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Gold Science and Technology ›› 2017, Vol. 25 ›› Issue (3): 70-76.doi: 10.11872/j.issn.1005-2518.2017.03.070

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Failure Risk Assessment Model of Filling Pipeline Based on KPCA and PSO-SVM

ZHANG Qinli，WANG Jing，WANG Xinmin   

  1. School of Resources and Safety Engineering，Central South University，Changsha     410083，Hunan，China
  • Received:2016-06-02 Revised:2016-09-28 Online:2017-06-30 Published:2017-09-11

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Abstract:

In order to predict the invalidation risk of backfilling pipeline more accurately，the evaluation model based on kernel principal component analysis and PSO-SVM is established.Eight quantitative indexes are selected as the evaluation index of failure risk of filling pipeline.And the sample data of fifteen mines were counted，which were processed by kernel principal component analysis，producing the main ingredients，as the input data of the optimized SVM model which ended up with a more accurate risk prediction on invalidation of backfilling pipeline.The results indicate that the average expected value relative errors of the five mines are below 5%.The invalidation risk assessment of backfill pipeline by the establishment of the kernel principal components analytic method and the optimized SVM model has the advantage of rapid analysis and high precision of prediction.A better evaluation is provided for the mine backfilling pipeline invalidation risk analysis.

Key words: failure risk level, filling pipe, kernel principal component analsis, support vector machine, combination predicting model

CLC Number: 

  • TD325

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