Fault detection is beneficial for chiller routine operation management in building automation systems.Considering the limitations of traditional principal component analysis(PCA)algorithm for chiller fault detection,a...Fault detection is beneficial for chiller routine operation management in building automation systems.Considering the limitations of traditional principal component analysis(PCA)algorithm for chiller fault detection,a so-called kernel entropy component analysis(KECA)method has been developed and the development results are reported in this paper.Unlike traditional PCA,in KECA,the feature extraction or dimensionality reduction is implemented in a new space,called kernel feature space.The new space is nonlinearly related to the input space.The data set in the kernel feature space is projected onto a principal component subspace constructed by the feature space principal axes determined by the maximum Rényi entropy rather than the top eigenvalues.The proposed KECA is more suitable to deal with nonlinear process without Gaussian assumption.Using the available experimental data from ASHRAE RP-1043,seven typical chiller faults were tested by the proposed KECA method,and the results were compared to that of PCA.Two statistics,i.e.T2 and squared prediction error(SPE),were employed for fault detection monitoring.The fault detection results showed that the proposed KECA method had a better performance in terms of a higher detection accuracy in comparison to the traditional PCA.For the seven typical faults,the fault detection ratios were over 55%,even at their corresponding least severity level when using the proposed KECA based chiller fault detection method.展开更多
Droplet phase change is important for energy storage and saving technology.The initial profile of the droplet is extremely important for its vaporization or solidification on a horizontal surface.To understand the eff...Droplet phase change is important for energy storage and saving technology.The initial profile of the droplet is extremely important for its vaporization or solidification on a horizontal surface.To understand the effect of liquid physical properties on droplet profile,a theoretical model was developed in this study,based on the Young-Laplace equation with gravity effect specially considered.After the model was experimentally validated by comparing the geometric shape of water droplets,it was further used for predicting droplet shapes of other materials,and thus analyzing the influence of different physical properties,such as temperature,pressure,surface wettability,etc.Results show that the results of this model agree well with the experimental data.The maximum and average deviations are less than 4.5%and 1.5%,respectively.For all kinds of droplets on the fixed surfaces,when the temperature increases,the droplet contact radius increases and height decreases.The droplets of nitro-gen and carbon dioxide are more sensitive to temperature than ethanol and ethylene glycol droplets.For 20𝜇L droplets on the surface of contact angle 150°,when the temperature changes from 273.15 K to 293.15 K,the droplet contact radiuses increase by 30.6%for carbon dioxide,1.2%for ethanol and 0.67%for ethylene glycol,and the droplet heights decrease by 42.9%,2.5%,1.1%,respectively.Results of this study are meaningful for predicting the phase change process of droplets on the horizontal surface by controlling their initial profiles.展开更多
基金The financial supports for the Natural Science Foundation of Zhejiang Province(Project No.LQ19E060007)are gratefully acknowledged.
文摘Fault detection is beneficial for chiller routine operation management in building automation systems.Considering the limitations of traditional principal component analysis(PCA)algorithm for chiller fault detection,a so-called kernel entropy component analysis(KECA)method has been developed and the development results are reported in this paper.Unlike traditional PCA,in KECA,the feature extraction or dimensionality reduction is implemented in a new space,called kernel feature space.The new space is nonlinearly related to the input space.The data set in the kernel feature space is projected onto a principal component subspace constructed by the feature space principal axes determined by the maximum Rényi entropy rather than the top eigenvalues.The proposed KECA is more suitable to deal with nonlinear process without Gaussian assumption.Using the available experimental data from ASHRAE RP-1043,seven typical chiller faults were tested by the proposed KECA method,and the results were compared to that of PCA.Two statistics,i.e.T2 and squared prediction error(SPE),were employed for fault detection monitoring.The fault detection results showed that the proposed KECA method had a better performance in terms of a higher detection accuracy in comparison to the traditional PCA.For the seven typical faults,the fault detection ratios were over 55%,even at their corresponding least severity level when using the proposed KECA based chiller fault detection method.
基金the National Nature Science Foundation of China(No.52076013)Discovery Early Career Researcher Award(DECRA)2020+2 种基金Australian Re-search Council(ARC)Australia(No.DE200101747)the CAS Key Laboratory of Cryogenics,TIPC,China(No.CRYO202001).
文摘Droplet phase change is important for energy storage and saving technology.The initial profile of the droplet is extremely important for its vaporization or solidification on a horizontal surface.To understand the effect of liquid physical properties on droplet profile,a theoretical model was developed in this study,based on the Young-Laplace equation with gravity effect specially considered.After the model was experimentally validated by comparing the geometric shape of water droplets,it was further used for predicting droplet shapes of other materials,and thus analyzing the influence of different physical properties,such as temperature,pressure,surface wettability,etc.Results show that the results of this model agree well with the experimental data.The maximum and average deviations are less than 4.5%and 1.5%,respectively.For all kinds of droplets on the fixed surfaces,when the temperature increases,the droplet contact radius increases and height decreases.The droplets of nitro-gen and carbon dioxide are more sensitive to temperature than ethanol and ethylene glycol droplets.For 20𝜇L droplets on the surface of contact angle 150°,when the temperature changes from 273.15 K to 293.15 K,the droplet contact radiuses increase by 30.6%for carbon dioxide,1.2%for ethanol and 0.67%for ethylene glycol,and the droplet heights decrease by 42.9%,2.5%,1.1%,respectively.Results of this study are meaningful for predicting the phase change process of droplets on the horizontal surface by controlling their initial profiles.
