Since the combustion system of coal-fired boiler in thermal power plant is characterized as time varying, strongly coupled, and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportio...Since the combustion system of coal-fired boiler in thermal power plant is characterized as time varying, strongly coupled, and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportional integral derivative (PID) control scheme. For the characteristics of the main steam pressure in coal-fired power plant boiler, the sliding mode control system with Smith predictive structure is proposed to look for performance and robustness improvement. First, internal model control (IMC) and Smith predictor (SP) is used to deal with the time delay, and sliding mode controller (SMCr) is designed to overcome the model mismatch. Simulation results show the effectiveness of the proposed controller compared with conventional ones.展开更多
This paper presents the ageing mechanism of fuse in nuclear power plant in detail. Metal Electromigration is identified as the dominant ageing mechanism. On this basis, the dominant status indicators, temperature and ...This paper presents the ageing mechanism of fuse in nuclear power plant in detail. Metal Electromigration is identified as the dominant ageing mechanism. On this basis, the dominant status indicators, temperature and resistance of fuse were ensured, and current-temperature curve was proposed. The infrared thermal imaging technology was used to inspect the ageing condition and prove the current-temperature curve. Finally, the accelerated ageing testing was conducted abiding by the dominant ageing mechanism, and the lifetime was evaluated.展开更多
Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making...Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.展开更多
Based on the research on domestic and international automatic technical development in fossil power plant,the paper analyses the recent situation of the coordinate control system between turbine and boiler of domestic...Based on the research on domestic and international automatic technical development in fossil power plant,the paper analyses the recent situation of the coordinate control system between turbine and boiler of domestic fossil Power Plant,provides the development thought of coordinate control system between turbine and boiler,and describes the application prospect in control system of fossil power plant combining with the application experience.展开更多
In recent years,developing Artificial Intelligence(AI)models for complex system has become a popular research area.There have been several successful AI models for predicting the Selective Non-Catalytic Reduction(SNCR...In recent years,developing Artificial Intelligence(AI)models for complex system has become a popular research area.There have been several successful AI models for predicting the Selective Non-Catalytic Reduction(SNCR)system in power plants and large boilers.However,all these models are in essence black box models and lack of explainability,which are not able to give new knowledge.In this study,a novel explainable AI(XAI)model that combines the polynomial kernel method with Sparse Identification of Nonlinear Dynamics(SINDy)model is proposed to find the governing equation of SNCR system based on 5-year operation data from a power plant.This proposed model identifies the system’s governing equation in a simple polynomial format with polynomial order of 1 and only 1 independent variable among original 68 input variables.In addition,the explainable AI model achieves a considerable accuracy with less than 21%deviation from base-line models of partial least squares model and artificial neural network model.展开更多
基金Supported by the National Natural Science Foundation of China (61174059, 60934007, 61233004)the National Basic Research Program of China (2013CB035406)Shanghai Rising-Star Tracking Program (11QH1401300)
文摘Since the combustion system of coal-fired boiler in thermal power plant is characterized as time varying, strongly coupled, and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportional integral derivative (PID) control scheme. For the characteristics of the main steam pressure in coal-fired power plant boiler, the sliding mode control system with Smith predictive structure is proposed to look for performance and robustness improvement. First, internal model control (IMC) and Smith predictor (SP) is used to deal with the time delay, and sliding mode controller (SMCr) is designed to overcome the model mismatch. Simulation results show the effectiveness of the proposed controller compared with conventional ones.
文摘This paper presents the ageing mechanism of fuse in nuclear power plant in detail. Metal Electromigration is identified as the dominant ageing mechanism. On this basis, the dominant status indicators, temperature and resistance of fuse were ensured, and current-temperature curve was proposed. The infrared thermal imaging technology was used to inspect the ageing condition and prove the current-temperature curve. Finally, the accelerated ageing testing was conducted abiding by the dominant ageing mechanism, and the lifetime was evaluated.
基金supported by the National Natural Science Foundations of China (Nos. 51674031,51874022)。
文摘Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.
文摘Based on the research on domestic and international automatic technical development in fossil power plant,the paper analyses the recent situation of the coordinate control system between turbine and boiler of domestic fossil Power Plant,provides the development thought of coordinate control system between turbine and boiler,and describes the application prospect in control system of fossil power plant combining with the application experience.
文摘In recent years,developing Artificial Intelligence(AI)models for complex system has become a popular research area.There have been several successful AI models for predicting the Selective Non-Catalytic Reduction(SNCR)system in power plants and large boilers.However,all these models are in essence black box models and lack of explainability,which are not able to give new knowledge.In this study,a novel explainable AI(XAI)model that combines the polynomial kernel method with Sparse Identification of Nonlinear Dynamics(SINDy)model is proposed to find the governing equation of SNCR system based on 5-year operation data from a power plant.This proposed model identifies the system’s governing equation in a simple polynomial format with polynomial order of 1 and only 1 independent variable among original 68 input variables.In addition,the explainable AI model achieves a considerable accuracy with less than 21%deviation from base-line models of partial least squares model and artificial neural network model.
