Association analysis on CAD design and manufacturing defect cases

doi:10.16265/j.cnki.issn 1003-3033.2021.11.008

Abstract

Abstract: In order to effectively prevent aviation safety incidents and find potential correlation between them, correlation of design and manufacturing defect cases reflected by CAD was analyzed. Firstly, rules of attribute extraction were developed for CAD. Then, risk levels of failure was taken as decision attributes to reduce condition attribute by using rough set model of incomplete information system. Finally, FP-growth algorithm was used to discover rules of vulnerable parts, event causes, accident levels, and treatment measures, so as to find out the internal relations among factors that cause unairworthiness or unsafe operation due to incompliance with operation regulation. The results show that association analysis of cases can extract rules with high confidence after rough set reduction, which is helpful for airworthiness management agencies to make corresponding decisions.

Key words: China airworthiness directive (CAD), design and manufacturing defect, rough set, FP-growth algorithm, incomplete information system, association rules

CLC Number:

X949

CAO Huiling, HU Yanjie. Association analysis on CAD design and manufacturing defect cases[J]. China Safety Science Journal, 2021, 31(11): 54-63.

References

[1] ZDZISLAW P. Rough sets and fuzzy sets[J]. Fuzzy Sets and Systems, 1985,17(1):99-102.
[2] 贾宝惠, 黄婕, 王玉鑫,等. 航空发动机单元体送修等级决策方法研究[J]. 机械科学与技术, 2018,37(3):487-492.
JIA Baohui, HUANG Jie, WANG Yuxin, et al. Research on decision-making method of maintenance level for aero engine module [J]. Mechanical Science and Technology for Aerospace Engineering, 2018,37(3):487-492.
[3] 王岩韬, 唐建勋, 赵嶷飞. 基于粗糙集和支持向量机的航班运行风险预测[J]. 中国安全科学学报, 2017,27(9):158-163.
WANG Yantao, TANG Jianxun, ZHAO Yifei. Prediction of risks in flight operations based on rough sets and support vector machine [J]. China Safety Science Journal, 2017,27(9):158-163.
[4] 瞿红春, 高鹏宇, 朱伟华,等. 基于邻域粗糙集和灰狼算法优化Elman的民航发动机滑油量预测[J]. 科学技术与工程, 2021,21(14):6 069-6 074.
QU Hongchun, GAO Pengyu, ZHU Weihua, et al. Prediction of aviation engine oil quantity based on neighborhood rough set and Elman optimized by grey wolf algorithm [J]. Science Technology and Engineering, 2021,21(14):6 069-6 074.
[5] 仲秋雁, 王然, 曲毅. 基于粗糙集的突发事件属性约简方法[J]. 运筹与管理, 2018,27(1):89-95.
ZHONG Qiuyan, WANG Ran, QU Yi. A method of attribute reduction for emergency based on rough set [J]. Operations Research and Management Acience, 2018,27(1):89-95.
[6] 冯运卿, 李雪梅, 李学伟. 基于粗糙集的复合属性铁路旅客出行决策影响因素分析与权重计算[J]. 铁道学报, 2014,36(9):1-9.
FENG Yunqing, LI Xuemei, LI Xuewei. Rough set theory based travel decision-making factor analysis and weight calculation for railway passengers of compound attributes[J]. Journal of the China Railway Society, 2014,36(9):1-9.
[7] HAN Jiawei, PEI Jian, YIN Yiwei. Mining frequent patterns without candidate generation[J].Acm Sigmod Record, 2000, 29(2):1-12.
[8] 姬浩, 苏兵, 吕美. 基于FP-growth算法的高校群体性突发事件关联规则分析[J]. 中国安全科学学报, 2012,22(12):144-151.
JI Hao, SU Bing, LYU Mei. Analysis of university mass emergency association rules based on FP-growth algorithm[J]. China Safety Science Journal, 2012,22(12):144-151.
[9] WANG Jun ,PAN Xing,WANG Ligeng, et al. Method of spare parts prediction models evaluation based on grey comprehensive correlation degree and association rules mining: a case study in aviation[J]. Mathematical Problems in Engineering, 2018,2018(1):1-10.
[10] MANFRED J, THOMAS D N, PAOLO V, et al. Query-Focused association rule mining for information retrieval[J]. Frontiers in Artificial Intelligence and Applications, 2013,257(12):245-254.
[11] ZHU Daiwu, NI Yin. The application of data mining in the civil aviation accident analysis[J]. Applied Mechanics and Materials, 2013,241/242/243/244:3 000-3 004.
[12] 王军武, 胡蝶, 吴寒,等. 小直径深层排水隧道盾构施工安全风险评价[J]. 中国安全科学学报, 2020,30(6):113-120.
WANG Junwu, HU Die, WU Han, et al. Risk assessment in construction of small-diameter deep drainage tunnel[J]. China Safety Science Journal, 2020,30(6):113-120.
[13] 王岩韬, 赵嶷飞. 基于多算法协作的航班运行风险辨识研究[J]. 中国安全科学学报, 2018,28(6):166-172.
WANG Yantao, ZHAO Yifei. Research on flight operations risk identification based on multi-algorithm collaboration[J]. China Safety Science Journal, 2018,28(6):166-172.
[14] 曾玲, 何普彦, 付敏. 不完备区间值信息系统的粗糙集约简算法[J]. 南京理工大学学报, 2013,37(4):524-529.
ZENG Ling, HE Puyan, FU Min. Attribute reduction algorithm based on rough set in incompleteinterval-valued information system[J]. Journal of Nanjing University of Science and Technology, 2013,37(4):524-529.
[15] 石夫乾, 孙守迁, 徐江. 基于粗糙集的感性知识关联规则挖掘研究[J]. 计算机集成制造系统, 2008,14(2):407-411,416.
SHI Fuqian, SUN Shouqian, XU Jiang. Association rule mining of Kansei knowledge based on rough set[J]. Computer Integrated Manufacturing Systems, 2008,14(2):407-411,416.
[16] 赵萌,秦金磊,潘一如,等.基于策略权重的模糊多属性决策方法[J]. 控制与决策,2021,36(5):1-9.
ZHAO Meng, QIN Jinlei, PAN Yiru,et al. Strategic weight manipulation in fuzzy multiple attribute decision making[J]. Control and Decision,2021,36(5): 1-9.
[17] 陈兴蜀, 张帅, 童浩,等. 基于布尔矩阵和MapReduce的FP-growth算法[J]. 华南理工大学学报:自然科学版, 2014,42(1):135-141.
CHEN Xingshu, ZHANG Shuai, TONG Hao, et al. FP-growth algorithm based on boolean matrix and MapReduce[J]. Journal of South China University of Technology:Natural Science Edition, 2014,42(1):135-141.
[18] 朱群雄, 赵春, 冯磊,等.关联规则的动态维护及其在财务数据中的应用[J].清华大学学报:自然科学版,2012,52(5):694-698,703.
ZHU Qunxiong, ZHAO Chun, FENG Lei, et al. Dynamic maintenance of association rules and its application in the enterprise financial data[J].Journal of Tsinghua University:Science and Technology, 2012,52(5):694-698,703.
[19] 霍纬纲, 邵秀丽. 基于TD-FP-growth的模糊关联规则挖掘算法[J]. 控制与决策,2009,24(10):1 504-1 508.
HUO Weigang, SHAO Xiuli. Algorithm for mining fuzzy association rule based on TD-FP-growth[J]. Control and Decision, 2009,24(10):1 504-1 508.
[20] YANG Ming, YANG Ping, JI Genlin, et al. Fast FP-growth for association rule mining[J]. Journal of Southeast University, 2003,19(4):320-323.