Engieering and Technology

Automatic Digital Inclinometer Calibration System Based on Image Recognition

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  • 1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. Shanghai Institute of Quality Inspection and Technical Research, Shanghai 200072, China

Accepted date: 2022-11-12

  Online published: 2025-03-21

Abstract

Traditional calibration method for the digital inclinometer relies on manual inspection, and results in its disadvantages of complicated process, low-efficiency and human errors easy to be introduced. To improve both the calibration accuracy and efficiency of digital inclinometer, an automatic digital inclinometer calibration system was developed in this study, and a new display tube recognition algorithm was proposed. First, a high-precision automatic turntable was taken as the reference to calculate the indication error of the inclinometer. Then, the automatic inclinometer calibration control process and the digital inclinometer zero-setting function were formulated. For display tube recognition, a new display tube recognition algorithm combining threading method and feature extraction method was proposed. Finally, the calibration system was calibrated by photoelectric autocollimator and regular polygon mirror, and the calibration system error and repeatability were calculated via a series of experiments. The experimental results showed that the indication error of the proposed calibration system was less than 4 , and the repeatability was 3.9 . A digital inclinometer with the resolution of 0.1 ◦ was taken as a testing example, within the calibration points’ range of [ − 90 ◦ , 90 ◦ ], the repeatability of the testing was 0.085◦, and the whole testing process was less than 90 s. The digital inclinometer indication error is mainly introduced by the digital inclinometer resolution according to the uncertainty evaluation.

Cite this article

Feng Zheming, Chen Gang, Nan Zhuojiang, Tao Wei . Automatic Digital Inclinometer Calibration System Based on Image Recognition[J]. Journal of Shanghai Jiaotong University(Science), 2025 , 30(2) : 280 -290 . DOI: 10.1007/s12204-023-2594-y

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