Risk Evaluation for Wear of Deep Well Vertical Filling Pipeline Based on Cloud Model and Distance Discriminant Weighting Method

With the rapid development of the world economy in recent years, the mineral resources in the shallow part of the Earth can no longer meet the needs of mankind, and resource development is continually moving into the deep part of the Earth. The filling method, in particular, has gradually been employed for the treatment of mining goaves in response to the requirements of environmentally sustainable development. As an important part of the filling system, the wear and tear of the deep filling pipeline is of great significance to the normal operation of the system, the safe production of the mine and the reasonable protection of the environment. In this paper, the wear situation of the deep well vertical filling pipeline is selected as the analysis angle to carry out the research, and the risk assessment model is constructed by combining the distance discriminant weighting method and the cloud model for the uncertainty of the wear risk grading assessment. Firstly, 11 quantitative factors and three qualitative factors were selected as evaluation indicators and employed as cloud model variables. Appropriate cloud model digital features were picked based on cloud model theory, to construct the cloud model of each indicator. Secondly, the distance discriminant weighting method is introduced to obtain the weight of each indicator, and the risk level of the vertical filling pipeline in deep wells is obtained by calculating the comprehensive certainty of the risk evaluation object belonging to different levels. Finally, the model was applied to Dongguashan Copper Mine, and the model calculation results were analyzed and compared with the actual wear situation. The results show that the model transforms the ambiguity and randomness into a certain quantitative value of certainty, completing the map from qualitative to quantitative. This method introduces a new idea and method for dealing with similar problems of vertical filling pipes in deep wells.

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Publication Details

Journal
Mathematics
Published
2026-05-22
DOI
https://doi.org/10.3390/math14111799
Primary Topic
Advanced Decision-Making Techniques
Type
article
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article

Risk Evaluation for Wear of Deep Well Vertical Filling Pipeline Based on Cloud Model and Distance Discriminant Weighting Method

Jiachuang Wang, J Wu, Mingjian Huang, Jiang Guo
Mathematics
Advanced Decision-Making Techniques
article

Risk Evaluation for Wear of Deep Well Vertical Filling Pipeline Based on Cloud Model and Distance Discriminant Weighting Method

Jiachuang Wang, J Wu, Mingjian Huang, Jiang Guo
article en

Abstract

With the rapid development of the world economy in recent years, the mineral resources in the shallow part of the Earth can no longer meet the needs of mankind, and resource development is continually moving into the deep part of the Earth. The filling method, in particular, has gradually been employed for the treatment of mining goaves in response to the requirements of environmentally sustainable development. As an important part of the filling system, the wear and tear of the deep filling pipeline is of great significance to the normal operation of the system, the safe production of the mine and the reasonable protection of the environment. In this paper, the wear situation of the deep well vertical filling pipeline is selected as the analysis angle to carry out the research, and the risk assessment model is constructed by combining the distance discriminant weighting method and the cloud model for the uncertainty of the wear risk grading assessment. Firstly, 11 quantitative factors and three qualitative factors were selected as evaluation indicators and employed as cloud model variables. Appropriate cloud model digital features were picked based on cloud model theory, to construct the cloud model of each indicator. Secondly, the distance discriminant weighting method is introduced to obtain the weight of each indicator, and the risk level of the vertical filling pipeline in deep wells is obtained by calculating the comprehensive certainty of the risk evaluation object belonging to different levels. Finally, the model was applied to Dongguashan Copper Mine, and the model calculation results were analyzed and compared with the actual wear situation. The results show that the model transforms the ambiguity and randomness into a certain quantitative value of certainty, completing the map from qualitative to quantitative. This method introduces a new idea and method for dealing with similar problems of vertical filling pipes in deep wells.

MathematicsVol. 14(11)
Central South University (CN), Zhengzhou University (CN), Guangzhou Automobile Group (China) (CN)
Openalex Percentile: Top 2%
Advanced Decision-Making Techniques
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