A weak alternating shaft current sensing in cooperation with a multi-branch shaft voltage sampler and least square optimization

Abstract It is of great significance for power systems to realize an accuracy and reliable monitoring of the weak shaft current since it is usually associated with early failures of generators. To achieve an effective measurement for weak shaft current, this paper proposes a non-contact shaft current measurement method for mA-level alternating current used in power systems. Firstly, principles and challenges of CT’s being applied to mA-level alternative current sensing are discussed. A split CT with magnetic shielding is proposed for mA-level current detection, along with a specially designed signal conditioning circuit. Correspondingly, the calculation method of the CT’s signal amplitude based on the quad-phase phase-sensitive detection algorithm is proposed, with a preprocessing algorithm used to eliminate modulation signal interference. Then, a multi-branch shaft voltage sampling circuit in cooperation with the least square optimization used for current demodulation is introduced, considering the actual CT output model. Further, the designed current measurement system which consists of the split CT, the CT’s conditioning circuit, and the multi-branch shaft voltage sampling circuit is analyzed. Finally, an experimental platform is designed and built for verification. The experimental results show that the non-contact measurement method for shaft current proposed in this paper is feasible, and the designed current measurement system can achieve an accuracy rate of over 90% for current detection within 10–50 mA. It provides a new solution for the detection of weak shaft current in power systems.

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Publication Details

Journal
Measurement Science and Technology
Published
2025-05-01
DOI
https://doi.org/10.1088/1361-6501/add318
Primary Topic
Magnetic Field Sensors Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A weak alternating shaft current sensing in cooperation with a multi-branch shaft voltage sampler and least square optimization

Hongli Hu, Kaihao Tang, Songyi Dian, Ke Yin et al.
Measurement Science and Technology
Magnetic Field Sensors Techniques
article

A weak alternating shaft current sensing in cooperation with a multi-branch shaft voltage sampler and least square optimization

Hongli Hu, Kaihao Tang, Songyi Dian, Ke Yin, B.S. Wang
article en

Abstract

Abstract It is of great significance for power systems to realize an accuracy and reliable monitoring of the weak shaft current since it is usually associated with early failures of generators. To achieve an effective measurement for weak shaft current, this paper proposes a non-contact shaft current measurement method for mA-level alternating current used in power systems. Firstly, principles and challenges of CT’s being applied to mA-level alternative current sensing are discussed. A split CT with magnetic shielding is proposed for mA-level current detection, along with a specially designed signal conditioning circuit. Correspondingly, the calculation method of the CT’s signal amplitude based on the quad-phase phase-sensitive detection algorithm is proposed, with a preprocessing algorithm used to eliminate modulation signal interference. Then, a multi-branch shaft voltage sampling circuit in cooperation with the least square optimization used for current demodulation is introduced, considering the actual CT output model. Further, the designed current measurement system which consists of the split CT, the CT’s conditioning circuit, and the multi-branch shaft voltage sampling circuit is analyzed. Finally, an experimental platform is designed and built for verification. The experimental results show that the non-contact measurement method for shaft current proposed in this paper is feasible, and the designed current measurement system can achieve an accuracy rate of over 90% for current detection within 10–50 mA. It provides a new solution for the detection of weak shaft current in power systems.

Measurement Science and TechnologyVol. 36(5)
Sichuan University (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 93%
Magnetic Field Sensors Techniques
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