Fuzheng Liu
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View article: Power Transformer Fault Diagnosis Method Based on SMOTE and Convolution Soft Threshold Network
Power Transformer Fault Diagnosis Method Based on SMOTE and Convolution Soft Threshold Network Open
Power transformers play an important role in the entire power grid. However, the fault diagnosis method based on machine learning suffers from decreased diagnostic performance when faced with redundant information interference and unbalanc…
View article: Fault diagnosis of power transformers based on dissolved gas analysis and improved LightGBM hybrid integrated model with dual‐branch structure
Fault diagnosis of power transformers based on dissolved gas analysis and improved LightGBM hybrid integrated model with dual‐branch structure Open
Aiming at the fault diagnosis problems of imbalanced data and insufficient mapping of characteristic information in fault samples collected by transformers at present, which lead to low accuracy and large diagnostic deviation in actual app…
View article: Fault Diagnosis Method of Rolling Bearing Based on ESGMD-CC and AFSA-ELM
Fault Diagnosis Method of Rolling Bearing Based on ESGMD-CC and AFSA-ELM Open
Incomplete fault signal characteristics and ease of noise contamination are issues with the current rolling bearing early fault diagnostic methods, making it challenging to ensure the fault diagnosis accuracy and reliability. A novel appro…
View article: Accuracy‐Improved Fault Diagnosis Method for Rolling Bearing Based on Enhanced ESGMD‐CC and BA‐ELM Model
Accuracy‐Improved Fault Diagnosis Method for Rolling Bearing Based on Enhanced ESGMD‐CC and BA‐ELM Model Open
The current methods for early fault diagnosis of rolling bearing have some flaws, such as poor fault feature information and insufficient fault feature extraction capability, which makes it challenging to guarantee fault diagnosis accuracy…
View article: Short-Term Load Forecasting Based on PSO-KFCM Daily Load Curve Clustering and CNN-LSTM Model
Short-Term Load Forecasting Based on PSO-KFCM Daily Load Curve Clustering and CNN-LSTM Model Open
Short-term load forecasting (STLF) with excellent precision and prominent efficiency plays a significant role in the stable operation of power grid and the improvement of economic benefits. In this paper, a novel model based on data mining…
View article: A Fault Diagnosis Solution of Rolling Bearing Based on MEEMD and QPSO-LSSVM
A Fault Diagnosis Solution of Rolling Bearing Based on MEEMD and QPSO-LSSVM Open
The vibration signals of rolling bearing are often non-stationary and non-linear, and consequently it is much more difficult to extract the deep characteristics in the time domain. In this paper, a new fault diagnosis method is proposed to…
View article: The Feature Extraction and Diagnosis of Rolling Bearing Based on CEEMD and LDWPSO-PNN
The Feature Extraction and Diagnosis of Rolling Bearing Based on CEEMD and LDWPSO-PNN Open
The vibration signals of rolling bearing are often highly nonstationary and nonlinear, and consequently it is not accurate to extract and identify the characteristics of these signals by the traditional methods. In order to improve the per…