Results 21 to 30 of about 296,188 (298)

Application of a flat variational modal decomposition algorithm in fault diagnosis of rolling bearings

Journal of Low Frequency Noise, Vibration and Active Control, 2020
Fault diagnosis of rolling bearings can effectively prevent sudden accidents and is an important factor for the safe operation of mechanical systems.
Haodong Li, Ying Xu, Dong An, Lixiu Zhang, Songhua Li, Huaitao Shi   +5 more
doaj   +1 more source

Adaptive Complex Variational Mode Decomposition for Micro-Motion Signal Processing Applications

Sensors, 2021
In order to suppress the strong clutter component and separate the effective fretting component from narrow-band radar echo, a method based on complex variational mode decomposition (CVMD) is proposed in this paper.
Saiqiang Xia, Jun Yang, Wanyong Cai, Chaowei Zhang, Liangfa Hua, Zibo Zhou   +5 more
doaj   +1 more source

Autonomous fault detection and diagnosis for permanent magnet synchronous motors using combined variational mode decomposition, the Hilbert-Huang transform, and a convolutional neural network

Computers & electrical engineering, 2023
The continuous and online monitoring of the condition of electrical machines is key to their safe operation. This study introduces a novel fault detection and diagnosis technique for continuous monitoring of faults in permanent magnet synchronous motors (
Ma’d El-Dalahmeh, M. Al‐Greer, Imran Bashir, M. El‐Dalahmeh, A. Demi̇rel, O. Keysan   +5 more
semanticscholar   +1 more source

Fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator

工程科学学报, 2016
Aiming at the characteristics of rolling bearing fault vibration signals and considering the merits of variational mode decomposition in mono-component separation and calculus enhanced energy operator in transient impulse detection, this article ...
ZHANG Dong, FENG Zhi-peng
doaj   +1 more source

Air gap eccentric analysis and fault detection of traction motor

Journal of Engineering and Applied Science, 2023
To solve the problem of air gap eccentric fault of traction motor, the fault characteristic frequency is close to the fundamental frequency, and the decomposed frequency affects each other, which is easy to cause spectrum aliasing.
Jintian Yin, Zhilong He, Li Liu, Zhihua Peng   +3 more
doaj   +1 more source

Streamflow prediction using a hybrid methodology based on variational mode decomposition (VMD) and machine learning approaches

Applied Water Science, 2023
The optimal management of water resources depends on accurate and reliable streamflow prediction. Therefore, researchers have become interested in the development of hybrid approaches in recent years to enhance the performance of modeling techniques for ...
F. Ahmadi, Mansour Tohidi, Meysam Sadrianzade   +2 more
semanticscholar   +1 more source

Enhanced Discrimination of Seismic Geological Channels Based on Multi-Trace Variational Mode Decomposition

Applied Sciences, 2022
The spectral decomposition is a valuable tool for improving the resolution of seismic interpretation, and thus can improve the accuracy of the subtle geo-features (thin and narrow channels, thin reservoirs, etc.).
Jiaxuan Leng, Zhichao Yu, Chaodong Wu
doaj   +1 more source

Deep Prediction Model Based on Dual Decomposition with Entropy and Frequency Statistics for Nonstationary Time Series

Entropy, 2022
The prediction of time series is of great significance for rational planning and risk prevention. However, time series data in various natural and artificial systems are nonstationary and complex, which makes them difficult to predict.
Zhigang Shi, Yuting Bai, Xuebo Jin, Xiaoyi Wang, Tingli Su, Jianlei Kong   +5 more
doaj   +1 more source

Denoising method of machine tool vibration signal based on variational mode decomposition and Whale-Tabu optimization algorithm

Scientific Reports, 2023
The noise from other sources is inevitably mixed in the vibration information of CNC machine tools obtained using the sensors. In this work, a de-noising method based on joint analysis is proposed.
Chengzhi Fang, Yushen Chen, Xiaolei Deng, Xiaoliang Lin, Yue Han, Junjian Zheng   +5 more
semanticscholar   +1 more source

A Novel Intelligent Fault Diagnosis Method Based on Variational Mode Decomposition and Ensemble Deep Belief Network

IEEE Access, 2020
The deep belief network is widely used in fault diagnosis and health management of rotating machinery. However, on the one hand, deep belief networks only tend to focus on the global information of bearing vibration, ignoring local information.
Chao Zhang, Yibin Zhang, Chenxi Hu, Zhenbao Liu, Liye Cheng, Yong Zhou   +5 more
doaj   +1 more source