A Novel Instantaneous Angular Parameter Detection Method Using Machine Vision Image Decoding for Rotating Machinery
Faced with noise and interference in industrial environments, the need to capture high-frequency and low-frequency signals, the requirements for high resolution and sampling rate of data acquisition systems, and the influence of harsh environments and vibrations, sensors cannot guarantee the stability of signal transmission and the integrity of data. This paper presents the principles and implementation of an innovative sensor system designed to measure the instantaneous angular parameters of rotating shafts at extremely low speeds, approaching zero velocity. The sensor system mainly consists of a sinusoidal modulation pattern and a set of image acquisition devices. The modulation pattern is affixed to the shaft's surface and rotates in unison with it. The camera is used to obtain the characteristic image of the pattern when it rotates with the shaft to calculate the instantaneous angular parameters. When the shaft rotates, the image feature is the phase modulation signal, and the modulation signal can be obtained by image feature tracking and mid-axis feature point extraction methods. The sensor system was experimentally verified using a rotating shaft experiment. The results show that the sensor measurement system is largely consistent with the motor speed setting value. The results show that it has high accuracy and reliability when obtaining low-speed operations with acceleration and deceleration transients.
Authors
- Chengsong Zhang (ORCID: https://orcid.org/0000-0003-1527-5691)
- Jie Ren (ORCID: https://orcid.org/0000-0001-9985-3430)
- Mingjun Ju
- Yuanyuan Zhou (ORCID: https://orcid.org/0000-0002-0800-5485)
- Zhongwen Hu (ORCID: https://orcid.org/0000-0001-9701-8562)
Institutions
- Anhui University (CN)
- Anhui University of Science and Technology (CN)
Publication Details
- Published
- 2024-10-31
- DOI
- https://doi.org/10.1109/icsmd64214.2024.10920545
- Citations
- 1
- Primary Topic
- Image and Object Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.25
Funders
- Anhui University of Science and Technology