Online monitoring and diagnosis of production processes face great challenges due to the nonlinearity and multivariate of complex industrial processes.Traditional process monitoring methods employ kernel function or m...Online monitoring and diagnosis of production processes face great challenges due to the nonlinearity and multivariate of complex industrial processes.Traditional process monitoring methods employ kernel function or multilayer neural networks to solve the nonlinear mapping problem of data.However,the above methods increase the model complexity and are not interpretable,leading to difficulties in subsequent fault recognition/diagnosis/location.A process monitoring and diagnosis method based on the free energy of Gaussian-Bernoulli restricted Boltzmann machine(GBRBM-FE)was proposed.Firstly,a GBRBM network was established to make the probability distribution of the reconstructed data as close as possible to the probability distribution of the raw data.On this basis,the weights and biases in GBRBM network were used to construct F statistics,which represents the free energy of the sample.The smaller the energy of the sample is,the more normal the sample is.Therefore,F statistics can be used to monitor the production process.To diagnose fault variables,the F statistic for each sample was decomposed to obtain the Fv statistic for each variable.By analyzing the deviation degree between the corresponding variables of abnormal samples and normal samples,the cause of process abnormalities can be accurately located.The application of converter steelmaking process demonstrates that the proposed method outperforms the traditional methods,in terms of fault monitoring and diagnosis performance.展开更多
This letter studies and analyzes the working features of main circuit of tri-level boost Power Factor Correct(PFC) converter and the advantages of tri-level switch converter in aspects of bearing high-voltage of power...This letter studies and analyzes the working features of main circuit of tri-level boost Power Factor Correct(PFC) converter and the advantages of tri-level switch converter in aspects of bearing high-voltage of power components,overall system loss and magnetic component selection based upon the single-level boost PFC switch converter.Besides,relying on the application of mi-croprocessor in power converter technology and DSP(Digital Signal Processing) chip's strong cal-culating capacity,the letter presents the adoption of modified scheme of tri-level boost PFC converter under the control of predictive control algorithm.Moreover,the operating principle and control method are specified,the results of circuit test and analysis are provided and the advantages of pre-dictive control technology-based multi-level boost PFC converter is verified.展开更多
基金the financial support from the National Key R&D Program of China(Grant No.2020YFA0405700).
文摘Online monitoring and diagnosis of production processes face great challenges due to the nonlinearity and multivariate of complex industrial processes.Traditional process monitoring methods employ kernel function or multilayer neural networks to solve the nonlinear mapping problem of data.However,the above methods increase the model complexity and are not interpretable,leading to difficulties in subsequent fault recognition/diagnosis/location.A process monitoring and diagnosis method based on the free energy of Gaussian-Bernoulli restricted Boltzmann machine(GBRBM-FE)was proposed.Firstly,a GBRBM network was established to make the probability distribution of the reconstructed data as close as possible to the probability distribution of the raw data.On this basis,the weights and biases in GBRBM network were used to construct F statistics,which represents the free energy of the sample.The smaller the energy of the sample is,the more normal the sample is.Therefore,F statistics can be used to monitor the production process.To diagnose fault variables,the F statistic for each sample was decomposed to obtain the Fv statistic for each variable.By analyzing the deviation degree between the corresponding variables of abnormal samples and normal samples,the cause of process abnormalities can be accurately located.The application of converter steelmaking process demonstrates that the proposed method outperforms the traditional methods,in terms of fault monitoring and diagnosis performance.
文摘This letter studies and analyzes the working features of main circuit of tri-level boost Power Factor Correct(PFC) converter and the advantages of tri-level switch converter in aspects of bearing high-voltage of power components,overall system loss and magnetic component selection based upon the single-level boost PFC switch converter.Besides,relying on the application of mi-croprocessor in power converter technology and DSP(Digital Signal Processing) chip's strong cal-culating capacity,the letter presents the adoption of modified scheme of tri-level boost PFC converter under the control of predictive control algorithm.Moreover,the operating principle and control method are specified,the results of circuit test and analysis are provided and the advantages of pre-dictive control technology-based multi-level boost PFC converter is verified.
