THE EEMD-RA-KU METHOD ON DIAGNOSIS OF BEARING FAULT by WU GuangHe, DING JianMing, LIN JianHui, ZHAO QiuYuan

“…Secondly,The IMFs were selected to reconstruct signals based on relative analysis（ RA） and kurtosis（ KU）. …”
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APPLICATION OF GWO-SVM IN WIND TURBINE GEARBOX FAULT DIAGNOSIS by HU Xuan, LI Chun, YE KeHua

“…Firstly,EEMD was used to decompose the vibration signal into the several intrinsic mode functions（ IMFs）. Secondly,calculated the IMFs’ fuzzy entropies in each state and constructed feature vectors. …”
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Forecasting Uranium Resource Price Prediction by Extreme Learning Machine with Empirical Mode Decomposition and Phase Space Reconstruction by Qisheng Yan, Shitong Wang, Bingqing Li

“…In the first stage, the original uranium resource price series are first decomposed into a finite number of independent intrinsic mode functions (IMFs), with different frequencies. In the second stage, the IMFs are composed into three subseries based on the fine-to-coarse reconstruction rule. …”
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Fault Feature Extraction and Diagnosis of Gearbox Based on EEMD and Deep Briefs Network by Kai Chen, Xin-Cong Zhou, Jun-Qiang Fang, Peng-fei Zheng, Jun Wang

“…The original data is decomposed into a set of intrinsic mode functions (IMFs) using EEMD, and then main IMFs were chosen for reconstructed signal to suppress abnormal interference from noise. …”
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A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network by Jingbo Gai, Yifan Hu, Junxian Shen

“…Firstly, the vibration signals of bearings in known states were decomposed by empirical mode decomposition (EMD) to obtain the intrinsic mode functions (IMFs) containing feature information. Then, the selected key IMFs which contain the main features were decomposed by singular value decomposition (SVD). …”
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ROLLING BEARING FAULT DIAGNOSIS BASED TWO TYPES OF FEATURES AND AFSA IMPROVED SVM by ZHANG LuYang, QIN Bo, ZHAO WenJun, LI Hong, ZHANG JianQiang, WANG JianGuao

“…To begin, original vibration signals are decomposed into intrinsic mode functions（IMFs） using VMD, among which the most effective fault information is selected based on the Kurtogram algorithm and the rules of maximum correlation coefficients. …”
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Bearing Fault Diagnosis based on Feature Visualization and Depth Adaptive Network by Hong Jiang, Yu Feng, Rong Fu

“…Firstly，the collected signals are analyzed by empirical mode decomposition method， and the Intrinsic mode functions（IMFs） are effectively determined by Mahalanobis distance measurement method. …”
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Internal Leakage Diagnosis of a Hydraulic Cylinder Based on Optimization DBN Using the CEEMDAN Technique by Peng Zhang, Xinyuan Chen

“…The raw AE signals are decomposed into a set of intrinsic mode functions (IMFs) by using CEEMDAN. Subsequently, according to the decreasing order of the Pearson correlation coefficient values, the first five IMFs are selected for signal reconstruction to suppress the abnormal interference from noise. …”
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Fault Diagnosis of Electromechanical Actuator Based on VMD Multifractal Detrended Fluctuation Analysis and PNN by Hongmei Liu, Jiayao Jing, Jian Ma

“…First, the vibration signals were decomposed by VMD into a number of intrinsic mode functions (IMFs). Second, the multifractal features hidden in IMFs were extracted by using MFDFA, and the generalized Hurst exponents were selected as the feature vectors. …”
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Wind speed prediction model based on multiscale temporal‐preserving embedding broad learning system by Jiayi Qiu, Yatao Shen, Ziwen Gu, Zijian Wang, Wenmei Li, Ziqian Tao, Ziwen Guo, Yaqun Jiang, Chun Huang

“…Firstly, frequency clustering‐based variational mode decomposition (FC‐VMD) is proposed to deal with the non‐stationary wind speed data into multiple intrinsic mode functions (IMFs). Then, temporal‐preserving embedding (TPE) is proposed to extract the underlying temporal manifold structure from the decomposed IMFs. …”
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An Improved Time-Frequency Analysis Method for Instantaneous Frequency Estimation of Rolling Bearing by Zengqiang Ma, Wanying Ruan, Mingyi Chen, Xiang Li

“…Firstly, the signal is decomposed into several intrinsic mode functions (IMFs) with different center frequency by VMD. Then, effective IMFs are selected by mutual information and kurtosis criteria and are reconstructed. …”
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The Behavioral Mechanism and Forecasting of Beijing Housing Prices from a Multiscale Perspective by Yan Li, Zhaoyang Xiang, Tao Xiong

“…Then, we compose the IMFs and residual into three components caused by normal market disequilibrium, extreme events, and the economic environment using the fine-to-coarse reconstruction algorithm. …”
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A structural health monitoring data reconstruction method based on VMD and SSA-optimized GRU model by Xiaoliang Jia, Guoyan Zhang, Zhiqiang Wang, Huacong Li, Jing Hu, Songlin Zhu, Caiwei Liu

“…The methodology initially employs Variational Mode Decomposition (VMD) to preprocess and decompose the existing data from the target sensor into Intrinsic Mode Functions (IMFs) and residuals. Subsequently, the Gated Recurrent Unit (GRU) network utilizes data from other sensors to reconstruct the IMFs and residuals, ultimately producing the data reconstruction results. …”
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Research on Feature Extracted Method for Flutter Test Based on EMD and CNN by Hua Zheng, Zhenglong Wu, Shiqiang Duan, Jiangtao Zhou

“…The IMFs are then reshaped to make them the suitable size to be input to the CNN. …”
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FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON EEMD-CNN by LI SiQi, JIANG ZhiJian

“…After that,choose appropriate IMFs according to the correlation coefficent and kurtosis calculating results to reconstruct the signal. …”
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Gear Fault Detection Based on Teager-Huang Transform by Hui Li, Haiqi Zheng, Liwei Tang

“…EMD can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs). TKEO can track the instantaneous amplitude and instantaneous frequency of the Intrinsic Mode Functions at any instant. …”
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Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa) by Médard Noukpo Agbazo, Gabin Koto N’Gobi, Eric Alamou, Basile Kounouhewa, Abel Afouda

“…Intrinsic Mode Functions (IMFs) are obtained according to the climatic region in which the stations are located. …”
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Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS by Zheng Xiaoxia, Jia Wenhui, Zhou Guowang, Li Jia

“…Firstly,VMD is used to decompose a fault signal into several intrinsic mode functions（ IMFs）,and introduced the permutation entropy to construct the feature vectors characterizing the modal component information. …”
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FAULT FEATURE EXTRACTION OF VIRIABLE RORATION SPEED GEARBOX GEAR BASED ON VMD AND ORDER TRACKING by DIE XuPeng, KANG JianShe, CHI Kuo

“…After obtaining the resampled signal,it would be adaptively decomposed by VMD according to the different center order,and then select the fault signal fron the IMFs（ Intrinsic Mode Function） by kurtosis criterion. …”
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Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection by Wei Liu, Kai He, Qun Gao, Cheng-yin Liu

“…Due to the nonstationary characteristics in vibration signals of the tail boom support of the longwall mining machine in this complicated environment, the empirical mode decomposition (EMD) is used to decompose the raw vibration signals into a number of intrinsic mode functions (IMFs) by which the initial feature vector matrices can be formed automatically. …”
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