采选技术与矿山管理

基于模糊故障树和蒙特卡洛方法的智能铲运系统可靠性分析

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  • 1.中南大学资源与安全工程学院,湖南 长沙 410083
    2.矿冶科技集团有限公司,北京 102628
    3.国家金属矿绿色开采国际联合研究中心,北京 102628
刘志祥(1967-),男,湖南宁乡人,博士,教授,从事采矿技术研究工作。liulzx@csu.edu.cn

网络出版日期: 2024-07-03

基金资助

山东省重大科技创新工程项目“深部金属矿智能化开采关键技术及装备集成研究和工程示范”(2019SDZY05);国家自然科学基金项目“海底金属矿开采充填体约束矿柱群力学模型构建与混沌破坏机制”(51974359);“金属矿海底基岩开采裂隙分形演化与突水混沌孕育机制”(51674288)

Reliability Analysis of Intelligent Shoveling System Based on Fuzzy Fault Tree and Monte Carlo Method

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  • 1.School of Resource and Safety Engineering, Central South University, Changsha 410083, Hunan, China
    2.BGRIMM Technology Group, Beijing 102628, China
    3.National Center for International Joint Research on Green Metal Mining, Beijing 102628, China

Online published: 2024-07-03

摘要

为了分析智能铲运系统在三山岛矿区内实际运行使用的可靠性,提出将模糊故障树分析与蒙特卡洛仿真相结合的研究方法。以智能铲运系统运行使用故障为顶事件,确定了16个中间事件和33个底事件,并构建了故障树模型。采用模糊集合理论的方法,通过10位专家的结果反馈,求取了各底事件的发生概率,进而对故障树进行了定量分析,得到顶事件发生概率为0.3481%。基于建立的故障树模型,采用蒙特卡洛仿真模拟的方法,编写蒙特卡洛仿真算法,合理设置仿真参数,最后得到了平均无故障时间、可靠性与不可靠性曲线以及系统失效概率曲线。通过对底事件的仿真重要度进行计算,结果表明:操作规范不合格(管理原因)和信息沟通失误(人员原因)对系统可靠性影响最大,影响最大的机械原因为操作装置故障和制动系统老化。通过将计算结果与实际数据进行对比分析,验证了该方法的准确性和有效性。

本文引用格式

刘志祥, 王凯, 杨小聪, 万串串, 周玉成 . 基于模糊故障树和蒙特卡洛方法的智能铲运系统可靠性分析[J]. 黄金科学技术, 2023 , 31(3) : 477 -486 . DOI: 10.11872/j.issn.1005-2518.2023.03.139

Abstract

With the intellectualization of mining equipment,its reliability problem is becoming more and more prominent,and has become an important topic in the mining industry.In this work,the method combining fuzzy fault tree analysis and Monte Carlo simulation was proposed to analyze the reliability of the intelligent shovel system for actual operation in the Sanshandao mine.By analyzing the performance of the system and its operation condition in the mine,the main factors affecting the reliability of the intelligent shovel operation system were determined.Taking the operation failure of the intelligent shovel system as the top event,16 intermediate events,as well as 33 bottom events,were determined,and a fault tree model was established through field investigation,literature review and expert discussion,etc.Using the method of fuzzy set theory,the language values were transformed into fuzzy numbers according to the corresponding affiliation functions by the results feedback from 10 experts.Then,the fuzzy number was transformed into the corresponding probability of brittle failure and probability of failure by using the formula of fuzzy number,upon which the probability of occurrence of the bottom event was obtained.Based on the occurrence probability of each bottom event,the quantitative analysis of the fault tree was carried out to obtain the minimum cut set of the fault tree.Thus,the probability of failure of intelligent shovel operation was calculated,and its value is 0.3481%,which is in line with the actual situation of production.In order to obtain the dynamic law of system reliability with time,the Monte Carlo simulation method was used based on the established fault tree model.The simulation parameters and process were set reasonably,and the Monte Carlo simulation algorithm was written,upon which the mean time to failure,reliability and unreliability curves and system failure probability curves were obtained.Through the analysis of the results,the effective running time and the change in the failure probability of the system were judged,which can provide a reference for the maintenance of the equipment.Moreover,the simulation importance of the bottom events was also calculated.The results indicate that the management reason(operation specification failure) and personnel reason(information communication failure) have the greatest impact on system reliability,and the most influential mechanical reasons are operation device failure and brake system aging.Managing from the above events,the probability of system failure can be effectively reduced.The results are consistent with the actual engineering situation,which demonstrates the effectiveness of the proposed method.This work can provide a reference for the production and operation of the mine and can be promoted in mines and other industries.

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