This paper proposes a novel locally linear backpropagation based contribution(LLBBC) for nonlinear process fault diagnosis. As a method based on the deep learning model of auto-encoder(AE), LLBBC can deal with the fau...This paper proposes a novel locally linear backpropagation based contribution(LLBBC) for nonlinear process fault diagnosis. As a method based on the deep learning model of auto-encoder(AE), LLBBC can deal with the fault diagnosis problem through extracting nonlinear features. When the on-line fault diagnosis task is in progress, a locally linear model is firstly built at the current fault sample. According to the basic idea of reconstruction based contribution(RBC), the propagation of fault information is described by using back-propagation(BP) algorithm. Then, a contribution index is established to measure the correlation between the variable and the fault, and the final diagnosis result is obtained by searching variables with large contributions. The smearing effect, which is an important factor affecting the performance of fault diagnosis, can be suppressed as well,and the theoretical analysis reveals that the correct diagnosis can be guaranteed by LLBBC. Finally, the feasibility and effectiveness of the proposed method are verified through a nonlinear numerical example and the Tennessee Eastman benchmark process.展开更多
Understanding the characteristics of O_(3)precursor contributions over multiple years is crucial for designing effective O_(3)control strategies over the Pearl River Delta(PRD)region of China.In this study,a deep lear...Understanding the characteristics of O_(3)precursor contributions over multiple years is crucial for designing effective O_(3)control strategies over the Pearl River Delta(PRD)region of China.In this study,a deep learning-based response surface model(DeepRSM)was developed and applied over the PRD(DeepRSM-PRD)to identify and quantify the main features of O_(3)regimes and regional contributions in the core PRD over multiple years(2019–2021).The Out-of-Sample(OOS)validation results indicated that DeepRSM-PRD effectively predicted the nonlinear response of O_(3)to emission controls,maintaining validity across non-training periods.Our study revealed that O_(3)generation was sensitive to volatile organic compounds(VOC)in the core PRD in 2019,with nitrogen oxides(NO_(x))-limited regimes emerging in most major cities in 2020 and 2021.Further investigation into source contributions showed that in our model domain,O_(3)formation in central cities of the PRD was primarily driven by local contributions and was susceptible to influence from nearby cities.With small emission reductions,VOC contributions predominantly drive O_(3)production in Guangzhou and Shenzhen.However,NO_(x)emissions were identified as the primary contributors in all central city receptors when anthropogenic emissions were removed,sharing 59.5%–69.3%in 2019,64.4%–72.3%in 2020,and 62.75%–73.2%in 2021.Our results highlight the need for a high focus on NO_(x)emissions control in the core PRD.In addition,for Guangzhou and Shenzhen,VOC reduction also plays a crucial role in the initial stages of modest emission reductions.展开更多
The Tibetan Plateau(TP)is a prevalent region for convection systems due to its unique thermodynamic forcing.This study investigated isolated deep convections(IDCs),which have a smaller spatial and temporal size than m...The Tibetan Plateau(TP)is a prevalent region for convection systems due to its unique thermodynamic forcing.This study investigated isolated deep convections(IDCs),which have a smaller spatial and temporal size than mesoscale convective systems(MCSs),over the TP in the rainy season(June-September)during 2001–2020.The authors used satellite precipitation and brightness temperature observations from the Global Precipitation Measurement mission.Results show that IDCs mainly concentrate over the southern TP.The IDC number per rainy season decreases from around 140 over the southern TP to around 10 over the northern TP,with an average 54.2.The initiation time of IDCs exhibits an obvious diurnal cycle,with the peak at 1400–1500 LST and the valley at 0900–1000 LST.Most IDCs last less than five hours and more than half appear for only one hour.IDCs generally have a cold cloud area of 7422.9 km^(2),containing a precipitation area of approximately 65%.The larger the IDC,the larger the fraction of intense precipitation it contains.IDCs contribute approximately 20%–30%to total precipitation and approximately 30%–40%to extreme precipitation over the TP,with a larger percentage in July and August than in June and September.In terms of spatial distribution,IDCs contribute more to both total precipitation and extreme precipitation over the TP compared to the surrounding plain regions.IDCs over the TP account for a larger fraction than MCSs,indicating the important role of IDCs over the region.展开更多
Phosphorescent and thermally activated delayed fluorescence(TADF)emitters can break through the spin statistics rules and achieve great success in external quantum efficiency(over 5%).However,maintaining high efficien...Phosphorescent and thermally activated delayed fluorescence(TADF)emitters can break through the spin statistics rules and achieve great success in external quantum efficiency(over 5%).However,maintaining high efficiency at high brightness is a tremendous challenge for applications of organic light emitting diodes.Hence,we reported two phenanthroimidazole derivatives PPI-An-CN and PPI-An-TP and achieved extremely low efficiency roll-off with about 99%of the maximum external quantum efficiency(EQEmax)maintained even at a high luminance of 1000 cd/cm2 based non-doped devices.When doping the two materials in CBP(4,4'-bis(N-carbazolyl)-1,1'-biphenyl),the doped devices still exhibited excellent stability at high brightness with CIEy≈0.07 and low turn-on voltage of only 2.8 V.The state-ofthe-art low efficiency roll-off makes the new materials attractive for potential applications.It is the first time that the Fragment Contribution Analysis method has been used to analyze the excited state properties of the molecules in the field of OLEDs,which helps us understand the mechanism more intuitively and deeply.展开更多
基金supported by the Key Project of National Natural Science Foundation of China(61933013)Ningbo 13th Five-year Marine Economic Innovation and Development Demonstration Project(NBH Y-2017-Z1)。
文摘This paper proposes a novel locally linear backpropagation based contribution(LLBBC) for nonlinear process fault diagnosis. As a method based on the deep learning model of auto-encoder(AE), LLBBC can deal with the fault diagnosis problem through extracting nonlinear features. When the on-line fault diagnosis task is in progress, a locally linear model is firstly built at the current fault sample. According to the basic idea of reconstruction based contribution(RBC), the propagation of fault information is described by using back-propagation(BP) algorithm. Then, a contribution index is established to measure the correlation between the variable and the fault, and the final diagnosis result is obtained by searching variables with large contributions. The smearing effect, which is an important factor affecting the performance of fault diagnosis, can be suppressed as well,and the theoretical analysis reveals that the correct diagnosis can be guaranteed by LLBBC. Finally, the feasibility and effectiveness of the proposed method are verified through a nonlinear numerical example and the Tennessee Eastman benchmark process.
基金supported by the National Key R&D Program of China(Nos.2023YFC3708505,2023YFC3708503,and 2023YFE0121300)the High-End Foreign Expert Recruitment Program,China(No.G2023163014L)。
文摘Understanding the characteristics of O_(3)precursor contributions over multiple years is crucial for designing effective O_(3)control strategies over the Pearl River Delta(PRD)region of China.In this study,a deep learning-based response surface model(DeepRSM)was developed and applied over the PRD(DeepRSM-PRD)to identify and quantify the main features of O_(3)regimes and regional contributions in the core PRD over multiple years(2019–2021).The Out-of-Sample(OOS)validation results indicated that DeepRSM-PRD effectively predicted the nonlinear response of O_(3)to emission controls,maintaining validity across non-training periods.Our study revealed that O_(3)generation was sensitive to volatile organic compounds(VOC)in the core PRD in 2019,with nitrogen oxides(NO_(x))-limited regimes emerging in most major cities in 2020 and 2021.Further investigation into source contributions showed that in our model domain,O_(3)formation in central cities of the PRD was primarily driven by local contributions and was susceptible to influence from nearby cities.With small emission reductions,VOC contributions predominantly drive O_(3)production in Guangzhou and Shenzhen.However,NO_(x)emissions were identified as the primary contributors in all central city receptors when anthropogenic emissions were removed,sharing 59.5%–69.3%in 2019,64.4%–72.3%in 2020,and 62.75%–73.2%in 2021.Our results highlight the need for a high focus on NO_(x)emissions control in the core PRD.In addition,for Guangzhou and Shenzhen,VOC reduction also plays a crucial role in the initial stages of modest emission reductions.
基金supported by the National Natural Science Foundation of China[grant number 42105064]the Second Tibetan Plateau Scientific Expedition and Research(STEP)program[grant number 2019QZKK0102]the special fund of the Yunnan University“double first-class”construction.
文摘The Tibetan Plateau(TP)is a prevalent region for convection systems due to its unique thermodynamic forcing.This study investigated isolated deep convections(IDCs),which have a smaller spatial and temporal size than mesoscale convective systems(MCSs),over the TP in the rainy season(June-September)during 2001–2020.The authors used satellite precipitation and brightness temperature observations from the Global Precipitation Measurement mission.Results show that IDCs mainly concentrate over the southern TP.The IDC number per rainy season decreases from around 140 over the southern TP to around 10 over the northern TP,with an average 54.2.The initiation time of IDCs exhibits an obvious diurnal cycle,with the peak at 1400–1500 LST and the valley at 0900–1000 LST.Most IDCs last less than five hours and more than half appear for only one hour.IDCs generally have a cold cloud area of 7422.9 km^(2),containing a precipitation area of approximately 65%.The larger the IDC,the larger the fraction of intense precipitation it contains.IDCs contribute approximately 20%–30%to total precipitation and approximately 30%–40%to extreme precipitation over the TP,with a larger percentage in July and August than in June and September.In terms of spatial distribution,IDCs contribute more to both total precipitation and extreme precipitation over the TP compared to the surrounding plain regions.IDCs over the TP account for a larger fraction than MCSs,indicating the important role of IDCs over the region.
基金supported by the National Natural Science Foundation of China(No.51673113)the Key Project of DEGP(No.2018KZDXM032)
文摘Phosphorescent and thermally activated delayed fluorescence(TADF)emitters can break through the spin statistics rules and achieve great success in external quantum efficiency(over 5%).However,maintaining high efficiency at high brightness is a tremendous challenge for applications of organic light emitting diodes.Hence,we reported two phenanthroimidazole derivatives PPI-An-CN and PPI-An-TP and achieved extremely low efficiency roll-off with about 99%of the maximum external quantum efficiency(EQEmax)maintained even at a high luminance of 1000 cd/cm2 based non-doped devices.When doping the two materials in CBP(4,4'-bis(N-carbazolyl)-1,1'-biphenyl),the doped devices still exhibited excellent stability at high brightness with CIEy≈0.07 and low turn-on voltage of only 2.8 V.The state-ofthe-art low efficiency roll-off makes the new materials attractive for potential applications.It is the first time that the Fragment Contribution Analysis method has been used to analyze the excited state properties of the molecules in the field of OLEDs,which helps us understand the mechanism more intuitively and deeply.
