Article
Engineering, Mechanical
Yanyan Nie, Fangyi Li, Liming Wang, Jianfeng Li, Mengyao Wang, Mingshuai Sun, Guoyan Li, Yanle Li
Summary: Planetary gearboxes are prone to gear local faults due to their difficult working environment, which can lead to significant losses and catastrophic events. This study proposes an improved phenomenological vibration model and calculates the relative phases between gear pairs to establish vibration models with/without local faults in order to diagnose these faults. Spectral structures and LFCFs are derived for diagnosis purposes, and simulation and experimental studies demonstrate the effectiveness of the proposed models.
MECHANISM AND MACHINE THEORY
(2022)
Article
Chemistry, Multidisciplinary
Pinyang Zhang, Changzheng Chen
Summary: This paper proposes an analysis and diagnosis two-stage framework based on time-frequency information analysis. It uses a U-net model for the semantic segmentation of vibration time-frequency spectrum and shape features to extract useful information for health state classification of planetary gearboxes.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Mechanical
Mian Zhang, Decai Li, KeSheng Wang, Qing Li, Yue Ma, Zhenzhong Liu, Tianbo Kang
Summary: An adaptive order-band energy ratio (AOER) method is proposed in this paper to quantitatively and intelligently diagnose gear faults under different operational conditions. The proposed method proves the OER to be a reliable fault indicator by analyzing the signal model. Experimental results demonstrate the effectiveness and outperformance of AOER for both stationary and non stationary operational conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Mechanical
Yi Qin, Qunwang Yao, Yi Wang, Yongfang Mao
Summary: This study proposes a parameter sharing adversarial domain adaptation network (PSADAN) to improve transfer diagnosis accuracy by constructing a shared classifier to unify fault classifiers and domain classifiers, simplifying network structure and enhancing domain confusion.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Mechanical
Yanyan Nie, Liming Wang, Fangyi Li, Jianfeng Li, Peng Cui, Jiaqi Hu, Guoyan Li, Yanle Li
Summary: This paper proposes a model-based vibration signal analysis method to interpret and understand the vibration characteristics of planetary gearboxes (PGs), providing guidance for their condition monitoring and fault diagnosis. By constructing a mathematical model of transmission path effects and a phenomenological vibration model, a comprehensive vibration signal model that accurately simulates the dynamic response of PGs is established. The vibration characteristics of the obtained signals are analyzed and validated through experiments and simulations.
MECHANISM AND MACHINE THEORY
(2022)
Article
Acoustics
Mian Zhang, Decai Li, Ming J. Zuo, Jun Liu, Hongbiao Xiang, Yang Song, Kesheng Wang
Summary: This paper discusses the modeling of vibration characteristics of planetary gearboxes, points out some issues in previous research, and proposes an improved method. By mapping the phase variation of multiple-planet gears into time-varying propagating distance, the neutralization phenomena of frequency components are solved, and a more reasonable model is proposed.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Engineering, Multidisciplinary
Hanyang Liu, Jing Lin, Jinyang Jiao, Boyao Zhang, Zongyang Liu, Xinyu Lu
Summary: Due to complex structural factors, traditional methods based on overall transmission error (OTE) are inadequate for identifying fault modes. In this work, a novel differential diagnosis (DD) framework based on encoder-measured data is proposed, which can accurately extract fault-dependent residual transmission error through filtering and singular value decomposition.
Article
Computer Science, Interdisciplinary Applications
Xinghua Huang, Guanqiu Qi, Neal Mazur, Yi Chai
Summary: In this paper, a deep residual networks-based intelligent fault diagnosis method for planetary gearboxes in cloud environments is proposed. By utilizing the super computing power of cloud computing and selecting appropriate wavelet basis functions, the proposed method achieves high diagnostic accuracy. Experimental results demonstrate the effectiveness of the proposed method.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Automation & Control Systems
Qinkai Han, Ziyuan Jiang, Yun Kong, Tianyang Wang, Fulei Chu
Summary: This study proposes a motor current model for diagnosing localized defects in planet rolling bearings (PRBs). A dynamic analysis of the motor-driven planetary gearbox system is conducted and a translational-torsional vibration model is developed. The model takes into account the time-varying impact caused by defects, as well as the influence of Hertzian contact and radial clearance on the support forces of PRBs. The model is validated through electromagnetic finite element calculations and dynamic response tests on a typical motor-driven planetary gearbox system. The results provide a theoretical basis for the quantitative diagnosis of PRB-localized defects.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Acoustics
Baoming Xu, Jiancong Shi, Min Zhong, Jun Zhang
Summary: This study proposes an adaptive parameter-induced stochastic resonance method, which combines high pass filter and Teager energy operator for signal preprocessing, and utilizes the grasshopper optimization algorithm to optimize system parameters. The method successfully extracts weak fault features from experimental vibration signals, achieving high signal-to-noise ratio and low computation cost.
Article
Acoustics
Mian Zhang, Hao Cui, Qing Li, Jie Liu, KeSheng Wang, Yongshan Wang
Summary: The article examines the diagnostic mechanisms of SER and SI in planetary gear vibration signal models, proposes the ISER indicator by selecting fewer sidebands, and validates its superior performance through experimental data. Three typical intelligent classification algorithms are employed to showcase the diagnostic abilities of these indicators.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Engineering, Electrical & Electronic
Yang Yang, Sha Wei, Tianqi Li, Hui Liu, Jun He
Summary: This article proposes a novel fault feature extraction method to extract the weak fault features of the planet bearing cage. The method utilizes the general parameterized time-frequency transform to accurately extract instantaneous rotational speed information from the planet bearing vibration signal for resampling. The fault characteristic components of the planet bearing cage can be extracted from the square envelop spectrum. The proposed method has been verified in experiments of a planetary transmission system test rig of an armored vehicle.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Mechanical
Sha Wei, Dong Wang, Zhike Peng, Zhipeng Feng
Summary: This study proposes an improved scheme called VNCD to overcome the limitations of VNCMD in fault diagnosis of planetary gearboxes under variable speed conditions. By modifying the optimization function and introducing a novel initial frequencies estimation method, VNCD shows better adaptability in practical applications and improves fault diagnosis effectiveness.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Mechanical
Lei Xu, Kang Ding, Guolin He, Yongzhuo Li, Zhuyun Chen
Summary: The study built a vibration signal model for the resonance modulation mechanism of sun gear's localized fault, identifying three groups of sidebands through simulation and experimental verification. This research provides an important frequency indicator for confirming the condition of planetary gearboxes.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Multidisciplinary
Yunhan Kim, Jong M. Ha, Kyumin Na, Jungho Park, Byeng D. Youn
Summary: In this study, a cepstrum-assisted empirical wavelet transform (CEWT) method is proposed to improve the fault diagnostic performance of planetary gearboxes through signal decomposition and processing.
