Research on Position Detection Technology for Cross-Linked Polyethylene-Insulated Cable Production Lines
Cable position detection technology is extremely important in the production process of cross-linked polyethylene (XLPE) cables. To cope with the complex and multi-interference industrial production environment, we utilize the principle of electromagnetic field sensing, exploiting the influence of metals on the surrounding magnetic field to achieve non-contact detection of the position of metal cables. Based on the principle of inductive balanced coil sensing, we propose a metal cable detection system scheme based on inductive balanced detection coils. We design the transmitting and receiving circuit modules. Firstly, the transmitting coil is excited and driven, and then a series of processes such as frequency selection amplification, automatic gain processing, detection, sampling and holding, and signal zeroing are performed on the received signal to improve the system sensitivity and anti-interference performance, ultimately accurately measuring the position of the cable. While implementing this system, we also conducted cable position detection experiments in a factory environment. The experimental results show that the system can achieve a root mean square error (RMSE) of no more than 2.5mm for position detection, indicating that the system can meet the needs of XLPE industrial production.
Authors
- Min Tao (ORCID: https://orcid.org/0000-0001-8194-2195)
- Sida Li (ORCID: https://orcid.org/0000-0001-6519-7295)
- Meiling Hu (ORCID: https://orcid.org/0000-0002-1135-7406)
- Xin Xu (ORCID: https://orcid.org/0000-0003-2954-6923)
- Xue Xia (ORCID: https://orcid.org/0000-0001-6908-5856)
Institutions
- Changchun University of Science and Technology (CN)
- Jilin University (CN)
- Harbin Institute of Technology (CN)
- State Key Laboratory on Integrated Optoelectronics (CN)
- BaiCheng Normal University (CN)
Publication Details
- Journal
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tim.2025.3527617
- Citations
- 2
- Primary Topic
- Power Line Inspection Robots
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- National Natural Science Foundation of China