基于改进PCA与有序多分类Logistic的充填管道磨损风险评估

doi:10.11872/j.issn.1005-2518.2019.05.740

Abstract

Abstract:

The filling mining method is mainstream mining method used in major mines today.The safe implementation of filling technology depends on the construction of a good filling pipeline transportation system.Considering the complexity of the filled pipeline system and the large number and variety of influencing factors，in order to accurately predict the wear risk of the filling pipeline of the mine，a wear risk assessment of the filling pipeline based on the improved PCA and the ordered multi-class Logistic regression combination model was built.On the basis of practical experience，a total of 12 items including the volume fraction of the filling slurry，the filling doubled line，the corrosiveness of the filling slurry，and the material of the pipe were selected.Reasonable risk levels were divided according to the characteristics of each indicator and the corresponding evaluation model was constructed.The filling production data of four mines such as Jinchuan Longshou mine and Dahongshan copper mine were taken as samples.The improved PCA algorithm was used to analyze the correlation of each index，and the three principal components with a cumulative contribution rate of 91.125% and factor load of the principal component of each indicator were obtained.In the end，the two indicators with low correlation and small influence index，the density of the filling slurry（27.75） and the corrosiveness of the filling slurry（27.60） were deleted.The preferred main indicators were substituted into the ordered multi-class Logistic regression model，the continuous indicator values were linearly fitted to the discrete risk levels，and the regression coefficients，standard errors and significance levels of each index were calculated，and the equations of probability fluctuations were solved. Finally，the probability of four mines corresponding to different wear risks Ⅰ（not easy to wear），Ⅱ（relatively easy to wear），Ⅲ（easy to wear），Ⅳ（very easy to wear） were obtained. They were： Jinchuan Longshou mine is 0.247，0.440，0.154，0.153； Dahongshan copper mine is 0.179，0.240，0.323，0.258； Hedong gold mine is 0.181，0.227，0.345，0.247； Xincheng gold mine is 0.181，0.227，0.345，0.247.From a theoretical point of view，the risk level corresponding to the probability of the largest value was used as the final judgment level of the wear risk of the mine filling pipeline，and Jinchuan Longshou mine is Ⅱ，Dahongshan copper mine is Ⅲ，Hedong gold mine is Ⅲ，Xincheng gold mine is Ⅲ. The mine also makes corresponding level protection and maintenance measures based on this.From the actual production application，it is said that the probability of the Ⅳ risk level should be paid special attention，and the normal operation of the filling pipeline should be guaranteed to the greatest extent within the scope permitted by technology and funds. The mathematical method combining improved PCA and ordered multi-class Logistic regression avoids the collinearity between the various indicators，reduces the interference of the weak indicators on the evaluation results，and obtains the accurate risk of wear risk of filling the pipeline.It provides a theoretical basis for scientific prediction of pipeline wear risk and the implementation of effective and economical protection measures for similar mines.The mine can construct an appropriate filling pipeline protection system according to its own development.

Key words: filling pipeline wearing, improve principal component analysis, ordered multi-class Logistic regression, wear risk, probability of risk level

CLC Number:

TD85

Shi WANG,Yi TANG,Xiao FENG. Risk Assessment of Filling Pipeline Wearing Based on Improved PCA and Ordered Multi-class Logistic[J].Gold Science and Technology, 2019, 27(5): 740-746.

Figures/Tables 7

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磨损等级	充填料浆体积分数/%	充填料浆密度/（t·m^-3）	粗颗粒占比/%	管道内径/mm	管道铺设不平整度/%	管道绝对糙度/μm	充填倍线	料浆流速与临界流速之比	管道使用年限/a
Ⅰ	I₁<30	I₂<1.5	I₃<20	I₄>200	I₅<1.0	I₆≤100	I₇≥7.0	I₈<1.0	I₁₀<2
Ⅱ	30≤I₁<40	1.5≤I₂<1.7	20≤I₃<40	150< I₄≤200	1.0≤I₅<3.0	I₆≤100	5.0≤I₇<7.0	1.0≤I₈<1.2	2≤I₁₀<5
Ⅲ	40≤I₁<50	1.7≤I₂<1.9	40≤I₃<60	100< I₄≤150	3.0≤I₅<5.0	300≤I₆<500	3.0≤I₇<5.0	1.2≤I₈<1.5	5≤I₁₀<10
Ⅳ	I₁≥50	I₂≥1.9	I₃≥60	I₄≤100	I₅≥5.0	I₆≥500	1.0≤I₇<3.0	I₈≥1.5	I₁₀≥10

磨损等级	充填骨料形状	充填料浆腐蚀性	管道材料
Ⅰ	圆形或椭圆形	中性并且不含有能与充填管道发生反应的成分	双金属耐磨复合管
Ⅱ	方形	特定条件下pH值发生变化与充填管道发生反应	钢塑复合管
Ⅲ	多棱角形	弱酸、弱碱以及一系列能与充填管道发生轻微反应的成分	陶瓷复合管
Ⅳ	极不规则	强酸、强碱或一系列容易与充填管道发生反应的成分	单一复合材料

矿山名称	I₁	I₂	I₃	I₄	I₅	I₆	I₇	I₈	I₉	I₁₀	I₁₁	I₁₂
金川龙首矿	56	1.98	38	199	2.72	300	3.2	1.3	8	1	2	2
大红山铜矿	33	1.69	42	160	0.98	500	9.6	3.0	7	3	3	2
河东金矿	24	1.68	52	82	0.56	100	5.2	1.6	10	3	2	3
新城金矿	52	1.94	33	107	1.27	200	5.8	3.5	6	4	3	1

主成分	I₁	I₂	I₃	I₄	I₅	I₆	I₇	I₈	I₉	I₁₀	I₁₁	I₁₂
Z₁	-0.65	-0.18	0.229	-0.39	-0.46	0.551	0.717	0.202	0.234	0.375	0.093	0.262
Z₂	-0.14	0.84	0.224	0.411	0.237	0.206	0.791	0.437	-0.23	-0.39	-0.10	0.137
Z₃	0.54	-0.01	0.371	0.646	0.226	0.085	0.097	0.301	0.138	0.599	0.435	0.239
B_i	42.06	27.75	37.44	35.75	34.61	39.77	38.14	30.47	37.89	36.71	27.60	33.71

变量	回归系数	标准误差	显著性水平
I₁	0.3507	0.3108	0.1128
I₃	0.0372	0.1826	0.3972
I₄	-0.1055	0.2686	0.0293
I₅	-0.0469	0.1782	0.2833
I₆	0.2416	0.1306	0.0633
I₇	0.2817	0.1026	0.0375
I₈	0.0983	0.1772	0.3985
I₉	0.2478	0.1812	0.1755
I₁₀	-0.2928	0.1428	0.0427
I₁₂	0.2793	0.1642	0.0694
β	1.7855	0.7634	0.0259

Risk Assessment of Filling Pipeline Wearing Based on Improved PCA and Ordered Multi-class Logistic

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