An Implementation Method for an Inductive Proximity Sensor with an Attenuation Coefficient of 1

Yuyin Zhao, Yu Fang, Jiajun Yang, Weixuan Zhang, Xiaoxing Ge, Songyin Cao and Xiaonan Xia
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Yuyin Zhao: School of Information Engineering, Yangzhou University, Yangzhou 225100, China
Yu Fang: School of Information Engineering, Yangzhou University, Yangzhou 225100, China
Jiajun Yang: School of Information Engineering, Yangzhou University, Yangzhou 225100, China
Weixuan Zhang: School of Information Engineering, Yangzhou University, Yangzhou 225100, China
Xiaoxing Ge: School of Information Engineering, Yangzhou University, Yangzhou 225100, China
Songyin Cao: School of Information Engineering, Yangzhou University, Yangzhou 225100, China
Xiaonan Xia: School of Information Engineering, Yangzhou University, Yangzhou 225100, China

Energies, 2020, vol. 13, issue 24, 1-15

Abstract: In order to achieve long-distance measurement, a bridge differential inductance detection circuit is employed; on this basis, an automatic zero adjustment technique for sensors using an integral–proportional-integral controller is proposed in this work to achieve consistent product production and efficient installation and debugging, and the mathematical model of the bridge differential inductance detection circuit is established to effectively design the controller parameters. Furthermore, an implementation method for an inductive proximity sensor with an attenuation coefficient of 1 is also proposed based on the bridge differential inductance detection circuit by querying the proximity distance table in the field-programmable gate array (FPGA) to detect multiple target metal objects at the same inductive distance. Simulation and experimental results show that the proposed method is correct and effective.

Keywords: inductive proximity sensor; integral–proportional-integral controller; automatic zero adjustment technique (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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