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学者姓名：崔玲丽
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摘要 ：
本发明公开了一种基于自适应模型粒子滤波算法的滚动轴承剩余使用寿命预测方法，该方法基于滚动轴承性能退化的演变规律，将退化过程划分为健康、退化和失效三个阶段。引入Box‑Cox变换及3σ原则，准确地确定了轴承开始退化的时刻及失效阈值，实现了健康状态的自主识别；针对单一预测模型难以准确跟踪轴承退化状态的难点，提出自适应模型匹配策略选择最优滤波模型的方法，实现了退化状态的动态追踪；创新性地提出了基于已有数据的全局/局部信息融合方法预测轴承寿命，避免了单次预测的偶然性，从而获得了剩余使用寿命概率密度函数的最佳估计。
引用：
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| GB/T 7714 | 崔玲丽 , 李文杰 , 王华庆 et al. 一种基于自适应模型粒子滤波算法的轴承寿命预测方法 : CN202211067564.8[P]. | 2022-09-01 . |
| MLA | 崔玲丽 et al. "一种基于自适应模型粒子滤波算法的轴承寿命预测方法" : CN202211067564.8. | 2022-09-01 . |
| APA | 崔玲丽 , 李文杰 , 王华庆 , 乔文生 . 一种基于自适应模型粒子滤波算法的轴承寿命预测方法 : CN202211067564.8. | 2022-09-01 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
本发明公开了一种基于数字孪生字典的自适应稀疏图学习轴承寿命预测方法，该方法建立了扩展指数模型及线性分段模型，生成涵盖多种退化行为的数字孪生字典，设计了新的图学习优化目标函数，引入稀疏正则化方法降低模型复杂度及参数敏感度，自适应获取数据的精确拓扑结构，基于构建的数字孪生字典及自适应稀疏图学习实现了剩余使用寿命的准确预测。
引用：
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| GB/T 7714 | 崔玲丽 , 王鑫 . 一种基于数字孪生字典的自适应稀疏图学习轴承寿命预测方法 : CN202210174135.4[P]. | 2022-02-24 . |
| MLA | 崔玲丽 et al. "一种基于数字孪生字典的自适应稀疏图学习轴承寿命预测方法" : CN202210174135.4. | 2022-02-24 . |
| APA | 崔玲丽 , 王鑫 . 一种基于数字孪生字典的自适应稀疏图学习轴承寿命预测方法 : CN202210174135.4. | 2022-02-24 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
本发明公开了一种基于时变卡尔曼滤波的滚动轴承剩余使用寿命预测方法，该方法可自动匹配滚动轴承不同退化阶段特点，分别建立基于一次线性函数和二次非线性函数的时变卡尔曼滤波器模型，以时移窗滤波相对误差指标因子自适应的判断轴承退化状态，自动切换卡尔曼滤波器处理不同阶段的监测数据，实现轴承剩余使用寿命的有效预测。
引用：
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| GB/T 7714 | 崔玲丽 , 王鑫 , 王华庆 et al. 一种基于时变卡尔曼滤波的滚动轴承剩余使用寿命预测方法 : CN202210173117.4[P]. | 2022-02-24 . |
| MLA | 崔玲丽 et al. "一种基于时变卡尔曼滤波的滚动轴承剩余使用寿命预测方法" : CN202210173117.4. | 2022-02-24 . |
| APA | 崔玲丽 , 王鑫 , 王华庆 , 乔文生 . 一种基于时变卡尔曼滤波的滚动轴承剩余使用寿命预测方法 : CN202210173117.4. | 2022-02-24 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
本发明公开了一种基于自适应奇异值分解的轴承微弱故障特征提取方法，首先针对正弦信号、复合正弦信号和周期性冲击信号各自SV的演变趋势，结合奇异值子对SVP的形成原理，分别提出最佳嵌入维数优化选取原则，明确了该参数的量化范围，进而根据信号自身特点，确定奇异值分解(SVD)的最佳嵌入维数。该方法可自适应匹配SVD的最佳嵌入维数，进而获得形成SVP分布的信号分解策略。随后，结合谐波干扰的能量及SVP分布，实现对包含轴承微弱故障成分的子信号进行定位。最后，采用反对角线平均法重构目标子信号，对其进行包络谱分析获得诊断结果。新方法能自适应匹配SVD的最佳嵌入维数，能有效实现滚动轴承微弱故障特征提取。
引用：
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| GB/T 7714 | 崔玲丽 , 刘银行 , 王鑫 . 一种基于自适应奇异值分解的滚动轴承微弱故障特征提取方法 : CN202210052833.7[P]. | 2022-01-18 . |
| MLA | 崔玲丽 et al. "一种基于自适应奇异值分解的滚动轴承微弱故障特征提取方法" : CN202210052833.7. | 2022-01-18 . |
| APA | 崔玲丽 , 刘银行 , 王鑫 . 一种基于自适应奇异值分解的滚动轴承微弱故障特征提取方法 : CN202210052833.7. | 2022-01-18 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究
关键词 ：
自适应分解 自适应分解 阶次分析 阶次分析 变分模态分解 变分模态分解 变转速齿轮箱 变转速齿轮箱
引用：
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| GB/T 7714 | 冯刚 , 刘桐桐 , 崔玲丽 et al. 基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究 [J]. | 冯刚 , 2021 , 45 (1) : 34-39,84 . |
| MLA | 冯刚 et al. "基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究" . | 冯刚 45 . 1 (2021) : 34-39,84 . |
| APA | 冯刚 , 刘桐桐 , 崔玲丽 , 机械传动 . 基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究 . | 冯刚 , 2021 , 45 (1) , 34-39,84 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Accurate modeling of the vibration signal model of planetary gearboxes is essential for the subsequent fault diagnosis. According to the existing improved phenomenological model based on the meshing vibration, this paper conducts further investigations on the vibration mechanism of the gearbox. The time delay phenomenon of faulty ring gear tooth participating in meshing is theoretically analyzed, and the assisted phases for experimental verification are proposed and deduced. Based on the improved model, the vibration signal under the fault condition is simulated and compared with the results of traditional methods. Subsequently, the paper proposes to divide and reconstruct this signal and use the maximum correlation kurtosis deconvolution (MCKD) to enhance its impact characteristics. The results show that the phase between the fault impact and its adjacent meshing impact is consistent with the proposed assisted phase. Finally, the correctness of the vibration mechanism and the improved phenomenological model are verified experimentally.
关键词 ：
Gear fault Gear fault MCKD MCKD Phenomenological model Phenomenological model Planetary gearbox Planetary gearbox Vibration mechanism Vibration mechanism
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| GB/T 7714 | Luo, Yingchao , Cui, Lingli , Zhang, Jianyu et al. Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault [J]. | JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY , 2021 , 35 (5) : 1867-1879 . |
| MLA | Luo, Yingchao et al. "Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault" . | JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 35 . 5 (2021) : 1867-1879 . |
| APA | Luo, Yingchao , Cui, Lingli , Zhang, Jianyu , Ma, Jianfeng . Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault . | JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY , 2021 , 35 (5) , 1867-1879 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
变转速齿轮箱由于工况复杂导致转频不稳定,齿轮箱的微弱故障信号可能会被掩盖在强噪声中,不能直接应用传统的时频分析方法,为故障特征的提取增加一定的难度。针对变转速信号的处理,传统的计算阶次分析方式(COT)很好地解决了变转速齿轮箱的故障特征难以提取出来的问题,但由于传统COT中所使用的重采样方法是基于样条插值法的,无法根据转频选取转频,导致重采样间隔并不均匀;提出了改进的阶次分析方法,根据采样的各点角速度依次进行重采样,提高了阶次分析的精度。同时,变转速齿轮箱因动力传递复杂,导致变转速齿轮箱噪声更加严重。变分模态分解(VMD)常被被用来去除复杂信号噪声,提取被掩盖在强噪声中的微弱故障信号。提出了自...
关键词 ：
变分模态分解 变分模态分解 变转速齿轮箱 变转速齿轮箱 自适应分解 自适应分解 阶次分析 阶次分析
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | 冯刚 , 刘桐桐 , 崔玲丽 . 基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究 [J]. | 机械传动 , 2021 , 45 (01) : 34-39,84 . |
| MLA | 冯刚 et al. "基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究" . | 机械传动 45 . 01 (2021) : 34-39,84 . |
| APA | 冯刚 , 刘桐桐 , 崔玲丽 . 基于改进阶次分析与自适应VMD的变转速齿轮箱故障诊断研究 . | 机械传动 , 2021 , 45 (01) , 34-39,84 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Accurately, apace and intelligently identifying the diverse faults of rotating machines is of great significance. However, high diagnostic accuracy is usually accompanied by lower model efficiency. To address this, a light intelligent diagnosis model based on improved Online Dictionary Learning (ODL) sample-making and simplified Convolutional Neural Network (CNN) is proposed. Within the sampling time, ODL based on Orthogonal Matching Pursuit (OMP) is used to select time-domain multi-channel signals to make RGB samples, which results in samples with smaller size and stronger features. Benefiting from the high-quality samples, the CNN model is simplified, only small-scale one-dimensional convolution kernels that undertake different tasks and global average pooling (GAP) layer are used, which greatly improve diagnostic efficiency of the network while ensuring diagnostic accuracy. Three different fault diagnosis cases of rotating machine suggest that the proposed model has high diagnostic accuracy along with high efficiency.
关键词 ：
Convolutional neural network Convolutional neural network Light intelligent diagnosis model Light intelligent diagnosis model Online dictionary learning Online dictionary learning Rotating machine Rotating machine Sample making Sample making
引用：
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| GB/T 7714 | Wang, Pengxin , Song, Liuyang , Hao, Yansong et al. A light intelligent diagnosis model based on improved Online Dictionary Learning sample-making and simplified convolutional neural network [J]. | MEASUREMENT , 2021 , 183 . |
| MLA | Wang, Pengxin et al. "A light intelligent diagnosis model based on improved Online Dictionary Learning sample-making and simplified convolutional neural network" . | MEASUREMENT 183 (2021) . |
| APA | Wang, Pengxin , Song, Liuyang , Hao, Yansong , Wang, Huaqing , Li, Shi , Cui, Lingli . A light intelligent diagnosis model based on improved Online Dictionary Learning sample-making and simplified convolutional neural network . | MEASUREMENT , 2021 , 183 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In the fault diagnosis of bearings, the high flexibility of the asymmetric Gaussian chirplet model enables the adapted dictionary-free orthogonal matching pursuit to manifest good performance. Since this method does not rely on predetermined dictionaries, it has potential advantages as well, especially for the impulses caused by compound faults that are multiple type's combination. Benefiting from the sparse representation architecture, the fault isolation can be skillfully converted into a 0-1 programming problem for elements selection in sparse vector, which may become one of the breakthroughs in solving compound faults’ isolation. Consequently, this paper attempts to give a solution using signal processing. Specifically, the maximum entropy deconvolution adjusted technique is used for preprocessing, which includes noise reduction and impulsiveness enhancement. Notch filter and spectral subtraction is utilized for impulses screening and extraction, and spectrum is employed for fault diagnosis. Simulation analysis and experimental tests verify the proposed method, whose results illustrated the potentiality to response the compound fault isolation and diagnosis. © 2021
关键词 ：
Failure analysis Failure analysis Fault detection Fault detection Notch filters Notch filters Signal processing Signal processing
引用：
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| GB/T 7714 | Cui, Lingli , Sun, Yin , Zhang, Jianyu et al. Adapted dictionary-free orthogonal matching pursuit and 0-1 programming to solve the isolation and diagnosis of bearing and gear compound faults [J]. | Measurement: Journal of the International Measurement Confederation , 2021 , 178 . |
| MLA | Cui, Lingli et al. "Adapted dictionary-free orthogonal matching pursuit and 0-1 programming to solve the isolation and diagnosis of bearing and gear compound faults" . | Measurement: Journal of the International Measurement Confederation 178 (2021) . |
| APA | Cui, Lingli , Sun, Yin , Zhang, Jianyu , Wang, Huaqing . Adapted dictionary-free orthogonal matching pursuit and 0-1 programming to solve the isolation and diagnosis of bearing and gear compound faults . | Measurement: Journal of the International Measurement Confederation , 2021 , 178 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Compound faults diagnosis of bearings and gears in gearboxes is a full-challenging task. The rational usage of meshing resonance is probable to be one of the breakthroughs to solve this problem. However, the existing detection method of meshing resonance is sensitive to noise and has risks of false demodulation. Meanwhile, it is difficult to guarantee that isolated components only contain one fault characteristic. Based on the mentioned problems, a spectrum of full-band preprocessing and 2-D separation method is raised. First, the inverted editing method of the original signal is proposed to reduce noise in the full frequency band. Second, the established resonance detection diagram and the introduced amplitude-level decomposition technique separate the processing results in the frequency and amplitude dimensions. Finally, the separate components are detected, respectively, by envelope analysis. Both the simulation analysis and experimental verification do support the effectiveness of this method. In addition, this article compares the existing method and solves the essential problems as well. © 1963-2012 IEEE.
关键词 ：
Separation Separation Fault detection Fault detection Resonance Resonance
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| GB/T 7714 | Cui, Lingli , Sun, Yin , Wang, Xin et al. Spectrum-Based, Full-Band Preprocessing, and Two-Dimensional Separation of Bearing and Gear Compound Faults Diagnosis [J]. | IEEE Transactions on Instrumentation and Measurement , 2021 , 70 . |
| MLA | Cui, Lingli et al. "Spectrum-Based, Full-Band Preprocessing, and Two-Dimensional Separation of Bearing and Gear Compound Faults Diagnosis" . | IEEE Transactions on Instrumentation and Measurement 70 (2021) . |
| APA | Cui, Lingli , Sun, Yin , Wang, Xin , Wang, Huaqing . Spectrum-Based, Full-Band Preprocessing, and Two-Dimensional Separation of Bearing and Gear Compound Faults Diagnosis . | IEEE Transactions on Instrumentation and Measurement , 2021 , 70 . |
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