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หมวดหนังสือ -> เอกสารสถาบันเทคโนโลยีพระจอมเกล้าเจ้าคุณทหารลาดกระบัง -> Feasibility study on near infrared spectroscopy for evaluation of combustion performance parameters andmoisture content of bamboo chips (dendrocalamus sericeus cl. Phamon)

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Title
Feasibility study on near infrared spectroscopy for evaluation of combustion performance parameters andmoisture content of bamboo chips (dendrocalamus sericeus cl. Phamon)
Title.Alternative
การศึกษาความเป็นไปได้ในการใช้เทคนิคเนียร์อินฟาเรดสเปกโทรสโกปีในการประเมินสมรรถนะการเผาไหม้และความชื้นของไม้ไผ่สับ (dendrocalamus sericeus cl. ฟ้าหม่น)
Creator
Amrit Shrestha
Creator.Orgname
King Mongkut's Institute of Technology Ladkrabang
Subject
Infrared spectroscopy
Subject
Combustion
Subject
Agricultural of Engineering--Thesis
Subject
King Mongkut's Institute of Technology Ladkrabang. Agricultural of Engineering--Thesis
Subject
Bamboo--Combustion
Description.Abstract
Abstract: The combustion performance parameter of the bamboo chips were compared with the L. leucocephalapellet. The ignition index, burnout index and combustionperformance index of grounded bamboo chips were found tobe 88.33E-04, 0.16E-03and 3.95E-07, whereas ignition index,burnout index and combustion performance index of groundedLeucaena leucocephala pellet were found to be 6.10E-04,8.20E-03 and 2.19E-07 respectively. From thethermogravimetric analysis, it can be concluded thatbamboo was easier to burn than the L. leucocephala pelletwhich is confirmed by the higher value of combustionperformance index of bamboo than that of L. leucocephalapellet. In order to measure the moisture content in bamboochip, two diode array near infrared (NIR) instruments, NIR-Gun (short wave, 600-1100 nm at 2 nm intervals) and Micro-NIR (long wave, 1150-2150 nm at 7 nm intervals), wereused for scanning the bamboo chips. Only the bamboo chipsof Dendrocalamus sericeus cl. Phamon were used for thiswork. The scanning for the measurement of moisture contentwas performed in Thailand atmospheric condition in theplantation area, Uttaradit, Thailand. The total number ofsamples used for developing model after removing outlierswas 252. The circumference and moisture content of bamboosused in this research were in the range between 16-39 cmand 39-86% wet basis (wb) respectively. Partial leastsquares regression technique was used to develop themodels to predict the moisture content in bamboo chip. Thecoefficient of determination of prediction set, standarderror of cross validation (SECV), standard error ofpredication (SEP), bias and RPD of optimum model of NIR-Gun are 0.924, 2.871% wb, 2.385% wb, -0.250% wb and3.656.respectively, while the values for Micro-Nir modelare found to be 0.743, 4.349% wb, 4.499% wb, 0.025% wb and1.972, respectively. The performance of the shortwavelength model was found better than long wavelengthmodel for the prediction of moisture content in bamboo dueto higher value of coefficient of determination and RPD.However, in prediction of moisture content in bamboo chips,the model shows the effect of different constituents ofthe bamboo more than moisture. On the other hand, the twodiode array NIR-instruments (NIR-Gun and Micro-NIR) andFourier transform near infrared (FT-NIR) instrument wereused to make model of combustion performance parameteri.e. ignition index, burnout index and combustionperformance index using the same partial least squaresregression technique. The total number of the sample usedfor making the model was 80 for both types of instruments.The samples were grounded to 2 mm size. The diffuse NIR-instruments models of combustion performance parameterused 13-20 PLS factors for the making the model. However,the diffuse NIR-instruments were unable to predict thecombustion performance parameter of the grounded bamboochips with any accuracy. The spectra were suffered fromthe noise, and the variability of the calibration setsamples used for making the models (for combustion index4.613-2.794E-07, ignition index 11.907-6.994E-03, burnoutindex 2.04-1.23E-04) were low. This may be the reason whythe diffuse NIR-instrument failed to predict. In contrast,the FT-NIR was able to predict the ignition index andburnout index but with very low accuracy. The coefficientof determination of prediction set, bias and RPD ofoptimum model of ignition index are 0.432, 3.960E-05 and1.33, with the number of PLS factors of the model 4, andthe coefficient of determination of prediction set, biasand RPD of optimum model of burnout index are 0.513, -2.210E-07, and 1.43, with the number of PLS factors of themodel 7
Publisher
สถาบันเทคโนโลยีพระจอมเกล้าเจ้าคุณทหารลาดกระบัง. สำนักหอสมุดกลาง
Publisher.Place
Bangkok
Publisher.Email
library@kmitl.ac.th
Contributor
Panmanas Sirisomboon
Contributor.Role
Thesis Advisor
Contributor.Email
panmanas.si@kmitl.ac.th
Date.Created
2016
Date.Issued
2018-12-11
Date.Modified
2018-12-24
Type
วิทยานิพนธ์/KMITL E-Thesis
Format
application/pdf
Identifier.KMITL CODE
KMITL-2016-EN-M-100-078
Source.CallNumber
EThesis
Language
tha
Coverage.Spatial
King Mongkut's Institute of Technology Ladkrabang. Central Library
Rights
King Mongkut's Institute of Technology Ladkrabang
Thesis
Thesis (M.Eng.(Agricultural of Engineering)) -- King Mongkut's Institute of Technology Ladkrabang, 2016
Thesis.DegreeName
Master of Engineering (Agricultural Engineering)
Thesis.Level
Master
Thesis.Descipline
Agricultural Engineering
Thesis.Grantor
King Mongkut's Institute of Technology Ladkrabang


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