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An Open-switch Fault Diagnosis Method for Single-phase PWM Rectifier Based on CEEMD-DNN
Based on complementary ensemble empirical mode decomposition and deep neural network (CEEMD-DNN), a novel diagnosis method is proposed to discover...
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Damage detection of bridge structures under moving loads based on CEEMD and PSD sensitivity analysis
This study proposes a new damage identification method based on a combination of complete ensemble empirical mode decomposition (CEEMD) and power...
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Source Number Enumeration Approach Based on CEEMD
Empirical mode decomposition (EMD) can be used to decompose complex signals into a limited number of intrinsic mode functions (IMFs), and each...
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A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highways
Many highways are acquiring smart transportation systems to improve traffic efficiency, safety and management. Intelligent transportation systems can...
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A CEEMD-ARIMA-SVM model with structural breaks to forecast the crude oil prices linked with extreme events
This paper develops an integrated framework to forecast the volatility of crude oil prices by considering the impacts of extreme events (structural...
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Rolling Bearing Fault Diagnosis Method with Adaptive CEEMD and Cyclic Spectrum Coherence
Rolling bearings are the key components of rail trains, and ensuring their normal operation is very important to the safety of trains. Aiming at the...
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A Hybrid Daily Carbon Emission Prediction Model Combining CEEMD, WD and LSTM
In order to improve the short-term prediction accuracy of carbon emissions, a new hybrid daily carbon emission prediction model is proposed in this...
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Open Circuit Fault Diagnosis of NPC Inverter Based on CEEMD and LSTM
The most important thing in my thesis is to put forward a strategy to diagnose the open circuit fault of IGBT in the neutral point clamped (NPC)...
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Dynamic monitoring and data analysis of a long-span arch bridge based on high-rate GNSS-RTK measurement combining CF-CEEMD method
The purpose of this article is to develop a combined data analysis method of Chebyshev filter (CF) and complementary ensemble empirical mode...
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A precise feature extraction method for shock wave signal with improved CEEMD-HHT
Efficient extraction of feature parameters is the key to evaluating weapon damage performance. At present, many classical feature extraction...
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Compensation Capacitor Status Monitoring Research Based on Feature Fusion and SVM
In order to meet the needs of railway electrical departments for “state repair” of track circuit compensation capacitors and timely and effective...
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Feature extraction based on vibration signal decomposition for fault diagnosis of rolling bearings
Rolling bearings typically operate under time-varying conditions, which present challenges for fault diagnosis due to the presence of modulation...
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Multi-step Ahead Wind Speed Forecasting Based on a Bi-LSTM Network Combined with Decomposition Technique
Wind energy is considered as one of the most attractive renewable energies and has the fastest development in power fields. It gradually becomes an...
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CEEMD-assisted kernel support vector machines for bearing diagnosis
The successful assessment of the health condition in rolling element bearings hinges on the early fault detection of fault of bearing elements. Early...
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A Stock Price Forecasting Model Integrating Complementary Ensemble Empirical Mode Decomposition and Independent Component Analysis
In recent years, due to the non-stationary behavior of data samples, modeling and forecasting the stock price has been challenging for the business...
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Hilbert-Huang Transform in Pavement Texture and Skid-Resistance Study
Insufficient skid-resistance of a pavement is a critical cause of traffic accidents. Pavement texture plays an important role in the skid...
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CEEMD-assisted bearing degradation assessment using tight clustering
Rolling element bearing is a critical component of various rotating machineries. As the demand of reliability of machinery gradually increases, the...
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Fault Diagnosis of Rolling Bearing Based on an Improved Denoising Technique Using Complete Ensemble Empirical Mode Decomposition and Adaptive Thresholding Method
PurposeThe vibration signals captured for rolling bearing are generally polluted by excessive noise and can lose the fault information at the early...
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Signal Denoising Algorithm of Massage Chair Movement Based on iForest-EEMD
Aiming at the problem of massage chair movement signal detection, a signal denoising algorithm based on iForest-EEMD is proposed. Wavelet threshold...
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Systematic Review on Fault Diagnosis on Rolling-Element Bearing
PurposeTo maintain machinery operations smoothly, Rolling-Element Bearings (REBs) are utilized so that the entire equipment’s safety is ensured....
