The Application of Wireless Sensor Networks to In-Service Motor Monitoring and Energy Management

Hu, Jingtao

doi:10.1109/icinis.2008.30

Cited by 9 publications

(3 citation statements)

References 2 publications

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“…Hu [34,35] presents a DSP-based system for motor monitoring using the air-gap torque method and WSN for data transmission. The estimation of various parameters such as power factor, efficiency, speed, and torque was proposed.…”

Section: Motor Monitoring Systemsmentioning

confidence: 99%

On the Impact of Local Processing for Motor Monitoring Systems in Industrial Environments Using Wireless Sensor Networks

Gomes

Adissi

Filho

et al. 2013

International Journal of Distributed Sensor Networks

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This paper presents a theoretical study for verifying the impact of using smart nodes in motor monitoring systems in industrial environments employing Wireless Sensor Networks (WSNs). Structured cabling and sensor deployment are usually more expensive than the cost of the sensors themselves. Besides the high cost, the wired approach offers little flexibility, making the network deployment and maintenance a complex process. In this context, wireless networks present a number of advantages compared to wired networks as, for example, the ease and speed of deployment and maintenance and the associated low cost. However, WSNs have several limitations, such as the low bandwidth and unreliability, especially in harsh environments (e.g., industrial plants). This paper presents a theoretical study on the performance of WSNs for motor monitoring applications in industrial environments, taking into account WSNs' characteristics (i.e., unreliability and communication and processing latency). The results obtained through mathematical models were analyzed together with experimental results, and it was demonstrated that employing intelligent nodes with local processing capabilities is essential for the applications under consideration, because it reduces the amount of data transmitted over the network allowing monitoring even in scenarios with high interference rate, paying off the extra latency resulting from local processing.

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Section: Motor Monitoring Systemsmentioning

confidence: 99%

On the Impact of Local Processing for Motor Monitoring Systems in Industrial Environments Using Wireless Sensor Networks

Gomes

Adissi

Filho

et al. 2013

International Journal of Distributed Sensor Networks

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show abstract

“…In recent decade, Wireles Sensor Networks (WSNs) have been improved and applied popularly in many fields because of low cost, low power consumption, small size and short transmission distance [1][2][3][4]. Hence, the ZigBee standard has been proposed to satisfy these requirements to achieve the goal of longer lifetime with higher reliability [5].…”

Section: Introductionmentioning

confidence: 99%

An efficient GTS allocation scheme for IEEE 802.15.4 MAC layer

Huang

Lee

2013

COMSIS J

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Based on IEEE 802.15.4, the contention-free period (CFP) adopts a guarantee time slot (GTS) mechanism to ensure each device can access the radio channel. However, it is hard to get the authority to access the radio channel due to more competitor access the radio channel simultaneously. To cope with this issue, we proposed a guarantee time slot mechanism to enhance the performance and utilization by using CFP. Our proposed method ensures each device has the authority to access the radio channel without any additional step. By comparing with the method of IEEE 802.15.4, the experimental results show that data average transmission delay and energy consumption can be reduced dramatically. In addition, the bandwidth and performance of network is improved since the pre-allocation mechanism can reduce the number of control packets. Several experiments have been conducted to demonstrate the performance of our work.

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“…Some examples of these application like robotic navigation Fu et al (2009), aircraft corrosion monitoring Demo et al (2010) , direct load control in residential areas Molina-Garcia et al (2007), personal mobile physiological monitoring and management system for chronic disease Toh et al (2008), Wildfire detection Antoine-Santoni et al (2006), www.intechopen.com in-service motor monitoring and energy management Hu (2008), application in petrochemical industry Ke et al (2008), application for critical infrastructure risk analysis of fossil fuelled power stations Isreb (2006) and tactical military applications Lee et al (2009) can be found in the litrature.…”

Section: Wireless Sensor Network Applicationsmentioning

confidence: 99%

Wireless Sensor Networks: Modelling and Simulation

Mahlknecht¹,

Madani²,

Kazmi³

2010

Discrete Event Simulations

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Although different modeling techniques have been proposed during the last 300 years, the differential equation formalism proposed by Newton and Leibniz has been the tool of choice for modeling and problem solving Taylor (1996);Wainer (2009). Differential equations provide a formal mathematical method (sometimes also called an analytical method) for studying the entity of interest. Computational methods based on differential equations could not be easily applied in studying human-made dynamic systems (e.g., traffic controllers, robotic arms, automated factories, production plants, computer networks, VLSI circuits). These systems are usually referred to as discrete event systems because their states do not change continuously but, rather, because of the occurrence of events. This makes them asynchronous, inherently concurrent, and highly nonlinear, rendering their modeling and simulation different from that used in traditional approaches. In order to improve the model definition for this class of systems, a number of techniques were introduced, including Petri Nets, Finite State Machines, min-max algebra, Timed Automata, etc. Banks & Nicol. (2005) (2000); Toffoli & Margolus. (1987). Wireless Sensor Network (WSN) is a discrete event system which consists of a network of sensor nodes equipped with sensing, computing, power, and communication modules to monitor certain phenomenon such as environmental data or object tracking Zhao & Guibas (2004). Emerging applications of wireless sensor networks are comprised of asset and warehouse * madani@ciit.net.pk † jawhaikaz@ciit.net.pk ‡ mahlknecht@ict.tuwien.ac.at 1 www.intechopen.com management, automotive, home and building automation, civil infrastructure monitoring, healthcare, industrial process control, military battlefield awareness, and security and surveillance Cerpa et al. (2001). As discussed earlier, modeling and simulation is a mean to verify the working and to measure the effectiveness of the different techniques proposed for WSNs. Analytical modeling provides quick insight for the techniques developed for WSNs but fail to give realistic results because of WSN specific constraints like limited energy and sheer number of sensor nodes Chen et al. (2006). Real world implementation and test beds are the most accurate method to verify the concepts but are restricted by costs, effort, and time factors as well as repeating environmental conditions is also not possible Zeigler (1976). Simulations provide a good approximation to verify different schemes and applications developed for WSNs at low cost and in less time. To have credible results through simulation, the choice of models and the simulation environment is important. There is always a tradeoff between credible simulation results and the time required to get these simulation results. The results always depend upon the level of abstraction of the models. The more detailed is the model, the better the accuracy of results but higher the amount of time required for simulation. The models used for simulation ...

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The Application of Wireless Sensor Networks to In-Service Motor Monitoring and Energy Management

Abstract: Abstract

Cited by 9 publications

References 2 publications

On the Impact of Local Processing for Motor Monitoring Systems in Industrial Environments Using Wireless Sensor Networks

On the Impact of Local Processing for Motor Monitoring Systems in Industrial Environments Using Wireless Sensor Networks

An efficient GTS allocation scheme for IEEE 802.15.4 MAC layer

Wireless Sensor Networks: Modelling and Simulation

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