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基于性能退化和材料损伤表征的高铁齿轮箱体故障诊断
引用本文:艾轶博,孙畅,张卫冬.基于性能退化和材料损伤表征的高铁齿轮箱体故障诊断[J].控制与决策,2018,33(7):1264-1270.
作者姓名:艾轶博  孙畅  张卫冬
作者单位:北京科技大学国家材料服役安全科学中心,北京100083,北京科技大学国家材料服役安全科学中心,北京100083,北京科技大学国家材料服役安全科学中心,北京100083
基金项目:国家自然科学基金项目(61273205).
摘    要:高铁齿轮箱体的服役环境恶劣,疲劳和拉伸损伤同时存在,服役周期长,缺少故障损伤数据.为此,针对高铁齿轮箱体的服役特点和安全性需求,采用基于性能退化方法,利用声发射技术对箱体损伤过程进行监测,并提出一种利用Adaboost调整样本分布的方法建立退化模型来表征箱体损伤状态.通过对箱体损伤过程的声发射信号进行分析,实现箱体的有效故障诊断,将箱体拉伸损伤故障诊断的绝对误差控制在30s以内,疲劳损伤故障诊断的相对误差基本控制在1.1{%

关 键 词:故障诊断  Adaboost算法  样本分布  性能退化  材料表征  高铁齿轮箱

Fault diagnosis of high speed gear-box shell based on performance degradation and material damage characterization
AI Yi-bo,SUN Chang and ZHANG Wei-dong.Fault diagnosis of high speed gear-box shell based on performance degradation and material damage characterization[J].Control and Decision,2018,33(7):1264-1270.
Authors:AI Yi-bo  SUN Chang and ZHANG Wei-dong
Affiliation:National Center for Materials Service Safety,University of Science and Technology Beijing,Beijing100083,China,National Center for Materials Service Safety,University of Science and Technology Beijing,Beijing100083,China and National Center for Materials Service Safety,University of Science and Technology Beijing,Beijing100083,China
Abstract:The service environment of the high speed gear-box shell is bad, fatigue and tensile damage exist at the same time, the service cycle is long, and the fault damage data is insufficient. Therefore, according to the service characteristics and safety requirements of the high speed gear-box shell, based on the performance degradation method, the acoustic emission technique is used to monitor the damage process of the gear-box shell. A method using the Adaboost algorithm to adjust the distribution of samples is proposed to establish the degradation model, which can characterize the damage state of the gear-box shell. By analyzing the acoustic emission signal of the damage process, the effective fault diagnosis of the box is realized. The absolute error of the tensile damage diagnosis of the shell is less than 30s, and the relative error of fatigue damage diagnosis is less than 1.1{%
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