[1]崔铁军,李莎莎.少故障数据条件下SFEP最终事件发生概率分布确定方法[J].智能系统学报,2020,15(1):136-143.[doi:10.11992/tis.201911002]
CUI Tiejun,LI Shasha.Determination method of target event occurrence probability in SFEP under the condition of less fault data[J].CAAI Transactions on Intelligent Systems,2020,15(1):136-143.[doi:10.11992/tis.201911002]
点击复制
CUI Tiejun,LI Shasha.Determination method of target event occurrence probability in SFEP under the condition of less fault data[J].CAAI Transactions on Intelligent Systems,2020,15(1):136-143.[doi:10.11992/tis.201911002]
少故障数据条件下SFEP最终事件发生概率分布确定方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
15
期数:
2020年第1期
页码:
136-143
栏目:
学术论文—人工智能基础
出版日期:
2020-01-05
- Title:
- Determination method of target event occurrence probability in SFEP under the condition of less fault data
- Keywords:
- safety system engineering; space fault network; system fault evolution process; less fault data; information diffusion; target event occurrence probability
- 分类号:
- TP18;X91
- 摘要:
- 为了在获得少故障数据条件下得到适合的系统故障演化过程（system fault evolution process，SFEP）中最终事件发生概率分布，提出一种考虑信息扩散且数据较少情况下的最终事件发生概率分布计算方法。该方法利用信息扩散原理以事件发生时因素为中心在研究区域内形成正态分布。同一事件的多次发生在研究区域中取最大值形成该事件发生概率分布，从而得到SFEP中边缘事件发生概率分布。将SFN中事件关系表示为关系组从而叠加关系，得到最终事件发生概率分布解析式计算分布。研究表明，所得结果与原有精确结果具有较高的符合性，但所需故障数据则少得多。可借助该方法在少故障数据条件下研究SFEP最终事件发生特征。
- Abstract:
- To get suitable probability distribution of the target event in the system fault evolution process (SFEP) with less fault data, we propose a calculation method of the probability distribution of the target event occurrence considering the information diffusion and less data. This method uses the information diffusion principle to form a normal distribution in the study area with the factors at the event occurrence as the center. Take the maximum value for many times of occurrence of the same event in the study area, forming the probability distribution of the event occurrence. Thereby, the probability distribution of the edge event occurrence in the SFEP is obtained. The event relationships in SFN are expressed as relationship set and then the relationships are superposed, and the analytic formula of probability distribution of target event occurrence is obtained. The research shows that the results are in good agreement with the original accurate results with much less fault data. This method can be used to study the target event occurrence characteristics of SFEP under the condition of less fault data.
- 参考文献/References:
-
[1] 崔铁军, 李莎莎, 朱宝岩. 空间故障网络及其与空间故障树的转换[J]. 计算机应用研究, 2019, 36(8): 2400–2403
CUI Tiejun, LI Shasha, ZHU Baoyan. Construction space fault network and recognition network structure characteristic[J]. Application research of computers, 2019, 36(8): 2400–2403
[2] 崔铁军, 李莎莎, 朱宝艳. 含有单向环的多向环网络结构及其故障概率计算[J]. 中国安全科学学报, 2018, 28(7): 19–24
CUI Tiejun, LI Shasha, ZHU Baoyan. Multidirectional ring network structure with one-way ring and its fault probability calculation[J]. China safety science journal, 2018, 28(7): 19–24
[3] CUI Tiejun, LI Shasha. Research on complex structures in space fault network for fault data mining in system fault evolution process[J]. IEEE access, 2019, 7: 121881–121896.
[4] 崔铁军, 李莎莎. 空间故障树与空间故障网络理论综述[J]. 安全与环境学报, 2019, 19(2): 399–405
CUI Tiejun, LI Shasha. Revision of the space fault tree and the space fault network system[J]. Journal of safety and environment, 2019, 19(2): 399–405
[5] 崔铁军. 空间故障树理论研究[D]. 阜新: 辽宁工程技术大学, 2015.
CUI Tiejun. Research on space fault tree theory[D]. Fuxin: Liaoning Technology University, 2015.
[6] 崔铁军, 马云东. 基于多维空间事故树的维持系统可靠性方法研究[J]. 系统科学与数学, 2014, 34(6): 682–692
CUI Teijun, MA Yundong. Research on the maintenance method of system reliability based on multi-dimensional space fault tree[J]. Journal of systems science and mathematical sciences, 2014, 34(6): 682–692
[7] 崔铁军, 马云东. 系统可靠性决策规则发掘方法研究[J]. 系统工程理论与实践, 2015, 35(12): 3210–3216
CUI Tiejun, MA Yundong. The method research on decision criterion discovery of system reliability[J]. Systems engineering—theory & practice, 2015, 35(12): 3210–3216
[8] 崔铁军, 马云东. DSFT的建立及故障概率空间分布的确定[J]. 系统工程理论与实践, 2016, 36(4): 1081–1088
CUI Tiejun, MA Yundong. Discrete space fault tree construction and failure probability space distribution determination[J]. Systems engineering—theory & practice, 2016, 36(4): 1081–1088
[9] 崔铁军, 马云东. DSFT中因素投影拟合法的不精确原因分析[J]. 系统工程理论与实践, 2016, 36(5): 1340–1345
CUI Tiejun, MA Yundong. Inaccurate reason analysis of the factors projection fitting method in DSFT[J]. Systems engineering—theory & practice, 2016, 36(5): 1340–1345
[10] LI Shasha, CUI Tiejun, LIU Jian. Study on the construction and application of cloudization space fault tree[J]. Cluster computing, 2019, 22(3): 5613–5633.
[11] CUI Tiejun, LI Shasha. Study on the construction and application of discrete space fault tree modified by fuzzy structured element[J]. Cluster computing, 2019, 22(3): 6563–6577.
[12] 崔铁军, 汪培庄, 马云东. 01SFT中的系统因素结构反分析方法研究[J]. 系统工程理论与实践, 2016, 36(8): 2152–2160
CUI Tiejun, WANG Peizhuang, MA Yundong. Inward analysis of system factor structure in 01 space fault tree[J]. Systems engineering—theory & practice, 2016, 36(8): 2152–2160
[13] CUI Tiejun, WANG Peizhuang, LI Shasha. The function structure analysis theory based on the factor space and space fault tree[J]. Cluster computing, 2017, 20(2): 1387–1399.
[14] 崔铁军, 马云东. 基于因素空间的煤矿安全情况区分方法的研究[J]. 系统工程理论与实践, 2015, 35(11): 2891–2897
CUI Tiejun, MA Yundong. Research on the classification method about coal mine safety situation based on the factor space[J]. Systems engineering—theory & practice, 2015, 35(11): 2891–2897
[15] CUI Tiejun, LI Shasha. Study on the relationship between system reliability and influencing factors under big data and multi-factors[J]. Cluster computing, 2019, 22(4): 10275–10297.
[16] LI Shasha, CUI Tiejun, LIU Jian. Research on the clustering analysis and similarity in factor space[J]. International journal of computer systems science & engineering, 2018, 33(5): 397–404.
[17] 吴昀璞, 金炜东, 任俊箫. 基于孪生卷积网络的高速列车转向架故障辨识[J]. 系统仿真学报, 2019, 31(11): 2562–2568
WU Yunpu, JIN Weidong, REN Junxiao. Fault identification of high-speed train bogie based on Siamese convolutional neural network[J]. Journal of system simulation, 2019, 31(11): 2562–2568
[18] 刘俊辰, 唐文秀, 金剑桥, 等. 基于改进SVDD算法的升降机轴承故障检测研究[J]. 重庆理工大学学报(自然科学), 2019, 33(7): 66–73
LIU Junchen, TANG Wenxiu, JIN Jianqiao, et al. Bearing fault detection method of elevator based on improved SVDD algorithm[J]. Journal of chongqing university of technology (natural science edition), 2019, 33(7): 66–73
[19] 张青青. 基于改进AlexNet的滚动轴承变工况故障诊断研究[D]. 兰州: 兰州理工大学, 2019.
ZHANG Qingqing. Research on fault diagnosis of rolling bearings under variable conditions based on improved AlexNet[D]. Lanzhou: Lanzhou University of Technology, 2019.
[20] 姜京男. 基于工况因素聚类分析的数控机床小样本可靠性建模[D]. 长春: 吉林大学, 2019.
JIANG Jinnan. Reliability modeling of NC machine tools with small samples based on clustering analysis of working conditions[D]. Changchun: Jilin University, 2019.
[21] 吕菲亚. 基于栈式自编码网络的故障诊断方法研究[D]. 杭州: 浙江大学, 2019.
LYU Feiya. Stacked autoencoder network based fault diagnosis[D]. Hangzhou: Zhejiang University, 2019.
[22] 赵江平, 丁洁, 陈敬龙. 基于GM-SVR的小样本条件下化工设备可靠性预测[J]. 中国安全生产科学技术, 2019, 15(1): 145–150
ZHAO Jiangping, DING Jie, CHEN Jinglong. Reliability prediction of chemical equipment under small sample condition based on GM and SVR[J]. Journal of safety science and technology, 2019, 15(1): 145–150
[23] 吴迪, 林国汉, 胡慧, 等. 基于指数正则化零空间鉴别分析的故障识别[J]. 系统科学与数学, 2018, 38(10): 1128–1139
WU Di, LIN Guohan, HU Hui, et al. Fault recognition based on exponential regularized null space linear discriminant analysis[J]. Journal of systems science and mathematical sciences, 2018, 38(10): 1128–1139
[24] 王妍. 小样本数据下数控刀架可靠性研究及其应用[D]. 吉林: 东北电力大学, 2018.
WANG Yan. Research and application of the reliability of CNC turret under small samples[D]. Jilin: Northeast Electric Power University, 2018.
[25] 朱孟兵. 基于小样本数据的数控机床MTBF评估[D]. 沈阳: 东北大学, 2012.
ZHU Mengbing. MTBF evaluation for CNC system based on small sample data[D]. Shenyang: Northeastern University, 2012.
[26] 渠寒花, 张国斌, 何险峰. 气象灾害形式概念分析模型[J]. 计算机工程与设计, 2019, 40(2): 516–522
QU Hanhua, ZHANG Guobin, HE Xianfeng. Formal concept analysis model of meteorological disasters[J]. Computer engineering and design, 2019, 40(2): 516–522
[27] 胡钢, 徐翔, 过秀成. 基于解释结构模型的复杂网络节点重要性计算[J]. 浙江大学学报(工学版), 2018, 52(10): 1989–1997, 2022
HU Gang, XU Xiang, GUO Xiucheng. Importance calculation of complex network nodes based on interpretive structural modeling method[J]. Journal of Zhejiang University (engineering science edition), 2018, 52(10): 1989–1997, 2022
[28] 张英, 李江涛. 基于系统动力学的数据化作战指挥模式分析[J]. 指挥控制与仿真, 2019, 41(2): 31–36
ZHANG Ying, LI Jiangtao. Analysis of data-based command based on system dynamics[J]. Command control & simulation, 2019, 41(2): 31–36
[29] 聂银燕, 林晓焕. 基于SDG的压缩机故障诊断方法研究[J]. 微电子学与计算机, 2013, 30(3): 140–142
NIE Yinyan, LIN Xiaohuan. Research on the fault diagnosis of compressor based on the SDG method[J]. Microelectronics & computer, 2013, 30(3): 140–142
- 相似文献/References:
-
[1]崔铁军,汪培庄.空间故障树与因素空间融合的智能可靠性分析方法[J].智能系统学报,2019,14(5):853.[doi:10.11992/tis.201807022]
CUI Tiejun,WANG Peizhuang.Intelligent reliability analysis method based on space fault tree and factor space[J].CAAI Transactions on Intelligent Systems,2019,14():853.[doi:10.11992/tis.201807022]
[2]崔铁军,李莎莎.系统故障因果关系分析的智能驱动方式研究[J].智能系统学报,2021,16(1):92.[doi:10.11992/tis.202003001]
CUI Tiejun,LI Shasha.Intelligent analysis of system fault data and fault causal relationship[J].CAAI Transactions on Intelligent Systems,2021,16():92.[doi:10.11992/tis.202003001]
[3]崔铁军,李莎莎.人工智能系统故障分析原理研究[J].智能系统学报,2021,16(4):785.[doi:10.11992/tis.202003046]
CUI Tiejun,LI Shasha.Research on system fault analysis principle based on artificial intelligence system[J].CAAI Transactions on Intelligent Systems,2021,16():785.[doi:10.11992/tis.202003046]
[4]崔铁军,李莎莎.线性熵的系统故障熵模型及其时变研究[J].智能系统学报,2021,16(6):1136.[doi:10.11992/tis.202006034]
CUI Tiejun,LI Shasha.System fault entropy model and its time-varying based on linear entropy[J].CAAI Transactions on Intelligent Systems,2021,16():1136.[doi:10.11992/tis.202006034]
[5]崔铁军,李莎莎.基于集对分析的SFT特征函数重构及性质研究[J].智能系统学报,2022,17(1):131.[doi:10.11992/tis.202007020]
CUI Tiejun,LI Shasha.Reconstruction of SFT characteristic function and its properties based on set pair analysis[J].CAAI Transactions on Intelligent Systems,2022,17():131.[doi:10.11992/tis.202007020]
[6]崔铁军,李莎莎.多因素集对分析的系统故障模式识别方法[J].智能系统学报,2022,17(2):387.[doi:10.11992/tis.202011006]
CUI Tiejun,LI Shasha.System fault-pattern recognition based on set pair analysis with multiple factors[J].CAAI Transactions on Intelligent Systems,2022,17():387.[doi:10.11992/tis.202011006]
[7]崔铁军,李莎莎.联系数和属性多边形的系统故障模式识别[J].智能系统学报,2022,17(3):568.[doi:10.11992/tis.202011019]
CUI Tiejun,LI Shasha.System fault pattern recognition based on the connection number and attribute polygon[J].CAAI Transactions on Intelligent Systems,2022,17():568.[doi:10.11992/tis.202011019]
[8]崔铁军,李莎莎.系统故障演化过程熵及其受逻辑关系的影响研究[J].智能系统学报,2024,19(3):749.[doi:10.11992/tis.202209036]
CUI Tiejun,LI Shasha.Study on entropy of system fault evolution process and its influence on logical relationships[J].CAAI Transactions on Intelligent Systems,2024,19():749.[doi:10.11992/tis.202209036]
[9]崔铁军,李莎莎.SFEP文本因果关系提取及其与SFN转化研究[J].智能系统学报,2020,15(5):998.[doi:10.11992/tis.201907021]
CUI Tiejun,LI Shasha.Causality extraction of SFEP text and its conversion to SFN[J].CAAI Transactions on Intelligent Systems,2020,15():998.[doi:10.11992/tis.201907021]
[10]崔铁军,李莎莎.空间故障网络的柔性逻辑描述[J].智能系统学报,2021,16(3):552.[doi:10.11992/tis.202003029]
CUI Tiejun,LI Shasha.Flexible logic description of space fault network[J].CAAI Transactions on Intelligent Systems,2021,16():552.[doi:10.11992/tis.202003029]
备注/Memo
收稿日期:2019-11-06。
基金项目:国家自然科学基金项目(51704141)；国家重点研发计划项目(2017YFC1503102)；国家自然科学基金委主任基金项目(61350003)
作者简介:崔铁军，副教授，博士，主要研究方向为系统可靠性及力学系统稳定性，提出和建立了空间故障树理论及空间故障网络理论。取得发明专利19项，发表学术论文100余篇，出版学术专著4部; 李莎莎，讲师，博士，主要研究方向为安全管理及其智能分析。取得发明专利5项，发表学术论文10余篇，出版学术专著2部
通讯作者:崔铁军.E-mail:ctj.159@163.com
更新日期/Last Update:
1900-01-01