The effective monitoring of the grounding current of the core and clamp of the converter transformer can prevent partial overheating, gassing of oil, and other abnormal conditions caused by the grounding fault of the core and clamp, ensuring the safety and stability of the power system. At present, the main detection and diagnosis method is to use the clamp current meter to detect the effective value of the grounding current. However, due to the larger capacity, higher voltage level, more complex structure and electromagnetic field distribution of the converter transformer, there is no clear standard and detection diagnosis method. Firstly, this paper analyzes the causes of grounding current and related calculations. And the design of the monitoring system for the grounding current of the converter transformer core and clamp design of the hardware system for the grounding current of the converter transformer is studied and the design process of the main circuit is given. Secondly, aiming at the problem of amplitude measurement deviation and non-integer frequency of harmonic generated by the grounding current of the core and clamp, a harmonic current detection and analysis scheme based on four Blackman-harris algorithms and the specific design process are proposed. Third, a diagnostic method based on probabilistic neural network is proposed, and a software platform is built to display and diagnose the grounding current state according to it. Finally, a prototype was manufactured and experimental study was carried out to verify the correctness of the proposed scheme.
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