Huacai Chen

Study on Optical Fiber Bragg Grating Temperature Sensors for Human Body Temperature Monitoring

It is usually that the sensitivity of fiber Bragg grating(FBG) temperature sensor is low, that is 0.010nm/°C, Which is not efficient for the accurate measurement of human body temperature. This paper develop two methods of FBG encapsulation to increasing the sensitivity of FBG temperature sensor. First, we used epoxy resin to encapsulate the FBG in Teflon pipe. Although temperature sensitivity was significantly improved about 12 times higher than naked FBG temperature sensor, its linearity was inferior than naked FBG sensor. In order to not destroy the linearity of the temperature sensor, we let the FBG in a free state in the capillary tube, only fix the two endpoint. The temperature sensitivity is 23.4pm/°C, and the linearity is good.

Effect of LED Supplemental Illumination on the Growth of Strawberry Plants

Effect of LED supplemental illumination on the growth of strawberry plants is presented. Four LED combination lighting systems with different LED colors and power were designed and developed for supplemental illumination of the strawberry plants cultivated in the greenhouse. The LED supplemental illumination time is 4 hours everyday. The growth parameters of the strawberry plants were measured every 7 days. The plant height, leaf number, petiole length, leaf area of the strawberry plants which cultivated with LED supplemental illumination were more superior to those cultivated under the normal condition. However, there was no significant difference in the number of blossoms and fruits. The study results indicated that the supplemental illumination with LED combination lighting systems could promote the vegetative growth of strawberry plants and the promoting effect is better with the LED power increase. LEDs combination of orange/red/blue ratio of 3:2:1 is more superior to the LEDs with red/blue ratio of 5:1. the spectrum of the former is much more similar to the absorption spectrum of the plant photosynthesis.

An Intelligent Controlling System for LED Plant Supplemental Lighting Greenhouse

An intelligent controlling system for LED plant supplemental lighting greenhouse is presented in this paper. The key unit of the system is a remote controlling and management center, which comprises of the sensing subsystem, the data acquisition subsystem, the information processing subsystem and the execution subsystem. The combined lighting with red and blue LED was used to provide supplemental lighting for plants in greenhouse. In order to adjust the environment of greenhouse, the controlling system will obtain real-time parameters feedback of the temperature, the relative humidity and the light intensity, and send commands to the execution subsystem through RS-485 communication lines.

Determination of Catechin Monomers in Tea Polyphenols Powder Using NIR and ANN

Near infrared diffuse reflectance spectra of 52 tea polyphenol powder samples were collected with FT-NIR spectrometer. The calibration models of total catechins(TC) were established with back-propagation artificial neuron network(BP-ANN) and radical based function artificial neuron network (RBF-ANN) and optimized with prediction sample set. The result showed that the RBF-ANN model is better than the BP-ANN model. Calibration models of total ester catechins(TEC), total simple catechins(TSC), catechin monomers (EGCG, GCG, ECG, D,L-C, EC and EGC) were established with RBF-ANN. The models of TC, TEC, TSC, EGCG, ECG were robust with prediction correlation coefficient(R) above 0.9 and prediction relative standard error (RSE) less than 0.10%. The models of GCG, D,L-C, EC, EGC had much higher RSE of over 0.15%. This result suggests that it is feasible to rapidly determinate the contents of TC, TEC, TSC, EGCG, ECG in tea polyphenols powder with NIR spectroscopy combined with RBF-ANN models.

A new apparatus for continuous measuring the falling velocity of the wind-dispersal seeds

A new apparatus for continuous measuring the falling velocity of wind-dispersal seeds is presented in this paper. The key unit of this apparatus is the photo-detectors installed on the ends of a vertical tube. The photodetector is composed of a LED and a photo-sensor. The LED light goes through a horizontal slit to from a flat light plane, which be received by the photo-sensors on the opposite side. When a plant seed falls down and passes through the flat light plane, a pulse signal will be detected by the photo-sensor. The average falling velocity of the seed is calculated according to the falling time and the distance from the starting point to the testing point. By using several tubes and photo-detectors, the apparatus can continuously measure the velocity of a seed falling down to different height. This apparatus avoids the affect of the static electricity and airflow to the seeds.

Non-Destructive Determination of the Quality Components in Fresh Pork Meat Using near Diffuse Reflectance Spectroscopy

Two kinds of sampling methods of optics integrating sphere diffuse reflectance chamber and optical fiber diffuse reflectance probe were employed to collect the near-infrared spectra of 72 fresh lean pork meat samples, respectively. The amount of fat, protein and water in pork meat were determined by the national standard analysis methods as reference. The quantitative analysis models of the above constituents in pork meat were developed by using partial least squares (PLS) regression with internal cross-validation and optimized through spectra pretreatment and spectra region selection. The correlation coefficients (R2) of the calibration models of fat, protein and water based on integrating sphere diffuse reflectance were 90.24%, 91.95% and 90.15%, respectively. And the values of RMSECV of these models were 0.377%, 0.011% and 0.323%, respectively. For the models on optical fiber bundle diffuse reflectance spectra, the values of R2 were 83.68%, 87.97% and 83.27% respectively, the values of RMSECV were 0.321%, 0.0099% and 0.277%, respectively. The calibration models were further validated by the prediction sample sets. The prediction mean square error (RMSEP) of the three constituents were 0.254%, 0.011% and 0.168% for the models established on integrating sphere diffuse reflectance spectra, the value of R2 were 96.64%, 91.51% and 97.45%, respectively. For the models on diffuse reflectance optic fiber probe spectra, the values of RMSEP were 0.361%, 0.012% and 0.193%, respectively, the values of R2 were 81.03%, 84.48% and 91.39%, respectively. T test results showed that there was no significant difference between actual values and the values predicted by the NIR models. Although the optical integrating sphere got a little higher prediction accuracy and stability than the optical fiber diffuse reflectance probe, both sampling methods could meet the rapid non-destructive determination of the amounts fat, protein and water in pork meat, and the latter is more suitable for hand-held and convenient.

Qualitative Determination of the Components of Textile Products Using near Infrared Spectroscopy

In the paper, A total of 40 pure or two-mixed textile weaves were prepared and classification of these samples was introduced using near infrared spectroscopy (NIRS), all textile samples are selected among four classes, which are Cotton-Terylene, Cotton-Polyurethane, Cotton and Terylene, according to theirs components. Near infrared diffuse reflectance spectra of the samples were collected, Mahalanobis distance was used to discriminate the samples coupled with principle components analysis (PCA), the results showed that near infrared spectroscopy could determine which class one textile weave belongs to easily comparing with traditional methods. In addition, the expectation of the further research on qualitative determination of textile products by NIR technology was discussed in the end of this paper.