Moisture content is an important trait for rubber sheet trading system.Therefore,a calibrationequation for predicting moisture content was created by near infrared(NIR)technique in order todevelop a more fair trading ...Moisture content is an important trait for rubber sheet trading system.Therefore,a calibrationequation for predicting moisture content was created by near infrared(NIR)technique in order todevelop a more fair trading system in Thailand.Spectra were recorded in two systems.One wasmeasurement on each rubber sheet and the other was on a pile of sheets.Both were[measured by ahandheld NIR spectrometer in the short wavelength region(700-1100 nm)in the transflectancemode using Teflon as a diffuse refector.The spectra showed the peak at about 900 nm whichbelongs to isoprene,the major component of rubber sheet.Pretreatment with second derivativewas applied to remove baseline shift effect occurring due to thickness differences on each rubber sheet.From validation results,moisture contents predicted by single sheet system were moreaccurate than a pile of sheet system with standard error of prediction(SEP)=0.39 %and bias of-0.07%,and they were not significantly diferent from the actual values at 95%confidence.As aresult,determining moisture content in each rubber sheet by a handheld NIR,spectrometerprovided accurate values,easy and rapid operation.展开更多
Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber industries.The quality of a rubber sheet can be visually examined by holding it against clear light to in...Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber industries.The quality of a rubber sheet can be visually examined by holding it against clear light to inspect for any specks and impurities inside,but its moisture content is difficult to evaluate based on a visual inspection and this might lead to unfair trading.Herein,we developed a rapid,robust and nondestructive near-infrared spectroscopy(NIRS)-based method for moisture content determination in rubber sheets.A set of 300 rubber sheets were divided into a calibration(200 samples)and prediction groups(100 samples).The calibration set was used to develop NIRS calibration equation using different calibration models,Partial Least Square Regression(PLSR),Least Square Support Vector Machine(LS-SVM)and Articial Neural Network(ANN).Among the models investigated,the ANN model with therst derivative of spectral preprocessing presented the best prediction with a coe±cient of determination(R^(2)_(P))of 0.993,root mean square error of calibration(RMSEC)of 0.126%and root mean square error of prediction(RMSEP)of 0.179%.The results indicated that the proposed NIRS-ANN model will be able to reduce human error and provide a highly accurate estimate of the moisture content in a rubber sheet compared to traditional wet chemistry estimation methods according to AOAC standards.展开更多
This paper presents experimental performance and artificial neural network modeling of a large-scale greenhouse solar dryer for drying of natural rubber sheets. The dryer consists of a parabolic roof structure covered...This paper presents experimental performance and artificial neural network modeling of a large-scale greenhouse solar dryer for drying of natural rubber sheets. The dryer consists of a parabolic roof structure covered with polycarbonate sheets on a concrete floor. The dryer is 9.0 m in width, 27.0 m in length and 3.5 m in height. Nine 15-W DC fans powered by three 50-W PV modules were used to ventilate the dryer. To investigate its performance, the dryer was used to dry six batches of natural rubber sheets. For each batch, 750 kg of rubber sheets were dried in the dryer. Results obtained from the experiments showed that drying temperatures varied from 32 ~C to 55 ~C and the use of the dryer led to a considerable reduction of drying time, as compared to the open air sun drying. In addition, the quality of the product from the dryer was high-quality dried products. A multilayer neural network model was developed to predict the performance of this dryer. The predictive power of the model was found to be high after it was adequately trained.展开更多
The phenolic resin-chloroprene nthher was used for sandwich in manufueturing the vibra-tion damping laminated steel sheet (also calied laminated sheet), Il is a metal matrix com-posite. The tensie-shear tests have bee...The phenolic resin-chloroprene nthher was used for sandwich in manufueturing the vibra-tion damping laminated steel sheet (also calied laminated sheet), Il is a metal matrix com-posite. The tensie-shear tests have been conducted over a range of temperatures from 20C to 150C and at the strain rates from 1.67× 10 ^(5) to 1.67× 10^(-2)s^(-1). The results show that test temperature will significaiilly affect the tensile shear strength of laminated sheet. and a minimal strength and a minimal activation energy occur near 80C . The tensile-shear breaking morphology of laminated sheet varies with strain rate and test temjteralurc.展开更多
基金supported by Industrial and Research Projects for Undergraduate Students 2008(The Thailand Research Fund)and Center of Excellence Project of Research,Development Institute at Kamphaengsaen,Kasetsart University。
文摘Moisture content is an important trait for rubber sheet trading system.Therefore,a calibrationequation for predicting moisture content was created by near infrared(NIR)technique in order todevelop a more fair trading system in Thailand.Spectra were recorded in two systems.One wasmeasurement on each rubber sheet and the other was on a pile of sheets.Both were[measured by ahandheld NIR spectrometer in the short wavelength region(700-1100 nm)in the transflectancemode using Teflon as a diffuse refector.The spectra showed the peak at about 900 nm whichbelongs to isoprene,the major component of rubber sheet.Pretreatment with second derivativewas applied to remove baseline shift effect occurring due to thickness differences on each rubber sheet.From validation results,moisture contents predicted by single sheet system were moreaccurate than a pile of sheet system with standard error of prediction(SEP)=0.39 %and bias of-0.07%,and they were not significantly diferent from the actual values at 95%confidence.As aresult,determining moisture content in each rubber sheet by a handheld NIR,spectrometerprovided accurate values,easy and rapid operation.
基金supported by the Faculty of Engineering at Kamphaeng Saen,Kasetsart University,Thailand.
文摘Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber industries.The quality of a rubber sheet can be visually examined by holding it against clear light to inspect for any specks and impurities inside,but its moisture content is difficult to evaluate based on a visual inspection and this might lead to unfair trading.Herein,we developed a rapid,robust and nondestructive near-infrared spectroscopy(NIRS)-based method for moisture content determination in rubber sheets.A set of 300 rubber sheets were divided into a calibration(200 samples)and prediction groups(100 samples).The calibration set was used to develop NIRS calibration equation using different calibration models,Partial Least Square Regression(PLSR),Least Square Support Vector Machine(LS-SVM)and Articial Neural Network(ANN).Among the models investigated,the ANN model with therst derivative of spectral preprocessing presented the best prediction with a coe±cient of determination(R^(2)_(P))of 0.993,root mean square error of calibration(RMSEC)of 0.126%and root mean square error of prediction(RMSEP)of 0.179%.The results indicated that the proposed NIRS-ANN model will be able to reduce human error and provide a highly accurate estimate of the moisture content in a rubber sheet compared to traditional wet chemistry estimation methods according to AOAC standards.
文摘This paper presents experimental performance and artificial neural network modeling of a large-scale greenhouse solar dryer for drying of natural rubber sheets. The dryer consists of a parabolic roof structure covered with polycarbonate sheets on a concrete floor. The dryer is 9.0 m in width, 27.0 m in length and 3.5 m in height. Nine 15-W DC fans powered by three 50-W PV modules were used to ventilate the dryer. To investigate its performance, the dryer was used to dry six batches of natural rubber sheets. For each batch, 750 kg of rubber sheets were dried in the dryer. Results obtained from the experiments showed that drying temperatures varied from 32 ~C to 55 ~C and the use of the dryer led to a considerable reduction of drying time, as compared to the open air sun drying. In addition, the quality of the product from the dryer was high-quality dried products. A multilayer neural network model was developed to predict the performance of this dryer. The predictive power of the model was found to be high after it was adequately trained.
文摘The phenolic resin-chloroprene nthher was used for sandwich in manufueturing the vibra-tion damping laminated steel sheet (also calied laminated sheet), Il is a metal matrix com-posite. The tensie-shear tests have been conducted over a range of temperatures from 20C to 150C and at the strain rates from 1.67× 10 ^(5) to 1.67× 10^(-2)s^(-1). The results show that test temperature will significaiilly affect the tensile shear strength of laminated sheet. and a minimal strength and a minimal activation energy occur near 80C . The tensile-shear breaking morphology of laminated sheet varies with strain rate and test temjteralurc.
