摘要
提出了一种基于模糊贝叶斯网络模型研究电动平衡车失速事故发生可能性的方法。从物因、人因、环境因素3个角度对电动平衡车的失速原因进行分析,在此基础上构建贝叶斯网络模型,引入三态条件概率进行修正,运用DUOWA算法进行专家群决策,形成电动平衡车失速事故发生可能性评估模型。将该模型运用于具体案例,计算出各基本事件与中间事件的失效概率,得到电动平衡车失速导致用户摔伤的可能性。案例分析结果表明,失速导致用户严重摔伤的可能性概率为0.469,轻微摔伤的可能性概率为0.360,无伤害的可能性概率为0.171。依据模型分析结果分别从硬件、软件、使用角度给出了有针对性的风险控制措施。
Based on the fuzzy Bayesian network model,this paper intends to propose a method for the probability of stalling accidents in self-balancing vehicles in hoping to identify and determine the stall risk of such vehicles.And,for this purpose,we have analyzed the causes of the stall from the following 3 aspects,that is,the material factors(products),the human operating factors and the environmental factors on the basis of clarifying the operating principle of the self-balancing vehicle.The working principle analysis and the stall cause analysis results of the integrated self-balancing vehicle we have proposed can be used to build up the Bayesian network model.And,then,it would be necessary to introduce the 3-state conditional probability of the normal,partial fault and the complete fault to correct the network nodes.Among them,the DUOWA(short for the Depended Uncertain Ordered Weighted Average) algorithm can be used to make the expertise decision for the conditional probability so as to form the possibility assessment model of the self-balancing vehicle stall accidents,which can be adopted to realize the specific case application.Besides,the failure probability of each basic event and the intermediate event can be calculated and worked out the probability that the self-balancing vehicle stall may cause the user to fall.And,finally,the case study indicates that the probability of the stall may cause a serious user's fall to 0.469,with the probability of a minor fall being 0.360 and the probability of no harm being 0.171.Furthermore,in terms of hardware,the risk can be controlled by increasing the motor power margin by improving the battery safety margin and increasing the redundant design of the key circuits.Thus,the analysis results of the evaluation model can help to give the targeted risk control measures.On the other hand,in terms of software,the risk can be controlled by strengthening the functions of the self-checking software system and monitoring the various parameters in the real time.Thus,in terms of usage,i
作者
黄国忠
姜莉文
谢志利
毕琦
王长林
张顶立
HUANG Guo-zhong;JIANG Li-wen;XIE Zhi-li;BI Qi;WANG Chang-lin;ZHANG Ding-li(School of Civil &Resources Engineering,University of Science and Technology Beijing,Beijing 100083,China;SAMR Defec- tive Product Administrative Center,Beijing 100101,China)
出处
《安全与环境学报》
CAS
CSCD
北大核心
2018年第6期2081-2085,共5页
Journal of Safety and Environment
基金
国家重点研发计划子课题(2018YFF0215504)
国家重点研发计划子课题(2018YFF0213106)
中国标准化研究院院长基金项目(282017Y-5303)
关键词
安全工程
电动平衡车
失速
贝叶斯网络
三态条件概率
safety engineering
self-balancing vehicles
stall
Bayesian network
three-state conditional probability
