• Smart Structures and Systems
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• v.1 no.2
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• pp.121-140
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• 2005

This paper presents a systematic investigation of the effect of sensor location on the data quality and subsequently, on the effectiveness of machine health monitoring. Based on an analysis of the signal propagation process from the defect location to the sensor, numerical simulations using finite element modeling were conducted on a bearing test bed to determine the signal strength at several representative sensor locations. The results showed that placing sensors closely to the machine component being monitored is critical to achieving high signal-to-noise ratio, thus improving the data quality. Using millimeter-sized piezoceramic plates, the obtained results were evaluated experimentally. A comparison with a set of commercial vibration sensors verified the developed structural dynamics-based sensor placement strategy. It further demonstrated that the proposed shock wave-based sensing technique provided an effective alternative to vibration measurement, while requiring less space for sensor installation.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.278-279
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• 2018

Due to the frequent occurrence of dangerous wild animals in rural or mountainous areas. it has been increasing damage of crops in every year. Fight bell or electric fence is typically installed to chase those wild animals. But there are problems that it is impossible to drive out birds and spends high installation and maintenance cost. In addition, it is inefficient to the risk of electric shock effect. In this study, the proposed system can drive out hazardous wildlife and birds regardless of installation location through realtime detection with the multi-sensing based IoT platform technology. This study showed a very large significance effect that can reduce crop damage by wildlife and birds.