This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this pap...This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this paper is on one hand the creation of a new DFIM model based on multi-model approach and, on the other hand, the synthesis of an adaptive PI multi-observer. The DFIM Volt per Hertz drive system behaves as a nonlinear complex system. It consists of a DFIM powered through a controlled PWM Voltage Source Inverter (VSI). The need of a sensorless drive requires soft sensors such as estimators or observers. In particular, an adaptive Proportional-Integral multi-observer is synthesized in order to estimate the DFIM’s outputs which are affected by different faults and to generate the different residual signals symptoms of sensor fault occurrence. The convergence of the estimation error is guaranteed by using the Lyapunov’s based theory. The proposed diagnosis approach is experimentally validated on a 1 kW Induction motor. Obtained simulation results confirm that the adaptive PI multiobserver consent to accomplish the detection, isolation and fault identification tasks with high dynamic performances.展开更多
In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （...In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （Institute of Tibetan Plateau Research, Chinese Academy of Sciences）, Qian] and four LSMs （BATS, VIC, CLM3.0 and CLM3.5）, to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over China's Mainland during 1982-2007. The results showed that various simulations of each member and their arithmetic mean （EnsAVlean） could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates （Obs_MTE）. For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs_MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens_Mean was closer to Obs_MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs_MTE and Ens_Mean exhibited a significant increasing trend during 1982-98; whereas after 1998, when the last big EI Nifio event occurred, the Ens_Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs_MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.展开更多
The Baumann Skin Typing System diagnoses patients as having one of 16 skin types based on their answers to a validated questionnaire [i] known as the Baumann Skin Type Indicator [ii]. The BSTI questionnaire has been t...The Baumann Skin Typing System diagnoses patients as having one of 16 skin types based on their answers to a validated questionnaire [i] known as the Baumann Skin Type Indicator [ii]. The BSTI questionnaire has been tested over the last decade on over 200,000 people of various ages and ethnicities in different geographic locations around the world. In this study, data were collected from 52,862 patients to compare skin type prevalence between those who presented to doctor’s offices and those who took the quiz without supervision online. The most common skin types varied only slightly between patients that took the quiz online and those that completed the questionnaire in their doctor’s office. This indicates that the prevalence of skin types seen in the doctor’s office is similar to that in the general population and that supervision is not necessary to get an accurate result on the BSTI. [iii] In addition, comparison of data gathered in China, Korea, and the US did not show a significant difference in skin type prevalence between Asian and Caucasian skin types. [iv] This study demonstrates that the English version of the BSTI is valid for English speaking patients online, and in doctors’ offices in the US, China and Korea.展开更多
Soil erosion is a complex process involving multiple natural and anthropic agents,causing the deterio-ration of multiple components comprising soil health.Here,we provide an estimate of the spatial pat-terns of cropla...Soil erosion is a complex process involving multiple natural and anthropic agents,causing the deterio-ration of multiple components comprising soil health.Here,we provide an estimate of the spatial pat-terns of cropland susceptibility to erosion by sheet and rill,gully,wind,tillage,and root crops harvesting and report the co-occurrence of these processes using a multi-model approach.In addition,to give a global overview of potential future changes,we identify the locations where these multiple concurrent soil erosion processes may be expected to intersect with projected dry/wet climate changes by 2070.Of a modelled 1.48 billion hectares(B ha)of global cropland,our results indicate that 0.56 B ha(-36%of the total area)are highly susceptible(classes 4 and 5)to a single erosion process,0.27 B ha(-18%of the total area)to two processes and 0.02 B ha(1.4%of the total area)to three or more processes.An estimated 0.82 B ha of croplands are susceptible to possible increases in water(0.68 B ha)and wind(0.14 B ha)erosion.We contend that the presented set of estimates represents a basis for enhancing our founda-tional knowledge on the geography of soil erosion at the global scale.The generated insight on multiple erosion processes can be a useful starting point for decision-makers working with ex-post and ex-ante policy evaluation of the UN Sustainable Development Goal 15(Life on Land)activities.Scientifically,this work provides the hitherto most comprehensive assessment of soil erosion risks at the global scale,based on state-of-the-art models.展开更多
文摘This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this paper is on one hand the creation of a new DFIM model based on multi-model approach and, on the other hand, the synthesis of an adaptive PI multi-observer. The DFIM Volt per Hertz drive system behaves as a nonlinear complex system. It consists of a DFIM powered through a controlled PWM Voltage Source Inverter (VSI). The need of a sensorless drive requires soft sensors such as estimators or observers. In particular, an adaptive Proportional-Integral multi-observer is synthesized in order to estimate the DFIM’s outputs which are affected by different faults and to generate the different residual signals symptoms of sensor fault occurrence. The convergence of the estimation error is guaranteed by using the Lyapunov’s based theory. The proposed diagnosis approach is experimentally validated on a 1 kW Induction motor. Obtained simulation results confirm that the adaptive PI multiobserver consent to accomplish the detection, isolation and fault identification tasks with high dynamic performances.
基金supported by the National Natural Science Foundation of China(Grant Nos.4140508391437220 and 41305066)+1 种基金the Natural Science Foundation of Hunan Province(Grant No.2015JJ3098)the Fund Project for The Education Department of Hunan Province(Grant No.14C0897)
文摘In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （Institute of Tibetan Plateau Research, Chinese Academy of Sciences）, Qian] and four LSMs （BATS, VIC, CLM3.0 and CLM3.5）, to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over China's Mainland during 1982-2007. The results showed that various simulations of each member and their arithmetic mean （EnsAVlean） could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates （Obs_MTE）. For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs_MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens_Mean was closer to Obs_MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs_MTE and Ens_Mean exhibited a significant increasing trend during 1982-98; whereas after 1998, when the last big EI Nifio event occurred, the Ens_Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs_MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.
文摘The Baumann Skin Typing System diagnoses patients as having one of 16 skin types based on their answers to a validated questionnaire [i] known as the Baumann Skin Type Indicator [ii]. The BSTI questionnaire has been tested over the last decade on over 200,000 people of various ages and ethnicities in different geographic locations around the world. In this study, data were collected from 52,862 patients to compare skin type prevalence between those who presented to doctor’s offices and those who took the quiz without supervision online. The most common skin types varied only slightly between patients that took the quiz online and those that completed the questionnaire in their doctor’s office. This indicates that the prevalence of skin types seen in the doctor’s office is similar to that in the general population and that supervision is not necessary to get an accurate result on the BSTI. [iii] In addition, comparison of data gathered in China, Korea, and the US did not show a significant difference in skin type prevalence between Asian and Caucasian skin types. [iv] This study demonstrates that the English version of the BSTI is valid for English speaking patients online, and in doctors’ offices in the US, China and Korea.
基金P.B.was funded by the Horizon Europe project AI4SoilHealth(Grant No.101086179)J.E.Y was funded by the EcoSSSoil Project,Korea Environmental Industry&Technology Institute(KEITI)(Grant No.2019002820004).
文摘Soil erosion is a complex process involving multiple natural and anthropic agents,causing the deterio-ration of multiple components comprising soil health.Here,we provide an estimate of the spatial pat-terns of cropland susceptibility to erosion by sheet and rill,gully,wind,tillage,and root crops harvesting and report the co-occurrence of these processes using a multi-model approach.In addition,to give a global overview of potential future changes,we identify the locations where these multiple concurrent soil erosion processes may be expected to intersect with projected dry/wet climate changes by 2070.Of a modelled 1.48 billion hectares(B ha)of global cropland,our results indicate that 0.56 B ha(-36%of the total area)are highly susceptible(classes 4 and 5)to a single erosion process,0.27 B ha(-18%of the total area)to two processes and 0.02 B ha(1.4%of the total area)to three or more processes.An estimated 0.82 B ha of croplands are susceptible to possible increases in water(0.68 B ha)and wind(0.14 B ha)erosion.We contend that the presented set of estimates represents a basis for enhancing our founda-tional knowledge on the geography of soil erosion at the global scale.The generated insight on multiple erosion processes can be a useful starting point for decision-makers working with ex-post and ex-ante policy evaluation of the UN Sustainable Development Goal 15(Life on Land)activities.Scientifically,this work provides the hitherto most comprehensive assessment of soil erosion risks at the global scale,based on state-of-the-art models.
