Article
Engineering, Mechanical
Xinglong Wang, Jinde Zheng, Qing Ni, Haiyang Pan, Jun Zhang
Summary: This paper proposes a novel method for selecting the optimal demodulation frequency band (ODFB) of rolling bearing vibration signals, called traversal index enhanced-gram (TIEgram) method. Through traversal segmentation model and weighted fusion indicator, this method can effectively select the ODFB of rolling bearing vibration signals, leading to a more accurate diagnosis effect.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Mechanical
Hervice Romeo Fogno Fotso, Claude Vidal Aloyem Kaze, Germaine Djuidje Kenmoe
Summary: This study investigates the bearing power loss in wind turbine gearboxes under actual operating wind speed, utilizing a neural network model to analyze the data. Results indicate that the bearing power loss is highly influenced by the wind turbine operating parameters, capacity, and oil used. The proposed approach shows effectiveness in real-time operating parameters.
TRIBOLOGY INTERNATIONAL
(2021)
Article
Engineering, Multidisciplinary
Yuandong Xu, Chao Fu, Ning Hu, Baoshan Huang, Fengshou Gu, Andrew D. Ball
Summary: The article introduces a phase linearisation-based modulation signal bispectrum method that can effectively handle noise in bearing vibration signals, obtaining accurate and reliable diagnostic results.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Article
Engineering, Multidisciplinary
Tian Han, Lingjie Ding, Dandan Qi, Chao Li, Zhi Fu, Weidong Chen
Summary: A fault diagnosis method based on Teager energy operator and second-order stochastic resonance (TSSR) is proposed for wind turbine mainshaft bearing, and its superiority and effectiveness are verified through experiments.
Article
Engineering, Electrical & Electronic
Xiaolong Wang, Guiji Tang, Xiaoli Yan, Yuling He, Xiong Zhang, Chao Zhang
Summary: This study investigates the application of adaptive chirp mode decomposition (ACMD) in wind turbine bearing fault diagnosis, proposes an optimized OACMD method, and validates its superiority in detecting bearing defects through experimental signals.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Mechanical
Boyao Zhang, Yonghao Miao, Jing Lin, Yinggang Yi
Summary: The adaptive CYCBD method proposed in this article uses EHPS to accurately estimate the target cyclic frequency or period, showing robustness in fault period identification. Compared to the original CYCBD, ACYCBD can extract weak impulses without prior knowledge of the period.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Yi Qin, Xingguo Wu, Jun Luo
Summary: This article proposes a digital twin model of life-cycle rolling bearing driven by the combination of data and model. By using measured signals and the bearing fault dynamic model, the size and evolution law of bearing defects can be estimated. These information is then introduced into the bearing dynamic model in virtual space, and finally the data in virtual space is mapped to the corresponding data in physical space using an improved neural network.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Tinggui Chen, Dejie Yu
Summary: This article proposes a novel method to diagnose bearing faults using acoustic metamaterials, which enhances the resonance frequency band to extract fault features. Compared to conventional denoising techniques, this method shows superior performance in low signal to noise ratios.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Mechanical
Bingyan Chen, Weihua Zhang, James Xi Gu, Dongli Song, Yao Cheng, Zewen Zhou, Fengshou Gu, Andrew Ball
Summary: In this paper, new detection methods of cyclostationarity are developed for rolling bearing fault diagnosis by constructing generalized envelope signals and using product envelope spectrum (PES), which improve the accuracy and robustness of fault diagnosis.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Jiahao Li, Yi Liu, Jiawei Xiang
Summary: Maximum CYCBD is a blind deconvolution method used to extract faults in mechanical systems. It faces challenges of setting the cyclic frequency in advance and defining a suitable filter length. To address these issues, an optimal maximum CYCBD method is developed. It involves processing raw signals, estimating the cyclic frequency, and determining the filter length adaptively. The proposed method is validated with data from a bearing dataset and experimental test rigs.
IEEE SENSORS JOURNAL
(2023)
Review
Energy & Fuels
Jarred Kenworthy, Edward Hart, James Stirling, Adam Stock, Jonathan Keller, Yi Guo, James Brasseur, Rhys Evans
Summary: This paper examines the rating lives of wind turbine main bearings and finds that ISO 281 rating life assessment does not account for reported rates of main bearing failures. It recommends conducting similar analyses to identify the causes of main bearing failures and possibly developing a new application standard specific to this component.
Article
Engineering, Mechanical
Xiaolong Wang, Yuling He, Haipeng Wang, Aijun Hu, Xiong Zhang
Summary: The study developed a novel hybrid approach for wind turbine bearing damage identification, which showed better performance compared to other contrastive methods in terms of characteristic extraction ability and damage identification precision through analysis of experimental signals and engineering case studies.
MECHANISM AND MACHINE THEORY
(2022)
Article
Automation & Control Systems
Wei Kang, Yongsheng Zhu, Ke Yan, Zhijun Ren, Dawei Gao, Jun Hong
Summary: This paper proposes a new signal extraction method RWSVD_IFK, which can effectively extract weak repetitive transients from fault rolling element bearings using reweighted singular value decomposition and improved Fast_kurtogram, and overcome the interference of cyclostationary and abnormal shock.
Article
Green & Sustainable Science & Technology
Ravi Pandit, David Infield, Matilde Santos
Summary: Continuous assessment of wind turbine performance is crucial for maximizing power generation at a low cost. This study aims to quantify and analyze the impact of wind shear and turbulence intensity on wind turbine power curves. The results show that taking these factors into consideration can improve the accuracy and reduce the uncertainty of power curve models.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Acoustics
Manuel Bauer, Netharasan Balaratnam, Julia Weidenauer, Fabian Wagner, Markus Kley
Summary: This paper compares different fault diagnosis methods for rolling bearings, including peak envelope, root-mean-square (RMS) envelope, and Hilbert envelope. Through experiments and evaluation of measurement data, the efficiency and quality characteristics of these methods are assessed, and a decision tool is proposed to help in selecting the appropriate demodulation technique.
JOURNAL OF VIBRATION AND CONTROL
(2023)
