Results 91 to 100 of about 211 (127)
Mechanical Systems and Signal Processing, 2019 Abstract Various existed time-series decomposition methods, including wavelet transform, ensemble empirical mode decomposition (EEMD), local characteristic-scale decomposition (LCD), singular spectrum analysis (SSA), etc., have some defects for nonlinear system signal analysis.
Haiyang Pan, Yu Yang, Jinde Zheng
exaly +3 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Measurement: Journal of the International Measurement Confederation, 2021
Abstract A novel fault diagnosis procedure based on improved symplectic geometry mode decomposition (SGMD) and optimized SVM is presented. In the proposed procedure, a vibration signal is firstly decomposed by SGMD into a set of components. Then a novel constraint condition based on cosine similarity is proposed to reconstruct the decomposed ...
Xiaoyuan Zhang +2 more
exaly +2 more sources
Abstract A novel fault diagnosis procedure based on improved symplectic geometry mode decomposition (SGMD) and optimized SVM is presented. In the proposed procedure, a vibration signal is firstly decomposed by SGMD into a set of components. Then a novel constraint condition based on cosine similarity is proposed to reconstruct the decomposed ...
Xiaoyuan Zhang +2 more
exaly +2 more sources
IEEE Transactions on Instrumentation and MeasurementIn the presence of noise interference, direction of arrival (DOA) estimation becomes challenging. Particularly, when radar signals are entirely submerged in noise, the spatial information within the signals becomes obscured, thereby affecting the precision of DOA estimation.
Zhaolin Zhang +4 more
openaire +3 more sources
ISA Transactions, 2023
Strong noise interference or compound fault coupling phenomenon may lead to the failure of fault diagnosis technology. This paper focuses on weak feature extraction and compound faults detection for rotating machinery fault diagnosis and proposes adaptive symplectic geometric mode decomposition (SGMD) using cycle kurtosis entropy.
Jiawei Xiang
exaly +3 more sources
Strong noise interference or compound fault coupling phenomenon may lead to the failure of fault diagnosis technology. This paper focuses on weak feature extraction and compound faults detection for rotating machinery fault diagnosis and proposes adaptive symplectic geometric mode decomposition (SGMD) using cycle kurtosis entropy.
Jiawei Xiang
exaly +3 more sources
Measurement: Journal of the International Measurement Confederation, 2021
Abstract On line lubricating oil debris measurement is an efficient way to judge the operating status of a machine, and the inductive oil debris sensor is widely adopted. Considering the debris sensor works in a harsh environment, it is a challenge work to reduce or separate the noise via signal processing, especially for the requirements of ...
Tianhong Zhang
exaly +2 more sources
Abstract On line lubricating oil debris measurement is an efficient way to judge the operating status of a machine, and the inductive oil debris sensor is widely adopted. Considering the debris sensor works in a harsh environment, it is a challenge work to reduce or separate the noise via signal processing, especially for the requirements of ...
Tianhong Zhang
exaly +2 more sources
2021 6th Asia Conference on Power and Electrical Engineering (ACPEE), 2021 Aiming at the difficulty of real-time monitoring of winding during transformer operation and insufficient methods for evaluating the short-circuit withstand capability of winding, a real-time evaluation system for the short-circuit withstand capability of transformer winding is proposed.
Jiaxu Wang, Jian Guo
openaire +2 more sources
IEEE Transactions on Instrumentation and MeasurementInternational ...
Ge Xin +5 more
openaire +2 more sources