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黄金科学技术 ›› 2023, Vol. 31 ›› Issue (3): 477-486.doi: 10.11872/j.issn.1005-2518.2023.03.139

• 采选技术与矿山管理 • 上一篇    下一篇

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

刘志祥1(),王凯1,杨小聪2,3,万串串2,3,周玉成2,3   

  1. 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
  • 收稿日期:2022-10-09 修回日期:2023-02-23 出版日期:2023-06-30 发布日期:2023-07-20
  • 作者简介: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
  • 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

Zhixiang LIU1(),Kai WANG1,Xiaocong YANG2,3,Chuanchuan WAN2,3,Yucheng ZHOU2,3   

  1. 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
  • Received:2022-10-09 Revised:2023-02-23 Online:2023-06-30 Published:2023-07-20

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。

关键词: 智能铲运系统, 可靠性指标, 模糊故障树, 故障概率, 蒙特卡洛仿真, 仿真重要度

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.

Key words: intelligent shoveling system, reliability index, fuzzy fault tree, failure probability, Monte Carlo simulation, importance of simulation

中图分类号: 

  • TD421

图1

智能铲运系统构架图"

表1

系统故障数据"

参数数值
总工作时间/h16 530
故障次数/次63
总维修时间/h76
故障概率/%0.4598
平均无故障时间/h262.4

表2

各级中间事件列表"

事件编号事件描述事件编号事件描述
M1设备使用原因故障M9行车路线设计不当
M2设计管理原因故障M10维护保养原因故障
M3其他原因故障M11人员管理原因故障
M4传动系统故障M12个人原因故障
M5液压系统故障M13环境原因故障
M6控制系统故障M14运行使用设计失误
M7制动系统故障M15维护保养缺漏
M8无线局域网故障M16异常环境条件

表3

底事件列表"

事件编号事件描述事件编号事件描述
X1电机模块温度过高X18路线设计不合理
X2电压异常X19路线调整不及时
X3电机控制器故障X20安全检查缺漏
X4油缸运行故障X21易损部件更换不及时
X5转向柱塞泵故障X22设备保养不规范
X6转向阀故障X23设备长期耗损
X7操作装置故障X24施工管理不到位
X8参数设置不合理X25人员工作经验欠缺
X9传感器故障X26操作规范不合格
X10压力控制器故障X27安全意识欠缺
X11空气压缩机故障X28工作不专注
X12制动系统老化X29信息沟通失误
X13无线局域网硬件故障X30温度、湿度过高
X14无线局域网软件故障X31粉尘浓度过高
X15无线局域网信号失效X32突发灾害事件
X16巷道转弯半径过小X33设备调整不及时
X17行车巷道路面障碍

图2

智能铲运系统运行使用故障树"

表 4

评价专家信息"

序号单位职称或职务工作年限序号单位职称或职务工作年限
1中南大学教授20年6柴胡栏子金矿高级工程师10年
2三山岛金矿副区长11年7三山岛金矿工程师10年
3三山岛金矿高级工程师10年8矿冶科技集团工程师9年
4三山岛金矿高级工程师9年9柴胡栏子金矿工程师8年
5柴胡栏子金矿高级工程师10年10矿冶科技集团工程师8年

表5

专家调查权重"

等级r对应专家编号计算系数vr计算权重wr等级r对应专家编号计算系数vr计算权重wr
1m1,m21.00.12203m5,m60.80.0976
2m3,m40.90.10984m7,m8,m9,m100.70.0853

图3

语言值对应的模糊数"

表6

底事件X1的专家意见及其权重"

专家编号专家意见模糊数权重w1,j专家编号专家意见模糊数权重w1,j
m1非常低(0,0,0.1,0.2)0.1220m6(0.1,0.2,0.2,0.3)0.0976
m2非常低(0,0,0.1,0.2)0.1220m7(0.1,0.2,0.2,0.3)0.0853
m3比较低(0.2,0.3,0.4,0.5)0.1098m8(0.1,0.2,0.2,0.3)0.0853
m4非常低(0,0,0.1,0.2)0.1098m9(0.1,0.2,0.2,0.3)0.0853
m5(0.1,0.2,0.2,0.3)0.0976m10比较低(0.2,0.3,0.4,0.5)0.0853

表7

底事件的脆失效概率和失效概率"

底事件编号

脆失效

概率

失效概率底事件编号

脆失效

概率

失效概率
X10.1868090.000175X180.1930060.000196
X20.1007220.000017X190.1918300.000192
X30.1159170.000030X200.1451080.000070
X40.1457680.000071X210.1897700.000185
X50.1644140.000111X220.2282250.000352
X60.1743790.000137X230.2644940.000581
X70.2094340.000261X240.1572060.000094
X80.1628990.000107X250.1677270.000119
X90.1285450.000044X260.2494330.000476
X100.1879410.000179X270.2105240.000266
X110.1550670.000089X280.2275760.000348
X120.2008600.000226X290.2334560.000380
X130.1677270.000119X300.2134660.000279
X140.1667120.000116X310.2820530.000722
X150.1659270.000114X320.1128860.000027
X160.1746330.000138X330.1662500.000115
X170.1788870.000150

表8

最小割集"

序号内容序号内容
MC1X1MC16X16*X19
MC2X2MC17X17*X19
MC3X3MC18X18*X19
MC4X4MC19X20*X23
MC5X5MC20X21*X23
MC6X6MC21X22*X23
MC7X7MC22X24
MC8X8MC23X25
MC9X9MC24X26
MC10X10MC25X27
MC11X11MC26X28
MC12X12MC27X29
MC13X13MC28X30*X33
MC14X14MC29X31*X33
MC15X15MC30X32*X33

图4

仿真流程图"

图5

可靠度与不可靠度曲线"

图6

失效概率分布"

图7

底事件重要度仿真结果"

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