Accumulative Imaging Method of Grounding Grid Topological Features Based on Combined Sources

Abstract

One essential requirement for grounding grid state detection is quick and accurate localization of the topology. The combined source detection approach works well for increasing the signal amplitude and detection efficiency inside large grounding grids. However, the presence of bypass branch currents and grounding grid breakpoints causes variations in the location calculated by the peak approach during tiny grounding grid topology detection. The magnetic field superposition method under the excitation mode of multiple sources exacerbates this positioning error. This paper presents a topological feature accumulation imaging method designed for combined sources to address this problem. The proposed approach examines the effect of the bias in the surrounding branch current amplitudes on topological localization by utilizing the concepts of electromagnetic induction. The factors contributing to increased topological localization errors were examined by investigating the relationship between the superposition effect of the surface magnetic induction strength and localization error under different combined excitations, particularly in the context of breakpoints in the grounding grid topology. The proposed method uses the top-hat algorithm to extract top-hat features of the amplitude of the surface magnetic induction intensity under every type of excitation. Top-hat eigenvalue accumulation was used to reduce topological localization offsets by mitigating superfluous signals. The advantage of this method over conventional processing approaches is demonstrated by simulations and test field experiments, which show enhanced accuracy in combined source topological localization for small grounding grids.

Keywords

• Grounding grid
• positioning biases
• combined sources
• top hat algorithm