An improved CRITIC and cloud model evaluation method for predicting the wear risk of vertical filling pipes in deep well
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Abstract:
To accurately predict wear degree of vertical filling pipe in deep mine, a cloud model has been established to assess the risk envolved. The paper has studied the case of four domestic enterprises, such as Longshou mining in Jinchuan. Fourteen elements, including the slurry volume fraction, were selected as risk assessment indexes. On the basis of to the cloud model theory, variable indicators were used to choose applicable digital characteristics. Taking the correlation between various indicators as well as internal variation of them into account, we introduced the improved CRITIC method to gain the index weight, and the pipeline wear risk grades were obtained by calculating the comprehensive determinacy of evaluation indicators. The results showed that the wear risk grades of vertical filling pipelines in Longshou Mine, Dongguashan Copper Mine, Suncun Mine and Gaofeng Mine in Guangxi were Ⅱ, Ⅲ, Ⅳ and Ⅲ respectively. Compared with other assessment methods, the computational model transforms ambiguity and randomness into a quantitative value of certainty, achieving a qualitative-to-quantitative mapping, providing an innovation for similar research of wear degree of vertical filling pipe in deep mine.
