Characterization of the susceptibility of ore particles to breakdown in high voltage pulse breakage and the influencing factors

The susceptibility of ore particles to electrical breakdown plays a critical role for high voltage pulse (HVP) breakage, yet its quantitative characterization still lacks deep understanding. Two indicators, namely breakdown delay time ( T d ) and breakdown strength ( E b) were compared, based on analysis on the two breakdown modes namely wavefront mode and post-wave mode. It was found that T d is more suitable to characterize the susceptibility of ore particles to electrical breakdown in HVP breakage than E b . A probabilistic model based on the Weibull distribution is developed to describe the relation of breakdown probability to T d . Regression analyses were conducted to investigate how operating parameters and particle properties influence T d and size reduction degree of ore particles in HVP breakage. The regressed models demonstrate potential capability to predict metallic minerals content and HVP breakage degree based on operating parameters and particle properties.

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Publication Details

Journal
International Journal of Mining Science and Technology
Published
2025-11-21
DOI
https://doi.org/10.1016/j.ijmst.2025.11.004
Primary Topic
Vacuum and Plasma Arcs
Type
article
Field-Weighted Citation Impact
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article

Characterization of the susceptibility of ore particles to breakdown in high voltage pulse breakage and the influencing factors

International Journal of Mining Science and Technology
Vacuum and Plasma Arcs
article

Characterization of the susceptibility of ore particles to breakdown in high voltage pulse breakage and the influencing factors

article en

Abstract

The susceptibility of ore particles to electrical breakdown plays a critical role for high voltage pulse (HVP) breakage, yet its quantitative characterization still lacks deep understanding. Two indicators, namely breakdown delay time ( T d ) and breakdown strength ( E b) were compared, based on analysis on the two breakdown modes namely wavefront mode and post-wave mode. It was found that T d is more suitable to characterize the susceptibility of ore particles to electrical breakdown in HVP breakage than E b . A probabilistic model based on the Weibull distribution is developed to describe the relation of breakdown probability to T d . Regression analyses were conducted to investigate how operating parameters and particle properties influence T d and size reduction degree of ore particles in HVP breakage. The regressed models demonstrate potential capability to predict metallic minerals content and HVP breakage degree based on operating parameters and particle properties.

International Journal of Mining Science and TechnologyVol. 36(1)
Southern University of Science and Technology (CN), Zhengzhou University (CN), Xi'an Railway Survey and Design Institute (CN), China Nonferrous Metals Changsha Investigation Design Institute (CN), Fuzhou University (CN)
Openalex Percentile: Top 41%
Vacuum and Plasma Arcs
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