Results 1 to 10 of about 4,609 (240)

Feature Extraction of Ship-Radiated Noise Based on Permutation Entropy of the Intrinsic Mode Function with the Highest Energy

Entropy, 2016
In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship-radiated noise is presented based on empirical mode decomposition theory and permutation ...
Yu-Xing Li, Ya-An Li, Zhe Chen, Xiao Chen   +3 more
doaj   +2 more sources

Fault Diagnosis for Rotating Machinery Using Multiscale Permutation Entropy and Convolutional Neural Networks

Entropy, 2020
In view of the limitations of existing rotating machine fault diagnosis methods in single-scale signal analysis, a fault diagnosis method based on multi-scale permutation entropy (MPE) and multi-channel fusion convolutional neural networks (MCFCNN) is ...
Hongmei Li, Jinying Huang, Xiwang Yang, Jia Luo, Lidong Zhang, Yu Pang   +5 more
doaj   +2 more sources

A comparative study of four types of multi-scale entropies in feature extraction of underwater acoustic signals for potential GNSS positioning applications

Frontiers in Physics, 2022
The combination of underwater acoustic processing and the Global Navigation Satellite System (GNSS) has achieved remarkable economic benefits in offshore operations.
Danning Zhao, Danning Zhao, Danning Zhao, Yu Lei, Jinsong Xu, Hongbing Cai   +5 more
doaj   +1 more source

Recognition study of denatured biological tissues based on multi-scale rescaled range permutation entropy

Mathematical Biosciences and Engineering, 2022
<abstract> <p>The recognition of denatured biological tissue is an indispensable part in the process of high intensity focused ultrasound treatment. As a nonlinear method, multi-scale permutation entropy (MPE) is widely used in the recognition of denatured biological tissue.
Bei Liu, Wenbin Tan, Xian Zhang, Ziqi Peng, Jing Cao   +4 more
openaire   +3 more sources

Fault Diagnosis Method Based on AUPLMD and RTSMWPE for a Reciprocating Compressor Valve

Entropy, 2022
In order to effectively extract the key feature information hidden in the original vibration signal, this paper proposes a fault feature extraction method combining adaptive uniform phase local mean decomposition (AUPLMD) and refined time-shift ...
Meiping Song, Jindong Wang, Haiyang Zhao, Xulei Wang   +3 more
doaj   +1 more source

Multi-scale permutation Lempel-Ziv complexity and its application in feature extraction for Ship-radiated noise

Frontiers in Marine Science, 2022
Permutation Lempel-Ziv complexity (PLZC) is a recently proposed method for analyzing signal complexity. However, PLZC only characterizes the signal complexity from single scale and has certain limitations.
Yingmin Yi, Yingmin Yi, Yuxing Li, Yuxing Li, Junxian Wu   +4 more
doaj   +1 more source

GA-PE-VMD and MSE Methods for Milling Chatter Feature Extraction of Thin-walled Parts

Journal of Harbin University of Science and Technology, 2023
In the high-speed milling of aviation parts, due to the low stiffness of thin-walled structure, it is easy to produce chatter. Chatter leads to poor surface quality, dimensional error and reducing the service life of tools and machines.Therefore, a ...
WANG Hanbin, LI Maoyue, LIU Xianli, WANG Zhixue, MENG Boyang   +4 more
doaj   +1 more source

Variation Characteristics and Complexity Measurement of Urban Precipitation Based on Multi-scale Permutation Entropy

Journal of Physics: Conference Series, 2020
Abstract In order to better judge the complexity of precipitation, this paper took some major cities of Heilongjiang Province as the research object, and used the Mann-Kendall test and multi-scale permutation entropy theory to study the complexity of precipitation.
Dong Liu, Tingqi Yan, Sicheng Liu, Ge Yan   +3 more
openaire   +1 more source

A Fault Feature Extraction Method for Rolling Bearings Based on Refined Composite Multi-Scale Amplitude-Aware Permutation Entropy [PDF]

IEEE Access, 2021
Aiming at the problems of unclear early fault characteristics and difficult extraction of rolling bearings, a new nonlinear dynamic analysis method called refined composite multi-scale amplitude-aware permutation entropy (RCMAAPE) is introduced in this paper.
Youshuo Song, Weiyu Wang
openaire   +2 more sources

Multi-Scale Analysis Based Ball Bearing Defect Diagnostics Using Mahalanobis Distance and Support Vector Machine

Entropy, 2013
The objective of this research is to investigate the feasibility of utilizing the multi-scale analysis and support vector machine (SVM) classification scheme to diagnose the bearing faults in rotating machinery.
Chun-Chieh Wang, Tian-Yau Wu, Chiu-Wen Wu, Shuen-De Wu   +3 more
doaj   +1 more source