A5029549421- Machine Fault Diagnosis Techniques
- Multilevel Inverters and Converters
- Gear and Bearing Dynamics Analysis
- Silicon Carbide Semiconductor Technologies
- Engineering Diagnostics and Reliability
- Advanced Computational Techniques and Applications
- Geochemistry and Geologic Mapping
- Mineral Processing and Grinding
- Power Systems and Renewable Energy
- High-pressure geophysics and materials
- Remote Sensing and Land Use
- earthquake and tectonic studies
- Rough Sets and Fuzzy Logic
- Machine Learning in Bioinformatics
- Geological and Geochemical Analysis
- Solar Radiation and Photovoltaics
- Advanced Algorithms and Applications
- Power Systems Fault Detection
- Integrated Energy Systems Optimization
- Geoscience and Mining Technology
- Energy Load and Power Forecasting
- Power Transformer Diagnostics and Insulation
Xi'an Shiyou University
2022-2023
Chinese Academy of Geological Sciences
2018
Shanghai Maritime University
2014-2015
Multilevel inverters, for their distinctive performance, have been widely used in high voltage and high-power applications recent years. As power electronics equipment reliability is very important to ensure multilevel inverter systems stable operation, it detect locate faults as quickly possible. In this context improve fault diagnosis accuracy efficiency of a cascaded H-bridge system (CHMLIS), strategy based on the principle component analysis multiclass relevance vector machine...
Abstract The traditional empirical wavelet transform (EWT) based on the Meyer and scale-space method can decompose a signal into several modes. However, this is not effective in dealing with strong noise non-stationary signals, which may lead to modal mixing or even too many invalid components. For purpose, combination of enhanced (EEWT) correlation kurtosis (CK) proposed paper. Firstly, EEWT used segment spectrum characteristics fluctuations. It uses minimum points envelope as boundaries...
Research Article| August 15, 2018 Passive crustal clockwise rotational deformation of the Sichuan Basin since Miocene and its relationship with tectonic evolution fault systems on eastern edge Tibetan Plateau Yabo Tong; Tong † 1Institute Geomechanics, Chinese Academy Geological Sciences, Beijing 100081, China2Key Laboratory Paleomagnetism Tectonic Reconstruction, Ministry Land Resources, China †tyb816@163.com Search for other works by this author on: GSW Google Scholar Yujun Sun; Sun...
In order to improve the accuracy of fault diagnosis and accelerate operation speed in a cascaded H-bridge multilevel inverter system (CHMLIS), strategy based on Relative Principle Component Analysis-Support Vector Machine (RPCA-SVM) is presented this paper. strategy, output voltage CHMLIS, which preprocessed through fast Fourier transform (FFT), used identify type location occurring SVM model. Then RPCA utilized reduce input sample's dimension. A lower dimensional sample will time necessary...
Abstract It is crucial to understand the rolling bearing fault diagnosis procedure since bearings are frequently used in rotating machinery and if a failure occurs, it will interfere with proper operation of entire piece or equipment. Deep learning increasingly being mechanical diagnosis, convolutional neural networks(CNN) most common type. In recent years, rapid growth artificial intelligence has caused methods evolve as well. A CNN diagnostic approach based on seagull optimization...
The multi-level inverter system is becoming a very promising candidate to replace the conventional two-level inverter, but reliability remains an open issue. most common problem that power switch transistors have open-circuit or short-circuit faults during operation. In order improve accuracy of fault diagnosis and accelerate operation speed in cascaded H-bridge multilevel system, novel strategy based on principle component analysis multiclass relevance vector machine (PCA-mRVM) presented...
Nowadays, cooling load is mainly attributable to upgrade of a new high power grid load. An accurate calculation and prediction can better meet demands at peak hours in summer. Based on the historical summer temperature data Sichuan province, characteristics are examined firstly. Next, random nonlinear relations studied. Finally, BP neural network model optimized by genetic algorithm (GA) employed achieve province. Results suggest that closely connected with air-conditioner ownership, GA...