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首页> 《中国测试》期刊 >本期导读>高速列车齿轮箱轴承故障诊断的自适应TQWT方法

高速列车齿轮箱轴承故障诊断的自适应TQWT方法

46    2019-11-28

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作者:龙莹1, 苏燕辰1, 高扬2, 李艳萍1, 何刘1

作者单位:1. 西南交通大学机械工程学院, 四川 成都 610031;
2. 中车戚墅堰机车车辆工艺研究所有限公司, 江苏 常州 213011


关键词:信号分析;故障诊断;可调品质因子小波变换;谱峭度;滚动轴承


摘要:

齿轮箱轴承是高速列车传动系统中重要的零部件之一,其故障诊断对保障列车运行安全具有重要意义。轴承故障诊断主要依靠其故障特征的提取,因此提出基于改进谱峭度(improved spectral kurtosis,ISK)的自适应可调品质因子小波变换(TQWT)故障特征的提取方法。首先在谱峭度基础上引入包络谱熵,提出既能度量信号脉冲强度又能表征其周期性的ISK指标。文章提出的方法利用ISK在TQWT的品质因子Q与冗余因子r的取值范围内自动选取最佳Qr参数,将信号分解成若干信号分量,并通过选取冲击特征丰富的分量信号进行合并、包络解调提取故障特征。仿真信号验证方法的可行性与有效性,将该方法运用于齿轮箱轴承故障诊断中,结果表明:该方法能挖掘原始信号中不易被发现的信息,使包络谱中故障特征丰富,能有效地诊断轴承故障。


Fault diagnosis of gearbox bearings of high-speed train applying adaptive TQWT
LONG Ying1, SU Yanchen1, GAO Yang2, LI Yanping1, HE Liu1
1. College of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China;
2. CRRC Qishuyan Institute Co., Ltd., Changzhou 213011, China
Abstract: Bearing of gearbox is one of the most important parts in the transmission system of high-speed train. Its fault diagnosis is of great significance for ensuring the safety of train operation. Bearing fault diagnosis mainly depends on the extraction of fault features. Therefore, an adaptive Tunable Q-factor wavelet transform (TQWT) fault feature extraction method based on improved spectral kurtosis index (ISK) is proposed. First, the envelope spectrum entropy is introduced on the basis of kurtosis, and the IK index which can measure both the pulse intensity and the periodicity of the signal is presented. The method proposed in this paper automatically optimizes the optimum Q and r parameters in the range of quality factor Q and redundancy factor r of TQWT, and obtains the signal components by processing the signals according to the parameters. It selects the signal components with rich impact characteristics to merge, and extracts the fault features from the envelope spectrum of the merged signal. The simulation signal validates the validity and feasibility of the algorithm. then the algorithm is applied to the in fault diagnosis of bearing of gearbox, the results show that this method can excavate the information that is not easy to be found in the original signal, and makes the fault feature of the envelope spectrum rich and can effectively diagnose the bearing fault.
Keywords: signal analysis;fault diagnosis;TQWT;spectrum kurtosis;rolling bearing
2019, 45(11):108-113  收稿日期: 2018-09-06;收到修改稿日期: 2018-10-18
基金项目: 国家自然科学基金项目(51305358)
作者简介: 龙莹(1993-),女,贵州锦屏县人,硕士研究生,专业方向为信号分析与故障诊断
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