Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

Lei Yu, Hongjun Wang, Yubin Yue, Shucong Liu, Xiangxiang Mao, Fengshou Gu

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)315-336
Number of pages22
JournalSDHM Structural Durability and Health Monitoring
Issue number4
Publication statusPublished - 2 Aug 2023

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