Results 11 to 20 of about 31,094 (285)

Compound Fault Diagnosis of Wind Turbine Gearbox via Modified Signal Quality Coefficient and Versatile Residual Shrinkage Network [PDF]

Sensors
Wind turbine gearbox fault diagnosis is critical to guarantee working efficiency and operational safety. However, the current diagnostic methods face enormous restrictions in handling nonlinear noise signals and intricate compound fault patterns. Herein,
Weixiong Jiang, Guanhui Zhao, Zhan Gao, Yuanhang Wang, Jun Wu   +4 more
doaj   +2 more sources

Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis [PDF]

IEEE Access, 2019
Intelligent compound fault diagnosis of rotating machinery plays a crucial role for the security, high-efficiency, and reliability of modern manufacture machines, but identifying and decoupling the compound fault are still a great challenge.
Ruyi Huang, Yixiao Liao, Shaohui Zhang, Weihua Li   +3 more
doaj   +2 more sources

Multiple Enhanced Sparse Representation via IACMDSR Model for Bearing Compound Fault Diagnosis. [PDF]

Sensors (Basel), 2022
For the sake of addressing the issue of extracting multiple features embedded in a noise-heavy vibration signal for bearing compound fault diagnosis, a novel model based on improved adaptive chirp mode decomposition (IACMD) and sparse representation, namely IACMDSR, is developed in this paper.
Zhang L, Zhao L, Wang C, Xiao Q, Liu H, Zhang H, Hu Y.   +6 more
europepmc   +4 more sources

Application of Deep Neural Network in Gearbox Compound Fault Diagnosis

Energies, 2023
Gearbox fault diagnosis is vital to ensure the efficient operation of rotating machinery, and most gearbox faults in industrial production occur in the form of compound faults. To realize the diagnosis of compound faults in gearboxes at different speeds,
Xiangfeng Zhang, Qinghong Xu, Hong Jiang, Jun Li   +3 more
doaj   +2 more sources

Compound Fault Diagnosis of Planetary Gearbox Based on Improved LTSS-BoW Model and Capsule Network [PDF]

Sensors
The identification of compound fault components of a planetary gearbox is especially important for keeping the mechanical equipment working safely. However, the recognition performance of existing deep learning-based methods is limited by insufficient ...
Guoyan Li, Liyu He, Yulin Ren, Xiong Li, Jingbin Zhang, Runjun Liu   +5 more
doaj   +2 more sources

Compound Fault Diagnosis of Rolling Bearing Based on Singular Negentropy Difference Spectrum and Integrated Fast Spectral Correlation [PDF]

Entropy, 2020
Compound fault diagnosis is challenging due to the complexity, diversity and non-stationary characteristics of mechanical complex faults. In this paper, a novel compound fault separation method based on singular negentropy difference spectrum (SNDS) and ...
Guiji Tang, Tian Tian
doaj   +2 more sources

Compound Fault Characteristic Analysis for Fault Diagnosis of a Planetary Gear Train

Sensors
The carrier eccentricity error and gear compound faults are most likely to occur simultaneously in an actual planetary gear train (PGT). Various faults and errors are coupled with each other to generate a complex dynamic response, which makes the ...
Yulin Ren, Guoyan Li, Xiong Li, Jingbin Zhang, Runjun Liu, Sifan Shi   +5 more
doaj   +3 more sources

Diagnosis of Compound Fault Using Sparsity Promoted-Based Sparse Component Analysis [PDF]

Sensors, 2017
Compound faults often occur in rotating machinery, which increases the difficulty of fault diagnosis. In this case, blind source separation, which usually includes independent component analysis (ICA) and sparse component analysis (SCA), was proposed to ...
Yansong Hao, Liuyang Song, Yanliang Ke, Huaqing Wang, Peng Chen   +4 more
doaj   +3 more sources

An Improved Fault Diagnosis Method and Its Application in Compound Fault Diagnosis for Paper Delivery Structure Coupling

Shock and Vibration
The coupling torque signal contains essential information about the operating condition of the motor-follower mechanical system. Artificial Intelligence methods have been effective in diagnosing coupling faults.
Fu Liu, Haopeng Chen, Yan Wang
doaj   +2 more sources

Compound Fault Diagnosis of Rolling Bearing Based on ALIF-KELM [PDF]

Mathematical Problems in Engineering, 2021
Aiming at the shortcomings of difficult classification of rolling bearing compound faults and low recognition accuracy, a composite fault diagnosis method of rolling bearing combined with ALIF and KELM is proposed. First, the basic concepts of ALIF and KELM are introduced, and then ALIF is used to decompose the sample data of vibration signals of ...
Jie Ma, Shitong Liang, Zhengyu Du, Ming Chen   +3 more
openaire   +1 more source