Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degrad...Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.展开更多
The goal of this study was to apply artificial neural networks to predict rain-fed wheat yield using meteorological data a few days to few months before harvesting. The climatic observation data used; were mean of dai...The goal of this study was to apply artificial neural networks to predict rain-fed wheat yield using meteorological data a few days to few months before harvesting. The climatic observation data used; were mean of daily minimum and maximum temperature, extreme of daily minimum and maximum temperature, sum of daily rainfall, number of rainy days, sum of daily sun hours, mean of daily wind speed, extreme of daily wind speed, mean of daily relative humidity, and sum of daily water requirements that were collected during 1990-1999 in Sararood Station for wheat phenological stages consisting; sowing, germination, emergence, 3rd leaves, tillering, stem formation, heading, flowering, milk maturity, wax maturity, full maturity, separately for each growing season. Then, they arranged in a matrix whose rows form each of the statistical years and the columns are meteorological factors at each phenological stage. Finally, the obtained model had the following capabilities： Prediction of wheat yield with maximum errors of 45-60 kg/ha at least two months before full maturity stage, determination of the sensitivity of each phenological stage with respect to meteorological factors, and determination of the priority order and importance of each meteorological factor effective in plant growth and crop yield.展开更多
A large portion of irrigation farmers make use of subjective （intuition） irrigation scheduling methods as supposed to objective or scientific irrigation scheduling methods, which need to be changed. The BEsproeiings...A large portion of irrigation farmers make use of subjective （intuition） irrigation scheduling methods as supposed to objective or scientific irrigation scheduling methods, which need to be changed. The BEsproeiingsWAterbestuursprogram （BEWAB＋） irrigation scheduling programme is based on the water balance equation and needs： （1） a crop production function; （2） a relative consumptive water demand curve and （3） an allowable depletion subroutine. The objective of this paper was to describe research aimed at obtaining information on （1） and （2） for pea and also to describe the effect of water application on yield and water use of pea. BEWAB＋ uses this information to estimate the daily irrigation water requirements for a particular soil-crop-atmosphere system under irrigation. A field experiment, based on published line-source irrigation methodology, was conducted on a 3 m deep loamy fine sand Bainsvlei or Ustic Quartzipsamment soil near Bloemfontein （26°08′S; 29°01′E） in South Africa. Results showed that there is a linear relationship of the form Ys = 8.07ET - 249 （r2 = 0.91）, where Ys is the seed yield of pea （kg/ha） and ET is evapotranspiration for the growing season （mm）. The relative consumptive water demand curve is represented by the following third order polynomial function that describes the relationship between time and relative ET for a pea growing season of 120 days： ETrelx = 0.09419646 - 0.01302413x ＋ 0.00059008x2 - 0.00000371x3. ETrelz denotes relative ET and x denotes time in days. A workable balance between practical problem solving and advanced irrigation science has been established with BEWAB＋. Pre-plant irrigation schedules can be made for semi-arid areas with the BEWAB＋ programme using easily obtainable inputs, like target yield, soil depth and soil particle size distribution information.展开更多
Projections of geodetic are important for all countries all over the world, where using system coordinates for solving any problems in measurements of surveying works. Russell projection is one of projections used in ...Projections of geodetic are important for all countries all over the world, where using system coordinates for solving any problems in measurements of surveying works. Russell projection is one of projections used in some countries. Direct algorithms in this projection use two methods. The first method uses partial differential equation, which is not after six orders in the series. While, the second method uses traditional series （exponential series）, which is very difficult and requires complex statistical analysis. New methodology has been applied for direct algorithms in Russell projection using general law of unlimited algorithms by simple method.展开更多
基金Projects(51475462,61374138,61370031)supported by the National Natural Science Foundation of China
文摘Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.
文摘The goal of this study was to apply artificial neural networks to predict rain-fed wheat yield using meteorological data a few days to few months before harvesting. The climatic observation data used; were mean of daily minimum and maximum temperature, extreme of daily minimum and maximum temperature, sum of daily rainfall, number of rainy days, sum of daily sun hours, mean of daily wind speed, extreme of daily wind speed, mean of daily relative humidity, and sum of daily water requirements that were collected during 1990-1999 in Sararood Station for wheat phenological stages consisting; sowing, germination, emergence, 3rd leaves, tillering, stem formation, heading, flowering, milk maturity, wax maturity, full maturity, separately for each growing season. Then, they arranged in a matrix whose rows form each of the statistical years and the columns are meteorological factors at each phenological stage. Finally, the obtained model had the following capabilities： Prediction of wheat yield with maximum errors of 45-60 kg/ha at least two months before full maturity stage, determination of the sensitivity of each phenological stage with respect to meteorological factors, and determination of the priority order and importance of each meteorological factor effective in plant growth and crop yield.
文摘A large portion of irrigation farmers make use of subjective （intuition） irrigation scheduling methods as supposed to objective or scientific irrigation scheduling methods, which need to be changed. The BEsproeiingsWAterbestuursprogram （BEWAB＋） irrigation scheduling programme is based on the water balance equation and needs： （1） a crop production function; （2） a relative consumptive water demand curve and （3） an allowable depletion subroutine. The objective of this paper was to describe research aimed at obtaining information on （1） and （2） for pea and also to describe the effect of water application on yield and water use of pea. BEWAB＋ uses this information to estimate the daily irrigation water requirements for a particular soil-crop-atmosphere system under irrigation. A field experiment, based on published line-source irrigation methodology, was conducted on a 3 m deep loamy fine sand Bainsvlei or Ustic Quartzipsamment soil near Bloemfontein （26°08′S; 29°01′E） in South Africa. Results showed that there is a linear relationship of the form Ys = 8.07ET - 249 （r2 = 0.91）, where Ys is the seed yield of pea （kg/ha） and ET is evapotranspiration for the growing season （mm）. The relative consumptive water demand curve is represented by the following third order polynomial function that describes the relationship between time and relative ET for a pea growing season of 120 days： ETrelx = 0.09419646 - 0.01302413x ＋ 0.00059008x2 - 0.00000371x3. ETrelz denotes relative ET and x denotes time in days. A workable balance between practical problem solving and advanced irrigation science has been established with BEWAB＋. Pre-plant irrigation schedules can be made for semi-arid areas with the BEWAB＋ programme using easily obtainable inputs, like target yield, soil depth and soil particle size distribution information.
文摘Projections of geodetic are important for all countries all over the world, where using system coordinates for solving any problems in measurements of surveying works. Russell projection is one of projections used in some countries. Direct algorithms in this projection use two methods. The first method uses partial differential equation, which is not after six orders in the series. While, the second method uses traditional series （exponential series）, which is very difficult and requires complex statistical analysis. New methodology has been applied for direct algorithms in Russell projection using general law of unlimited algorithms by simple method.
