Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (12): 2892-2897.doi: 10.13229/j.cnki.jdxbgxb20211278

Previous Articles     Next Articles

Risk identification method of foundation pit engineering of high⁃rise buildings based on fuzzy clustering maximum tree algorithm

Han-chao LIAO(),Mi-yuan SHAN()   

  1. School of Business,Hunan University,Changsha 410082,China
  • Received:2021-11-27 Online:2022-12-01 Published:2022-12-08
  • Contact: Mi-yuan SHAN E-mail:liaohanchao2152@yeah.net;shanmiyuan@163.com

Abstract:

In view of the limitations of foundation pit engineering investigation and the temporary nature of the project, a risk identification method of high-rise building foundation pit engineering based on fuzzy clustering maximum tree algorithm was proposed. The fuzzy similarity matrix was established by the absolute value subtraction method, the risk index data was standardized, and the risk evaluation index was used to divide the risk level of foundation pit construction. Using fuzzy clustering to quantitatively influence the coupling relationship between elements, the maximum tree structure in the form of undirected connected weight graph was described, and the risk identification was realized through the connected vertices in the connection tree structure. The simulation results show that the proposed method can accurately describe the specific location of the risk while determining the risk level of foundation pit engineering, and the recognition accuracy and efficiency can meet the expected requirements with strong robustness.

Key words: foundation pit construction, fuzzy clustering, maximum tree algorithm, risk identification, evaluating indicator

CLC Number: 

  • TU94

Fig.1

Risk evaluation index system of foundation pit engineering"

Table 1

Risk classification results of foundation pit engineering"

风险评价系数取值施工风险水平风险级别
0~0.2微弱风险1
0.2~0.4弱风险2
0.4~0.6中风险3
0.6~0.8强风险4
0.8~1.0高强风险5

Table 2

Risk identification results of foundation pit engineering by this method"

监测项目指标桩体水平位移地表沉降地下水位
累积量/mm速率/(mm·d?1累积量/mm速率/(mm·d?1累积量/mm速率/(mm·d?1
监测值36.520.6115.430.941084254
指标风险概率0.930.040.150.110.130.11
监测项风险概率0.7430.1150.156
总体风险概率0.548

Fig.2

Schematic diagram of dynamic change of foundation pit risk identification"

Fig.3

Comparison of risk identification results of three methods for foundation pit engineering"

Fig.4

Comparison of risk identification efficiency of three methods for foundation pit"

1 钟春玲,梁东,张云龙,等. 体外预应力钢-混凝土组合简支梁自振频率计算[J].吉林大学学报:工学版,2020,50(6):2159-2166.
Zhong Chun-ling, Liang Dong, Zhang Yun-long, et al. Calculation of natural frequency of externally prestressed steel-concrete composite simply supported beams[J]. Journal of Jilin University(Engineering and Technology Edition), 2020,50(6):2159-2166.
2 钱雪忠,姚琳燕. 面向稀疏高维大数据的扩展增量模糊聚类算法[J]. 计算机工程,2019,45(6):75-81, 88.
Qian Xue-zhong, Yao Lin-yan. Extended incremental fuzzy clustering algorithm for sparse high-dimensional big data[J]. Computer Engineering, 2019,45(6):75-81, 88.
3 Ren X, Fan W, Li J, et al. Building information model-based finite element analysis of high-rise building community subjected to extreme earthquakes[J]. Advances in Structural Engineering, 2019, 22(4):971-981.
4 王飞球,黄健陵,符竞,等. 基于BP神经网络的跨既有线高速铁路桥梁施工安全风险评估[J].铁道科学与工程学报,2019,16(5):1129-1136.
Wang Fei-qiu, Huang Jian-ling, Fu Jing, et al. Risk assessment of construction safety of high-speed railway bridge across existing lines based on BP neural network[J]. Journal of Railway Science and Engineering, 2019,16(5):1129-1136.
5 华莹,何军,赵金城. 高层建筑施工现场危险区域识别及评估方法研究[J].施工技术,2019,48(6):100-104.
Hua Ying, He Jun, Zhao Jin-cheng. Research on identification and evaluation method of hazardous area of high-rise building construction site[J]. Construction Technology, 2019, 48(6):100-104.
6 Nakaguro M, Sato Y, Tada Y, et al. Prognostic implication of histopathologic indicators in salivary duct carcinoma: proposal of a novel histologic risk stratification model[J]. American Journal of Surgical Pathology, 2019, 44(4):526-535.
7 荀志远,张丽敏,徐瑛莲,等. 基于组合赋权云模型的装配式建筑安全风险评价[J]. 数学的实践与认识,2020,50(7):302-310.
Xun Zhi-yuan, Zhang Li-min, Xu Ying-lian, et al. Evaluation of prefabricated buildings safety risk based on combination weighting and cloud model[J]. Mathematics in Practice and Theory, 2020,50(7):302-310.
8 Wang W Y, Wang Y. Diagnosis index system setup for implementation status management in large-scale construction projects[J]. Mathematical Problems in Engineering, 2021(1): 1-9.
9 郭文娟. 大数据背景下的房屋建筑施工风险评估模型[J]. 科技通报,2019,35(4):198-201.
Guo Wen-juan. Risk assessment model for building construction under the background of big data[J]. Bulletin of Science and Technology, 2019,35(4):198-201.
10 Chen W, Zhang G, Jiao Y, et al. Unascertained measure-set pair analysis model of collapse risk evaluation in mountain tunnels and its engineering application[J]. KSCE Journal of Civil Engineering, 2020, 25(6):1-17.
11 李蒙,邹健,刘苹,等. 基于BIM的隧道施工安全风险辨识模型研究[J].工业安全与环保,2019,45(5):69-71.
Li Meng, Zou Jian, Liu Ping, et al. Research on tunnel construction safety risk identification model based on BIM[J]. Industrial Safety and Environmental Protection, 2019,45(5):69-71.
12 Lu Y, Gong P, Tang Y, et al. BIM-integrated construction safety risk assessment at the design stage of building projects[J]. Automation in Construction, 2021, 124(2): No.103553.
13 黄俊斌,张国维,闫肃,等. 基于物联网技术的建筑火灾风险动态评估[J]. 消防科学与技术,2020,39(10):1371-1375.
Huang Jun-bin, Zhang Guo-wei, Yan Su, et al. Dynamic assessment of building fire risk based on internet of things technology[J]. Fire Science and Technology, 2020,39(10):1371-1375.
14 Baat M, Wieringa N, Droge S, et al. Smarter sediment screening: effect-based quality assessment, chemical profiling, and risk identification[J]. Environmental Science and Technology, 2019, 53(24):14479-14488.
15 吴贤国,冯宗宝,秦文威,等. 基于物元理论和证据理论的盾构隧道施工邻近建筑物风险评价[J].铁道标准设计,2020,64(4):104-110.
Wu Xian-guo, Feng Zong-bao, Qin Wen-wei, et al. Risk assessment of adjacent buildings induced by shield tunneling construction based on matter-element theory and extension theory[J]. Railway Standard Design, 2020,64(4):104-110.
16 Man S S, Chan A, Alabdulkarim S. Quantification of risk perception: development and validation of the construction worker risk perception(CoWoRP) scale[J]. Journal of Safety Research, 2019, 71:25-39.
17 Yang J, Wang J, Wei G, et al. An adaptive probabilistic mapping matrix search algorithm for vulnerability analysis of PPS[J]. Annals of Nuclear Energy, 2019, 131:433-442.
18 李依霖. 复杂网络隐私信息传输入侵风险评估仿真[J].计算机仿真,2020,37(6):156-159, 164.
Li Yi-lin. Intrusion risk assessment simulation of big data privacy information transmission in complex network[J]. Computer Simulation, 2020,37(6):156-159, 164.
19 Kayhan B M, Cebi S, Kahraman C. Determining and prioritizing main factors of supplier reliability in construction industry[J]. Journal of Multiple-valued Logic and Soft Computing, 2019, 32(1/2):111-134.
20 Stewart M G, Li J. Risk-based assessment of blast-resistant design of ultra-high performance concrete columns[J]. Structural Safety, 2021, 88(3):No.102030.
[1] SI Jian-bo, YAO Yan, GUO Wei-ying, YANG Fang. Web user cluster method and realization based on fuzzy clustering [J]. 吉林大学学报(工学版), 2013, 43(增刊1): 485-488.
[2] LU Shan, LEI Ying-jie, KONG Wei-wei, LEI Yang, ZHENG Kou-quan. Robust fundamental matrix estimation based on kernel fuzzy clustering [J]. 吉林大学学报(工学版), 2012, 42(02): 434-439.
[3] SHEN Xuan-jing, WANG Kai-ye, QIAN Qing-ji, LIU Ying-jie, LI Xiang. Image segmentation using adaptive balloon force snake model [J]. 吉林大学学报(工学版), 2011, 41(05): 1394-1400.
[4] Xu Xin-wei,Zhou Liang,Xu Xiao-ming, Ding Qiu-lin . User intention recognition for Web initiative services based
on hybrid intelligent mining
[J]. 吉林大学学报(工学版), 2007, 37(02): 419-0423.
[5] Lu Ying-rong,Yang Yin-sheng,Lv Feng . Optimal vehicle routing problem based on fuzzy clustering analysis [J]. 吉林大学学报(工学版), 2006, 36(增刊2): 147-151.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] Hu Zong-Jie,Wu Zhi-jun,Gao Guang-hai,Li Li-guang . Optimization of premixed diesel homogeneous charge preparation by spray hot-impingement[J]. 吉林大学学报(工学版), 2007, 37(01): 79 -84 .
[2] Wang Qing-nian,Zheng Jun-feng,Wang Wei-hua . New adaptive control strategy of parallel hybrid electric bus[J]. 吉林大学学报(工学版), 2008, 38(02): 249 -0253 .
[3] Dong Wei, Yu Xiu-min, Zhang You-kun . CVT control strategies for engine brake on long downhill of vehicle [J]. 吉林大学学报(工学版), 2006, 36(05): 650 -0653 .
[4] . [J]. 吉林大学学报(工学版), 2007, 37(06): 1392 -1396 .
[5] Dong Jing, Zhao Xiao-hui, Ying Na. Pitch detection algorithm based on dyadic wavelet transforms[J]. 吉林大学学报(工学版), 2006, 36(06): 978 -0982 .
[6] HE Ren, CHEN Qiang-Zhang. Vehicle regenerative braking using dual switched reluctance motors/generators[J]. 吉林大学学报(工学版), 2009, 39(05): 1137 -1141 .
[7] LI Suo-jun,GAO Hai-bo,DENG Zong-quan. Multi-objective optimization of rocker-bogie suspension parameters of  lunar rover for energy-saving passing obstacle[J]. 吉林大学学报(工学版), 2010, 40(03): 729 -0734 .
[8] MENG Ling-qi,DU Yong,MA Sheng-biao,GUO Bin . Nonlinearity of vertical vibration of medium plate mill [J]. 吉林大学学报(工学版), 2009, 39(03): 712 -0715 .
[9] ZHAO Shu-zhi,ZHU Yong-gang,ZHAO Bei. Study on capacity forecast of urban cars based on environmental protection[J]. 吉林大学学报(工学版), 2009, 39(增刊2): 191 -0193 .
[10] YUAN Yue-ming, GUAN Wei, QIU Wei. Map matching algorithm for inner suburban freeway based on handover location technique[J]. 吉林大学学报(工学版), 2011, 41(05): 1240 -1245 .