful power management. While managing power requires understanding the amount of energy harvestable from the local environment, current solar prediction methods rely only on recent local history, which makes them susceptible to high variability. In this paper, we present a model and algorithms for distributed solar current prediction, based on multiple linear regression to predict future solar current based on local, in-situ climatic and solar measurements. These algorithms leverage spatial information from neighbors and adapt to the changing local conditions not captured by global climatic information. We implement these algorithms on our Fleck platform and run a 7-week-long experiment validating our work. In analyzing our results from this experiment, we determined that computing our model requires an increased energy expenditure of 4.5mJ over simpler models (on the order of 10^{-7}% of the harvested energy) to gain a prediction improvement of 39.7%.Comment: 28 pages, accepted at TOSN and awaiting publicatio

    Performance testing of a low power consumption wireless sensor communication system integrated with an energy harvesting power source

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    This paper presents the performance testing results of a wireless sensor communication system with low power consumption integrated with a vibration energy harvesting power source. The experiments focus on the system’s capability to perform continuous monitoring and to wirelessly transmit the data acquired from the sensors to a user base station, completely battery-free. Energy harvesting technologies together with system design optimisation for power consumption minimisation ensure the system’s energy autonomous capability demonstrated in this paper by presenting the promising testing results achieved following its integration with Structural Health Monitoring (SHM) and Body Area Network (BAN) applications

    Resource Aware Sensor Nodes in Wireless Sensor Networks

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    Wireless sensor networks are continuing to receive considerable research interest due, in part, to the range of possible applications. One of the greatest challenges facing researchers is in overcoming the limited network lifetime inherent in the small locally powered sensor nodes. In this paper, we propose IDEALS, a system to manage a wireless sensor network using a combination of information management, energy harvesting and energy monitoring, which we label resource awareness. Through this, IDEALS is able to extend the network lifetime for important messages, by controlling the degradation of the network to maximise information throughput
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