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学者姓名：崔玲丽
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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
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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：
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| 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
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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
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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 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
The turn domain resampling (TDR) method is proposed in the paper on the basis of the existing angle domain resampling for solving the problem of non-fixed fault frequency under variable working conditions. TDR can select the appropriate sampling order according to the influence of frequency conversion, which avoided the error caused by the spline interpolation method. It can provide accurate parameters for the subsequent calculation of the equivalent frequency order. Variable multi-scale morphological filtering (VMSMF) method is proposed for the purpose of further reducing the interference of noise in resampling signal to feature extraction. VMSMF adaptively selects structural elements according to the parameter change of impact signal to make its scale more targeted. It only needs to calculate once using the optimal structural unit for a particular impact, and the filtering accuracy and operating efficiency have been greatly improved. The main steps of this article are as follows. First, the TDR is used to resample the original signal as to get the resampling signal which is still submerged by the strong noise. In the second step, VMSMF is used to filter the resampling signal to obtain the signal with less noise interference. Finally, the fault characteristics of the filtering signal was extracted and compared with the possible fault frequency calculated by the sampling parameters provided by resampling, so as to determine the fault type of the planetary gearbox. By analyzing the simulation signal and the experimental signal respectively, this method can find out the corresponding fault characteristics effectively.
关键词 ：
VMSMF VMSMF fault diagnosis fault diagnosis variable speed variable speed TDR TDR planetary gearbox planetary gearbox
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| GB/T 7714 | Liu, Tongtong , Cui, Lingli , Zhang, Chao . Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering [J]. | SYMMETRY-BASEL , 2021 , 13 (1) . |
| MLA | Liu, Tongtong et al. "Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering" . | SYMMETRY-BASEL 13 . 1 (2021) . |
| APA | Liu, Tongtong , Cui, Lingli , Zhang, Chao . Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering . | SYMMETRY-BASEL , 2021 , 13 (1) . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
The lumped parameter model (LPM) is a common modeling method for simulating the vibration signal of the planetary gearbox. Generally, the simulation results are not directly used for the subsequent analysis, because two factors need to be considered: the transmission paths of vibration signals and the amplitude modulation effect of the carrier. However, both of these factors are subjectively affected. In order to overcome this problem, a new method for generating the gearbox vibration signal is proposed. Based on LPM, the vibration displacement of each component is solved, and meshing forces of the internal gear pairs are calculated. Then, the ring gear with bolt constraints is simplified to the Euler-Bernoulli beam, and the vibration signal of any point on the ring gear is established by solving the vibration of the beam. Subsequently, based on the new signal model, the transmission mechanism, the amplitude modulation and the overlapping phenomenon of the vibration signal, and the effect of bolt constraint on the vibration of the gearbox are analyzed. Finally, the correctness of the new method and the effect of bolt constraint on the vibration signal are verified by experiments. © 2021
关键词 ：
Amplitude modulation Amplitude modulation Bolts Bolts Epicyclic gears Epicyclic gears Vibration analysis Vibration analysis
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| GB/T 7714 | Luo, Yingchao , Cui, Lingli , Ma, Jianfeng . Effect of bolt constraint of ring gear on the vibration response of the planetary gearbox [J]. | Mechanism and Machine Theory , 2021 , 159 . |
| MLA | Luo, Yingchao et al. "Effect of bolt constraint of ring gear on the vibration response of the planetary gearbox" . | Mechanism and Machine Theory 159 (2021) . |
| APA | Luo, Yingchao , Cui, Lingli , Ma, Jianfeng . Effect of bolt constraint of ring gear on the vibration response of the planetary gearbox . | Mechanism and Machine Theory , 2021 , 159 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Recently, the diagnosis of rotating machines based on deep learning models has achieved great success. Many of these intelligent diagnosis models are assumed that training and test data are subject to independent identical distributions (IIDs). Unfortunately, such an assumption is generally invalid in practical applications due to noise disturbances and changes in workload. To address the above problem, this article presents a high-stability diagnosis model named the multiscale feature fusion convolutional neural network (MFF-CNN). MFF-CNN does not rely on tedious data preprocessing and target domain information. It is composed of multiscale dilated convolution, self-adaptive weighting, and the new form of maxout (NFM) activation. It extracts, modulates, and fuses the input samples' multiscale features so that the model focuses more on the health state difference rather than the noise disturbance and workload difference. Two diagnostic cases, including noisy cases and variable load cases, are used to verify the effectiveness of the present model. The results show that the present model has a strong health state identification capability and anti-interference capability for variable loads and noise disturbances.
关键词 ：
Convolutional neural network (CNN) Convolutional neural network (CNN) feature fusion feature fusion feature learning feature learning intelligent diagnosis intelligent diagnosis rotating machines rotating machines
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| GB/T 7714 | Wang, Pengxin , Song, Liuyang , Guo, Xudong et al. A High-Stability Diagnosis Model Based on a Multiscale Feature Fusion Convolutional Neural Network [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2021 , 70 . |
| MLA | Wang, Pengxin et al. "A High-Stability Diagnosis Model Based on a Multiscale Feature Fusion Convolutional Neural Network" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 70 (2021) . |
| APA | Wang, Pengxin , Song, Liuyang , Guo, Xudong , Wang, Huaqing , Cui, Lingli . A High-Stability Diagnosis Model Based on a Multiscale Feature Fusion Convolutional Neural Network . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2021 , 70 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
The performance degradation assessment (PDA) of rolling element bearings is a necessary link to ensure the reliability of high-end equipment. However, traditional health indicators (HIs) are not sensitive to early defects, and there are often large local fluctuations in the later stage of degradation. Hence, this paper propose a novel PDA method to obtain HIs with early warning capability and monotone trend. Firstly, an improved graph spectrum reconstruction method is proposed to enhance the characteristics of signals. The random phase space reconstruction strategy is introduced to solve the problem of large-scale graph Laplacian matrix decomposition. Then, the spectrums of the enhanced signals are characterized, namely the high-dimensional degradation features in frequency domain are extracted and smoothed by Kalman filter. Finally, the Laplacian Eigenmaps is used to extract the intrinsic degeneration manifolds from the high-dimensional degradation features as the established HIs. Life cycle degradation data and quantitative failure data are analyzed to verify the effectiveness of the proposed method. Compared with other state-of-art methods, the results show that the HIs established by the proposed method reflect the degradation earlier and have obvious degradation trend. It effectively realizes the mapping between degradation and HI. © 2021
关键词 ：
Frequency domain analysis Frequency domain analysis Matrix algebra Matrix algebra Phase space methods Phase space methods Laplace transforms Laplace transforms Roller bearings Roller bearings Life cycle Life cycle
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| GB/T 7714 | Wang, Xin , Cui, Lingli , Wang, Huaqing et al. A generalized health indicator for performance degradation assessment of rolling element bearings based on graph spectrum reconstruction and spectrum characterization [J]. | Measurement: Journal of the International Measurement Confederation , 2021 , 176 . |
| MLA | Wang, Xin et al. "A generalized health indicator for performance degradation assessment of rolling element bearings based on graph spectrum reconstruction and spectrum characterization" . | Measurement: Journal of the International Measurement Confederation 176 (2021) . |
| APA | Wang, Xin , Cui, Lingli , Wang, Huaqing , Jiang, Hong . A generalized health indicator for performance degradation assessment of rolling element bearings based on graph spectrum reconstruction and spectrum characterization . | Measurement: Journal of the International Measurement Confederation , 2021 , 176 . |
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