| Title |
Self-powering wireless devices for cloud manufacturing applications / |
| Authors |
Ostasevicius, V ; Jurenas, V ; Markevicius, V ; Gaidys, R ; Zilys, M ; Cepenas, M ; Kizauskiene, L |
| DOI |
10.1007/s00170-015-7617-x |
| Full Text |
|
| Is Part of |
International journal of advanced manufacturing technology.. London : Springer. 2016, vol. 83, iss. 9-12, p. 1937-1950.. ISSN 0268-3768. eISSN 1433-3015 |
| Keywords [eng] |
turning tool ; milling tool ; vibrations ; energy harvesting ; wireless transmission |
| Abstract [eng] |
Cloud manufacturing will play a significant role in future manufacturing, enabling companies to share resources and equipping them with scalable, flexible as well as cost-efficient manufacturing solutions with cheaper maintenance. With the main focus on cloud manufacturing, this paper aims to propose new devices for monitoring of manufacturing processes. The proposed self-powered wireless devices cover two main groups: rotating and non-rotating cutting tools. The most common rotating tool—mill—and non-rotating one—turning tool—are examined. Energy harvesting from the accelerations of the rotating cutting tool is mostly influenced by the speed of the tool and the number of cutting edges, while energy harvesting from the non-rotating tool is affected by the vibration modes of the tool. A significant difference between these two types of excitation frequencies obliges to use cantilever for energy harvesting from the rotating tool and disc-shaped piezoelectric harvesters for the non-rotating tool. The results of theoretical and experimental studies of the dynamics of these harvesters show an effective way for approaching their natural frequencies to the resonant frequencies of the cutting tools. The amplitude-frequency analysis of vibrations of the tool could be useful for the technological process monitoring as well as for the evaluation of machine tool state. Vibration and acoustic signal analysis using fast Fourier transform (FFT) enables to identify the level of tool wear and, moreover, the mode of tool fixture and technical state of the spindle. As the intensity of energy accumulation depends on the state of the cutting tool wear, it indicates and detects the tool condition. The voltage generated from the cutting tool vibrations of the harvester exponentially rises till the capacitor is fully charged and a wireless signal is sent to the receiver. All the proposed technique and methods are inseparable from cloud manufacturing technologies. |
| Published |
London : Springer |
| Type |
Journal article |
| Language |
English |
| Publication date |
2016 |
| CC license |
|
