摘要
针对我国动车组故障影响特点和运用管理要求,按照故障严重程度不同对动车组事故和故障进行分类,制定了动车组A类、B类、C类和D类故障的可靠性指标;依据可靠性工程理论,给出动车组百万km故障率指标定义及其计算式;提出动车组故障率统计分析方法,并对某型动车组寿命周期内故障率变化规律、高级修效果和特定部件周期性故障规律进行分析。结果表明:动车组的早期惯性故障经过有效整治后,故障率显著降低并持续平稳;高级修前故障率呈逐渐上升趋势,高级修后呈微弱的早期故障期,随后明显下降;空调系统的季节性故障率变化趋势分析表明,在每年夏季的6—8月间具有明显的故障率峰值,应强化维修保养措施。示例分析表明,此方法可基于运用维修大数据对动车组故障规律进行验证和分析。
Based on the characteristics of EMU faults and the requirements for the operation and management in China,the accidents and faults of EMU are classified according to the severity of faults,and the reliability indices are formulated for Class A,B,C and D faults of EMU.According to the theory of reliability engineering,the definition and the formula of the fault rate index for every million km of EMU are given.The statistical analysis method for the fault rate of EMU is proposed.The change rule of the fault rate for one type of EMU in its life cycle,the effect of advanced repair and the periodic fault rule of certain components are analyzed.Results show that after the early inertia faults of EMU are effectively regulated,the fault rate has been significantly reduced and continued to be stable.The fault rate of the advanced repair is increasing gradually.After the advanced repair,there is a weak early fault period and then there is a dramatic decline.The trend analysis for the seasonal fault rate of the air-conditioning system shows that there is a significant peak of fault rate from June to August every summer and the maintenance measures should be strengthened.Example analyses show that the proposed method can be used to verify and analyze the fault rule of EMU based on the big data of operation and maintenance.
出处
《中国铁道科学》
EI
CAS
CSCD
北大核心
2018年第1期88-92,共5页
China Railway Science
基金
中国铁路总公司科技研究开发计划项目(2016J007-A
J2016J006
2017J007-B
2017F025)
关键词
动车组
故障分类
可靠性分析
统计分析
大数据
Electric multiple unit
Fault classification
Reliability analysis
Statistical analysis
Big data
