Bowen Li , Zhenhua Xi , Huzhong Zhang , Gang Li , Yunjian Song , Wenjie Jia , Kun Liu , Detian Li
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引用次数: 0
Abstract
This paper propose a non-contact spherical rotor posture detection method based on monocular vision and deep learning to enable high-precision monitoring of rotor motion in a Spinning Rotor Gauge (SRG). By integrating convolutional neural network (CNN) landmark detection with random sample consensus (RANSAC) trajectory fitting, real-time estimation of the rotor’s deflection angle and spin angle is achieved with an error of less than 0.5°. Experimental results demonstrate that, within the rotational speed range of 440–800 Hz, increasing the rotational speed does not induce any significant change in the angle of the rotor’s spin axis, thereby validating the stability of the sensor. The rotor attitude experiments from 1 kHz to 10 kHz proved the correlation between the rotor deflection angle and its magnetic moment. This study provides the first vision-based dynamic monitoring solution for precise calibration of SRGs under high-vacuum conditions, offering a novel approach for vacuum calibration procedures and residual drag investigations in SRGs.
期刊介绍:
Vacuum is an international rapid publications journal with a focus on short communication. All papers are peer-reviewed, with the review process for short communication geared towards very fast turnaround times. The journal also published full research papers, thematic issues and selected papers from leading conferences.
A report in Vacuum should represent a major advance in an area that involves a controlled environment at pressures of one atmosphere or below.
The scope of the journal includes:
1. Vacuum; original developments in vacuum pumping and instrumentation, vacuum measurement, vacuum gas dynamics, gas-surface interactions, surface treatment for UHV applications and low outgassing, vacuum melting, sintering, and vacuum metrology. Technology and solutions for large-scale facilities (e.g., particle accelerators and fusion devices). New instrumentation ( e.g., detectors and electron microscopes).
2. Plasma science; advances in PVD, CVD, plasma-assisted CVD, ion sources, deposition processes and analysis.
3. Surface science; surface engineering, surface chemistry, surface analysis, crystal growth, ion-surface interactions and etching, nanometer-scale processing, surface modification.
4. Materials science; novel functional or structural materials. Metals, ceramics, and polymers. Experiments, simulations, and modelling for understanding structure-property relationships. Thin films and coatings. Nanostructures and ion implantation.