Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

被引：0
作者：
Yu L. [1 ]
Wang H. [1 ]
Yue Y. [1 ]
Liu S. [1 ]
Mao X. [2 ]
Gu F. [3 ]
机构：
[1] Intelligent Sensing and Control of High-End Equipment Beijing International Science and Technology Cooperation Base, Beijing Information Science and Technology University, Beijing
[2] Machinery Technology Development Co, Ltd., Beijing
[3] Centre for Efficiency and Performance Engineering, University of Huddersfield, Queensgate, West Yorkshire, Huddersfield
来源：
SDHM Structural Durability and Health Monitoring | 2023年 / 17卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Condition monitoring; piezoelectric energy harvesting; self-powered; vibration acceleration sensor; wireless transmission;
D O I：
10.32604/sdhm.2022.024899
中图分类号：
学科分类号：
摘要：
In recent years, high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year. During the machining process, the high-end equipment failure may have a great impact on the product quality. It is necessary to monitor the status of equipment and to predict fault diagnosis. At present, most of the condition monitoring devices for mechanical equipment have problems of large size, low precision and low energy utilization. A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed. Based on rotor sensing technology, a sensor is made to mount on the tool holder and build the related circuit. Firstly, the energy management module collects the mechanical energy in the environment and converts the piezoelectric vibration energy into electric energy to provide 3.3 V for the subsequent circuit. The lithium battery supplies the system with additional power and monitors’ the power of the energy storage circuit in real-time. Secondly, a three-axis acceleration sensor is used to collect, analyze and filter a series of signal processing operations of the vibration signal in the environment. The signal is sent to the upper computer by wireless transmission. The host computer outputs the corresponding X, Y, and Z channel waveforms and data under the condition of the spindle speed of 50∼2500 r/min with real-time monitoring. The KEIL5 platform is used to develop the system software. The small-size piezoelectric vibration sensor with high-speed, high-energy utilization, high accuracy, and easy installation is used for spindle monitoring. The experiment results show that the sensor system is available and practical. © 2023 Tech Science Press. All rights reserved.
引用
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页码：315 / 336
页数：21
相关论文
共 25 条
  • [1] Isamu N., Ryo T., Keiichi S., Masahir O., Katsuyuki K., Development of innovative intelligent machine tool based on CAM-CNC integration concept–adaptive control based on predicted cutting force, International Journal of Automation Technology, 13, 3, (2019)
  • [2] Cheng X., Yao T. Q., Zhang Y. W., Liu Z. M., Analysis of the dynamic characteristics of the tool holder-spindle-bearing system considering the effects of joints dynamic parameters, Proceedings of the 8th International Conference on Vibration Engineering, pp. 150-157, (2021)
  • [3] Wei N., Wu J. P., Tang Y. X., Lu S. B., Wang L. N., Self-powered supercapacitor-mode tactile sensor based on polygonal litchi–like nanospheres decorated three-dimensional reduced graphene oxide aerogel for wearable electronics device, Journal of Power Sources, 479, (2020)
  • [4] Wang H. J., Gu Y. H., Wang M., Zhao C., Multi-source information fusion state recognition model for high-end CNC equipment, Chinese Journal of Instrumentation, 39, 4, pp. 61-66, (2018)
  • [5] Wang Y. P., Chen X. Z., Li L. Y., Research on machine tool spindle bearing fault diagnosis based on wavelet packet mixed features and support vector machine, Journal of Electronic Measurement and Instrumentation, 35, 2, pp. 59-64, (2021)
  • [6] Albarbar A., Mekid S., Starr A., Pietruszkiewicz R., Suitability of MEMS accelerometers for condition monitoring: An experimental study, Sensors, 8, 2, pp. 784-799, (2008)
  • [7] Abele E., Altinatas Y., Bercher C., Machine tool spindle units, CIRPAnnals-Manufacturing Technology, 59, 2, pp. 781-802, (2010)
  • [8] Mones Z., Feng G., Ogbulaor U. E., Wang T., Gu F., Et al., Performance evaluation of wireless MEMS accelerometer for reciprocating compressor condition monitoring, Proceedings of the International Conference on Power Transmissions, pp. 893-900, (2016)
  • [9] Han Y. D., Li Z., Data acquisition and preprocessing of MEMS accelerometer, Instrument Technology and Sensors, 2, pp. 16-19, (2015)
  • [10] Kaneta R., Hasegawa T., Kido J., Abe T., Sohgawa M., Redesigned microcantilevers for sensitivity improvement of microelectromechanical system tactile sensors, Journal of Robotics and Mechatronics, 34, 3, (2022)
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