| 基于改进安全域的轴箱轴承状态监测 |
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| 引用本文： | 赵聪聪,白杨,刘玉梅,赵颖慧,施继红. 基于改进安全域的轴箱轴承状态监测[J]. 西南交通大学学报, 2020, 55(4): 889-895. DOI: 10.3969/j.issn.0258-2724.20180584 |
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| 作者姓名： | 赵聪聪 白杨 刘玉梅 赵颖慧 施继红 |
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| 作者单位： | 1. 吉林农业大学工程技术学院;2. 一汽-大众汽车有限公司;3. 吉林大学交通学院;4. 一汽研发总院智能网联开发院 |
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| 基金项目： | 国家自然科学基金资助项目（51575232）；吉林省科技厅重点科技攻关项目（20160204018GX）；吉林省科技厅自然科学基（20180101056JC） |
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| 摘 要： | 为了提高高速列车轴箱轴承的运行可靠性,将安全域理论引入到轴承的状态监测,并将传统安全域估计转化为确定安全域的边界值来避免复杂模型参数的影响;利用归一化内禀模态分量的能量距构建轴承运行的状态特征向量,根据关联函数建立轴承安全域边界值估计模型,采用粒子群优化算法进行寻优求解;基于求解结果,结合关联函数定量分析轴承的运行状态,利用轴承全寿命疲劳试验进行验证,并将该方法应用于轴箱轴承的状态监测.研究结果表明:全寿命试验的轴承运行状态的检出率和分类正确率分别为0.951和0.939;高速列车轴箱轴承运行状态的分类正确率为0.935,轴承运行正常,与其实际状态相一致.
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| 关 键 词： | 高速列车 轴箱轴承 安全域边界值 关联函数 状态监测 |
| 收稿时间： | 2017-11-30 |
Condition Monitoring of Axle Box Bearing Based on Improved Safety Region |
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| ZHAO Congcong,BAI Yang,LIU Yumei,ZHAO Yinghui,SHI Jihong. Condition Monitoring of Axle Box Bearing Based on Improved Safety Region[J]. Journal of Southwest Jiaotong University, 2020, 55(4): 889-895. DOI: 10.3969/j.issn.0258-2724.20180584 |
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| Authors: | ZHAO Congcong BAI Yang LIU Yumei ZHAO Yinghui SHI Jihong |
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| Abstract: | To improve the operating reliability of the axle box bearing of high-speed trains, the safety region theory was introduced into condition monitoring of the axle box bearing. The traditional assessment of the safety region was transformed into determining the boundary values, aiming to avoid the influence of complex model parameters on the evaluation process of the safety region. The normalized energies of intrinsic mode functions were used to construct the eigenvector of bearing operating state, and the correlation function was used to establish the evaluation model of the safety region boundary values, where the particle swarm optimization algorithm was adopted to get optimal solution. On the basis of estimation results of boundary values, correlation function was utilized to assess the operating state of bearing quantitatively. The effectiveness was verified by the fatigue test of rolling bearing, and the method was used for condition monitoring of the axle box bearing. The results show that the detection rate and classification rate of bearing operating state of fatigue test are 0.951 and 0.939, respectively; the classification rate of operating state of the axle box bearing is 0.935, indicating that the axle box bearing is running normally, which is consistent with its actual operating state. |
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