System Design of Three-coordinate Dynamic Synchronous Tester Based on STM32

Wenqiang Li; Ke Ouyang; Zhongtao Cao; Jin Chen

doi:10.54097/bsjbqp25

Authors

Wenqiang Li
Ke Ouyang
Zhongtao Cao
Jin Chen

DOI:

https://doi.org/10.54097/bsjbqp25

Keywords:

STM32, magnetic encoder, three coordinate tester, TCA9548A, AS5600 magnetic encoder.

Abstract

In this paper, a three-coordinate dynamic synchronous tester system based on STM32 is developed. STM32F103C8T6 chip is used as the control system. The control system mainly consists of three modules: motion control module, magnetic encoder measurement module and displacement data collection module. The STM32 main control controls the three-axis stepper table to move according to the specified instructions, the AS5600 magnetic encoder is used to measure the data of the three-way stepper motor, and the TCA9548A module is used to expand the IIC channel and realize the communication between the STM32 and the host computer, and the data is transmitted to the host computer through serial communication. The test results show that the system meets the needs of the existing domestic industrial level, the cost is moderate, the performance is reliable and the operation is simple, and meets the practical application requirements.

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References

[1] J. H. Robert, H. P. Paulo. Coordinate measuring machines and systems[M]. Boca Raton: CRC Press, 2016:18-21.

[2] Z. Qin, Y. Lu. Self-organizing manufacturing network: A paradigm towards smart manufacturing in mass personalization[J]. Journal of Manufacturing Systems, 2021,60:35-47.

[3] W Liu,X Li．Binocular-vision—based error detection system and identification method for 5 PIGEs of rotary axis in five-axis machine tool[J]．Precision Engineering,2017,1:208-222．

[4] J. H. Robert, H. P. Paulo. Coordinate measuring machines and systems[M]. Boca Raton: CRC Press, 2016:18-21.

[5] Z. Qin, Y. Lu. Self-organizing manufacturing network: Aparadigm towards smart manufacturing in mass personalization[J]. Journal of Manufacturing Systems, 2021, 60:35-47.

[6] STOJADINOVICSM, MAJSTOROVICVD, DURAKBASANM, et al. Towards anIntelligent Approach for CMM Inspection Planning of PrismaticParts[J]. Measurement. 2016,92：326-339．

[7] Zou H B,Ding YJ,Zhang J,et al.Precise geometric error model based on z-axis motion platform of micro v-groove machine tools[J].The International Journal of Advanced Manufacturing Technology,2017,92(9-12):3219-3224.