A novel robust diagnostic system based on a linear fractional transform(LFT)representation combined with a static redundancy approach is proposed to design a residual generator for fault detection and localization in ...A novel robust diagnostic system based on a linear fractional transform(LFT)representation combined with a static redundancy approach is proposed to design a residual generator for fault detection and localization in a wind system using the doubly fed induction generator(DFIG).As a result,faults in DFIG-based grid-connected wind systems can be grouped into three classes of faults,namely,model uncertainty-related faults(FLMU),set point disturbance-related faults(FLDS)and parameter uncertainty-related faults(FLPU).Based on the parity-space residual generations,an artificial neural network(ANN)structure has been combined with the classification to enable the assessment of hidden,indistinguishable or small amplitude faults.The training validation with two data sizes of 1278*4 and 1278*1 respectively at the inputs and outputs of the proposed ANN,presents better performance for a mean squared error value(MSE=3.0532e 9),and a good correlation between outputs and targets for a regression value(R=1).It emerges that the proposed robust and complete diagnostic system for the optimal and sustainable integration of wind turbines into the grid,offers very great advan-tages,particularly with regard to the precise and rapid detection of faults,and the assessment of hidden faults and/or ambiguous fault states in the wind system based on DFIG.In addition,the proposed approach allows the use of a reduced number of data,sensors and actuators required.Consequently,the system maintenance difficulties,complexity and cost of the diagnostic system are reduced.展开更多
Thermoelectric devices are one of the technologies used either to generate electricity by applying a temperature difference using thermal energy or as a heating/cooling system by applying an electrical voltage.The num...Thermoelectric devices are one of the technologies used either to generate electricity by applying a temperature difference using thermal energy or as a heating/cooling system by applying an electrical voltage.The number of materials required to produce a product is an important factor in determining its price.Production costs associated with these materials,as well as their availability and quality,play a crucial role in price determination by manufacturers.In this context,a method that employs a uniform volume distribution was implemented.This approach enabled the analysis to focus on other variables,thereby promoting a more precise and relevant evaluation of overall performance.Based on the finite element method,this study investigated the influence of geometric shape,including Rect-leg,Y-leg,Pin-leg and X-leg designs,on the performance of solar thermoelectric generators and thermoelectric coolers.The study was conducted considering the same hot alumina junction surface that receives solar radiation;however,the ef-fective surface,which corresponded to the heat flow area and had a similar area near the exposed surface,varied depending on the chosen leg geometry,thus impacting the heat flux due to the variation in thermal resistance.In the case of a solar thermoelectric generator,the Rect-leg model,having the same effective surface area,presented the lowest heat loss value resulting from convection and radiation in the heat spreader and the hot alumina plate.Under the same conditions,the Y-leg showed the highest value.The Rect-leg design generated,by using thermal and optical concentration,the highest output power of 0.028 and 0.054 W,and efficiency of 3.47%and 4.7%,respectively,whereas the Y-leg generated lower values of 0.006523 and 0.018744 W for power,and 2.83%and 2.71%for efficiency,respectively.In the case of the thermoelectric coolers,the Y-leg generated the highest temperature difference between the hot and cold sides of 67.28 K at an electric current value of 1.8 A,whereas the Rect-leg,Pin-leg and X-leg generated~66.25,~67.02 and~67.19 K at 6.1,2.7 and 2.6 A.展开更多
文摘A novel robust diagnostic system based on a linear fractional transform(LFT)representation combined with a static redundancy approach is proposed to design a residual generator for fault detection and localization in a wind system using the doubly fed induction generator(DFIG).As a result,faults in DFIG-based grid-connected wind systems can be grouped into three classes of faults,namely,model uncertainty-related faults(FLMU),set point disturbance-related faults(FLDS)and parameter uncertainty-related faults(FLPU).Based on the parity-space residual generations,an artificial neural network(ANN)structure has been combined with the classification to enable the assessment of hidden,indistinguishable or small amplitude faults.The training validation with two data sizes of 1278*4 and 1278*1 respectively at the inputs and outputs of the proposed ANN,presents better performance for a mean squared error value(MSE=3.0532e 9),and a good correlation between outputs and targets for a regression value(R=1).It emerges that the proposed robust and complete diagnostic system for the optimal and sustainable integration of wind turbines into the grid,offers very great advan-tages,particularly with regard to the precise and rapid detection of faults,and the assessment of hidden faults and/or ambiguous fault states in the wind system based on DFIG.In addition,the proposed approach allows the use of a reduced number of data,sensors and actuators required.Consequently,the system maintenance difficulties,complexity and cost of the diagnostic system are reduced.
文摘Thermoelectric devices are one of the technologies used either to generate electricity by applying a temperature difference using thermal energy or as a heating/cooling system by applying an electrical voltage.The number of materials required to produce a product is an important factor in determining its price.Production costs associated with these materials,as well as their availability and quality,play a crucial role in price determination by manufacturers.In this context,a method that employs a uniform volume distribution was implemented.This approach enabled the analysis to focus on other variables,thereby promoting a more precise and relevant evaluation of overall performance.Based on the finite element method,this study investigated the influence of geometric shape,including Rect-leg,Y-leg,Pin-leg and X-leg designs,on the performance of solar thermoelectric generators and thermoelectric coolers.The study was conducted considering the same hot alumina junction surface that receives solar radiation;however,the ef-fective surface,which corresponded to the heat flow area and had a similar area near the exposed surface,varied depending on the chosen leg geometry,thus impacting the heat flux due to the variation in thermal resistance.In the case of a solar thermoelectric generator,the Rect-leg model,having the same effective surface area,presented the lowest heat loss value resulting from convection and radiation in the heat spreader and the hot alumina plate.Under the same conditions,the Y-leg showed the highest value.The Rect-leg design generated,by using thermal and optical concentration,the highest output power of 0.028 and 0.054 W,and efficiency of 3.47%and 4.7%,respectively,whereas the Y-leg generated lower values of 0.006523 and 0.018744 W for power,and 2.83%and 2.71%for efficiency,respectively.In the case of the thermoelectric coolers,the Y-leg generated the highest temperature difference between the hot and cold sides of 67.28 K at an electric current value of 1.8 A,whereas the Rect-leg,Pin-leg and X-leg generated~66.25,~67.02 and~67.19 K at 6.1,2.7 and 2.6 A.
