|本期目录/Table of Contents|

[1]张宇栋,卿黎,牛犇.焊接结构失效事故征候的灰色马尔科夫预测[J].中国安全生产科学技术,2015,11(2):131-137.[doi:10.11731/j.issn.1673-193x.2015.02.022]
 ZHANG Yu-dong,QING Li,NIU Ben.Prediction of welding structure failure incidents based on grey Markov model[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2015,11(2):131-137.[doi:10.11731/j.issn.1673-193x.2015.02.022]
点击复制

焊接结构失效事故征候的灰色马尔科夫预测
分享到:

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
11
期数:
2015年2期
页码:
131-137
栏目:
职业安全卫生管理与技术
出版日期:
2015-02-28

文章信息/Info

Title:
Prediction of welding structure failure incidents based on grey Markov model
作者:
张宇栋1 卿黎1 牛犇2
(1. 昆明理工大学 国土资源工程学院,云南 昆明650093;2. 昆明锅炉有限责任公司, 云南 昆明650217)
Author(s):
ZHANG Yu-dong1 QING Li1 NIU Ben2
1. Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming Yunnan 650093, China; 2. Kunming Boiler Co., Ltd., Kunming Yunnan 650217, China)
关键词:
灰色预测马尔科夫链锅炉压力容器焊接结构失效事故征候
Keywords:
grey predictionMarkov chainsboiler and pressure vesselwelding structure failureincidents
分类号:
X933
DOI:
10.11731/j.issn.1673-193x.2015.02.022
文献标志码:
A
摘要:
焊接结构的可靠性,是锅炉压力容器特种设备安全研究的重要内容。将事故征候的预测研究引入锅炉压力容器特种设备的焊接结构安全分析的研究领域,通过灰色预测理论模型GM(1,1)与马尔科夫链预测理论模型相结合,利用两者的优点,不仅提高了对波动性较大的随机变量的预测结果可靠度,同时延展了灰色预测的应用。结合应用算例,将灰色马尔科夫预测模型与传统的GM(1,1)在焊接结构失效事件的前瞻性预测中的应用进行了对比,灰色马尔科夫预测模型对焊接结构失效事件的预测精度在98% 以上,且较GM(1,1)模型预测结果的精度平均提高了近4%,能够消除GM(1,1)模型的固有偏差。灰色马尔科夫预测模型符合对锅炉压力容器特种设备焊接结构安全研究的实际要求。
Abstract:
The reliability of welding structure in boiler and pressure vessel is an important research in the field of safety science about special equipment. Through the combination of grey prediction model GM(1,1) and Markov chains prediction model, by taking advantage of the two theory models, the study on prediction of incidents was introduced into the safety analysis on welding structure of boiler and pressure vessel. It not only improves the prediction reliability of the random variables with larger fluctuation, but also extends the application of grey prediction. Combined with the practical example, the application of grey Markov model in prospective prediction of welding structure failure incidents was compared with that by traditional GM(1,1) model. It showed that the prediction accuracy of the welding structure failure incidents reached 98% by means of grey Markov prediction model, which was almost 4% higher than that by the GM(1,1)model with inherent deviation. The prediction method of grey Markov model meets the actual requirements of safety research on welding structure for the special equipment of boiler and pressure vessel.

参考文献/References:

[1]王永刚, 吕学梅. 民航事故征候的灰色马尔可夫预测[J]. 安全与环境学报, 2008, 8(1): 163-165 WANG Yong-gang, LV Xue-mei. Grey Markov Model for forecasting civil aviation incidents[J]. Journal of Safety and Environment, 2008, 8(1): 163-165
[2]霍志勤, 罗帆. 近十年中国民航事故及事故征候的统计分析[J]. 中国安全科学学报, 2006, 16(12): 65-71 HUO Zhi-qin, LUO Fan. Statistic analysis on accidents and incidents in the last decade in China civil aviation[J]. China Safety Science Journal, 2006, 16(12): 65-71
[3]龙会国, 龙毅, 陈红冬. 高温再热器T23 / 12Cr1MoV异种钢焊缝失效机理[J]. 中国电力, 2011, 44(5): 70-73 LONG Hui-guo, LONG Yi, CHEN Hong-dong. Mechanism of T23/12CrlMoV dissimilar steel welding failure in high temperature reheater[J]. Electric Power, 2011, 44(5): 70-73
[4]何勇, 鲍一丹. 灰色马尔可夫预测模型及其应用[J]. 系统工程理论与实践, 1992, 4(7): 59-63 HE Yong, BAO Yi-dan. Grey-Markov forecasting model and its application[J]. Systems Engineering Theory &Practice, 1992, 4(7): 59-63
[5]蒲伟, 卿黎, 牛犇. 模糊综合评价法在锅炉焊缝安全评定中的应用[J]. 安全与环境学报, 2014, 14(4): 115-119 PU Wei, QING Li, NIU Ben. Application of fuzzy comprehensive evaluation method on safety assessment of the boiler welding seam[J]. Journal of Safety and Environment, 2014, 14(4): 115-119
[6]杨锦伟, 孙宝磊. 基于灰色马尔科夫模型的平顶山市空气污染物浓度预测[J]. 数学的实践与认识, 2014, 44(2): 64-70 YANG Jin-weil, SUN Bao-lei. The prediction of air pollutant concentration in Pingdingshan based on Grey Markov Model[J]. Mathematics in Practice and Theory, 2014, 44(2): 64-70
[7]肖新平, 毛树华. 灰色预测与决策[M]. 北京: 科学出版社, 2013
[8]林岩, 陈帅, 陈燕, 等. 道路交通事故的灰色马尔科夫预测模型与算法[J]. 武汉理工大学学报(交通科学与工程版), 2013, 37(5): 924-928 LIN Yan, CHEN Shuai, CHEN Yan, et al. Grey-Markov model and algorithm for traffic accidents forecasting[J]. Journal of Wuhan University of Technology(Transportation Science & Engineering), 2013, 37(5): 924-928
[9]刘永阔, 谢春丽, 于竹君, 等. 基于GM(1,1)模型与灰色马尔可夫GM(1,1)模型的核动力装置趋势预测方法研究[J]. 原子能科学技术, 2011, 45(9): 1075-1097 LIU Yong-kuo, XIE Chun-li, YU Zhu-jun, et al. Trend prediction methods study of nucIear power plant based on GM(1,1) and Grey-Markov GM(1,1) models[J]. Atomic Energy Science and Technology, 2011, 45(9): 1075-1097
[10]陈忠兵, 赵彦芬, 赵建仓, 等.厚壁12Cr1MoVG钢焊接接头裂纹分析及其控制[J]. 中国电机工程学报, 2012, 32(35): 137-143 CHEN Zhong-bing, ZHAO Yan-fen, ZHAO Jian-cang, et al. Analysis and control for cracks in welded joint of thick walled steel 12CrlMoVG[J]. Proceedings of the Chinese Society for Electrical Engineering, 2012, 32(35): 137-143
[11]陈睿. 钛合金焊接原始疲劳质量评估[D]. 南昌航空大学, 2011, 6
[12]崔庆玲, 罗云, 崔刚, 等. 基于灰色理论的特种设备安全事故预测研究[J]. 中国安全生产科学技术, 2013, 9(5): 141-144 CUI Qing-ling, LUO Yun, CUI Gang, et al. Study on prediction of special equipment accident based on grey theory[J]. Journal of Safety Science and Technology, 2013, 9(5): 141-144
[13]赵玲, 许宏科. 基于改进的灰色马尔可夫链模型的交通事故预测[J]. 数学的实践与认识, 2013, 43(20): 92-98 ZHAO Ling, XU Hong-ke. Traffic accident prediction based on improved Grey-Markov chain Model[J]. Mathematics in Practice and Theory, 2013, 43(20): 92-98
[14]陈钊, 徐阿猛.基于灰色马尔科夫模型的钻孔瓦斯流量预测[J]. 中国安全科学学报, 2012, 22(3): 79-85 CHEN Zhao, XU A-meng.Prediction of gas flow-rate from boreholes based on Grey-Markov model[J]. China Safety Science Journal, 2012, 22(3): 79-85
[15]姜翔程, 陈森发. 加权马尔可夫SCGM(1,1)c模型在农作物干旱受灾面积预测中的应用[J]. 系统工程理论与实践, 2009, 29(9): 179-185 JIANG Xiang-cheng, CHEN Sen-fa. Application of weighted Markov SCGM(1,1)c model to predict drought crop area[J]. Systems Engineering Theory and Practice,2009, 29(9): 179-185

相似文献/References:

[1]高扬,王向章.基于SPA-Markov的飞行安全态势评估与预测研究[J].中国安全生产科学技术,2016,12(8):87.[doi:10.11731/j.issn.1673-193x.2016.08.014]
 GAO Yang,WANG Xiangzhang.Research on assessment and prediction of flight safety situation based on SPA-Markov[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(2):87.[doi:10.11731/j.issn.1673-193x.2016.08.014]
[2]孙钦莹,李向阳.基于随机Petri网的跨组织应急协同模型构建[J].中国安全生产科学技术,2015,11(9):63.[doi:10.11731/j.issn.1673-193x.2015.09.010]
 SUN Qin-ying,LI Xiang-yang.Establishment of emergency coordination model across organizations based on stochastic Petri net[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2015,11(2):63.[doi:10.11731/j.issn.1673-193x.2015.09.010]
[3]邓兵兵,代宝乾,汪彤.基于Isograph的地铁车载ATP系统动态故障树分析[J].中国安全生产科学技术,2016,12(5):80.[doi:10.11731/j.issn.1673-193x.2016.05.014]
 DENG Bingbing,DAI Baoqian,WANG Tong.Dynamic fault tree analysis of on-board ATP system in metro based on Isograph[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(2):80.[doi:10.11731/j.issn.1673-193x.2016.05.014]
[4]王起全,飞禹舟,任国友.职工群体性突发事件发生原因演化分析及对策研究[J].中国安全生产科学技术,2016,12(5):180.[doi:10.11731/j.issn.1673-193x.2016.05.031]
 WANG Qiquan,FEI Yuzhou,REN Guoyou.Study on reasons evolution analysis and countermeasures of workers mass emergency[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(2):180.[doi:10.11731/j.issn.1673-193x.2016.05.031]
[5]晋良海,吴菊华,余迪,等.水电厂电力设备事故应急响应FPN-MC模型及效能分析[J].中国安全生产科学技术,2017,13(4):123.[doi:10.11731/j.issn.1673-193x.2017.04.020]
 JIN Lianghai,WU Juhua,YU Di,et al.FPN-MC model on emergency response of electrical equipment accident in hydro-power plant and its performance analysis[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2017,13(2):123.[doi:10.11731/j.issn.1673-193x.2017.04.020]

备注/Memo

备注/Memo:
昆明理工大学自然科学研究基金资助项目(KKSY201321083)
更新日期/Last Update: 2015-02-28