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Open Access

Real-time FPGA-LabVIEW homebuilt system for noise reduction in AFM imaging

Qiuyuan SUN1,2,3Zhifei YAO1,2,4Jianheng SUN1,2,3Bohui ZHAO1,2,4Ketong ZHANG1,2,3Haoran YAO1,2,3Jiuyan WEI1,2,3Huanfei WEN1,2,4Jun TANG1,2,3Zongmin MA1,2,3( )Jun LIU1,2,4
State Key Laboratory of Widegap Semiconductor Optoelectronic Materials and Technologies, North University of China, Taiyuan 030051, China
Key Lab of Quantum Sensing and Precision Measurement, Taiyuan 030051, China
School of Semiconductors and Physics, North University of China, Taiyuan 030051, China
School of Instrument and Electronics, North University of China, Taiyuan 030051, China
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Abstract

Atomic force microscopy (AFM) probe vibration monitoring is essential for achieving accurate nanoscale imaging and reliable signal interpretation. This paper presents a low-noise vibration detection method based on a real-time FPGA-LabVIEW homebuilt system. The FPGA receives signals from a quadrant photodiode (QPD), performs analog-to-digital conversion and parallel processing, and integrates cascaded digital filters for noise reduction. A finite impulse response (FIR) low-pass filter extracts the static spot position, while an infinite impulse response (IIR) band-pass filter preserves the probe’s resonance vibrations. Compared with conventional analog detection, the proposed system reduces background noise by approximately 50% (measured as 50.23%), enhances the signal-to-noise ratio (SNR) from 15 dB to 20 dB, and maintains FPGA signal-processing latency below 5 μs. This work demonstrates that the proposed real-time FPGA-LabVIEW AFM noise optimization system significantly improves signal-to-noise ratio and real-time performance, providing a practical solution for high-precision, low-noise AFM imaging.

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Journal of Measurement Science and Instrumentation
Pages 355-366

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Cite this article:
SUN Q, YAO Z, SUN J, et al. Real-time FPGA-LabVIEW homebuilt system for noise reduction in AFM imaging. Journal of Measurement Science and Instrumentation, 2026, 17(2): 355-366. https://doi.org/10.62756/jmsi.1674-8042.2026030

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Received: 12 January 2026
Revised: 07 March 2026
Accepted: 24 April 2026
Published: 01 June 2026
© The Author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.