摘要：
BGA micro-joint with double substrates used by SAC305 lead-free solder is fabricated by reflowing process based on substrate FR-4. The microstructures of the solder joints are studied through the method of rapid thermal cycling (RPC). The double-based plate Cu/SAC305/Cu solder joint was tested at extreme temperature 60-180 degrees C by rapid thermal cycling 48 hours and 72 hours respectively, it was found the IMC grow by the zigzag shape, and fatigue cracks greatly appear at the interface of IMC/Cu, they are initiating and propagating along the boundary, and thread through the cross section of solder joint in the end, which lead to the failure of solder joint.
摘要：
The purpose of this study is to conduct qualitative analysis on the adulteration in peanut oil by combining data fusion of Raman and near infrared (NIR) spectral characteristics with chemometrics methods. With laser Raman and NIR spectrometer, the spectra of 134 adulterated oil samples and 24 pure peanut oil were collected. The spectra data of Raman and NIR were preprocessed. Competitive adaptive reweighted sampling(CARS) were used to extract the characteristic wavelengths of the spectra data. Combining data fusion technique and partial least squares linear discriminant analysis (PLS-LDA) method, the Ram-PLS-LDA model, NIR-PLS-LDA model and Ram-NIR-PLS-LDA model were established by using the obtained feature layer data. The calibration set and prediction set accuracy of the SG9-airPLS-Nor-CARS-SNV_DTCARS-PLS-LDA model are 100%. According to the analysis, the prediction accuracy of Ram-NIR-PLS-LDA model is better than that of single spectral model, data fusion technology can enhance the ability to identify the model, which is conducive to practical application. It shows that the two kinds of spectra are complementary, and the using of spectral analysis and data fusion technology has great application value in the identification of edible oil.
摘要：
The objective of this paper is to investigate the effect of rapid thermal cycling on microstructure and optical property (luminous flux and luminous efficiency) of high power light emitting diode (LED) by thermal fatigue testing from -40 to 125. Under an application of thermal fatigue device as a heating source, the specimens that were being non-operating and thermal fatigue testing in the experiment were rapidly heated and cooled based on a control system that employs a fuzzy logic algorithm, respectively. The optical performances, including luminous flux, luminous efficiency, radiant power and color temperature (CCT) of LED specimens were tested and analyzed. It was found that the rapid thermal cycling have similar evident influence on them. The results showed that the color purity of LED was also descended, the correlated color temperature (CCT) was also risen, but their changing rate and extents are different. The high and low temperature distribution in LED chip was simulated by finite element modeling which is helpful for the failure analysis and design of the reliability of the LED packaging. The microstructures of LED chips are analyzed after different rapid thermal cycling time. The results are showed that rapid thermal cycling can affect greatly the LED properties and interface microstructures. All the results indicate that this approach to rapid thermal cycling by using rapid heating source is feasible to investigate the optical performance of high power LED, so it can also effectively verify the reliability of LED devices.
摘要：
An approach based on multi-source spectra data fusion for identification of edible oil is proposed. A qualitative model based on fusion of Raman spectra and near-infrared spectroscopy (Raman-NIR) was established and compared with conventional single-spectra model. The spectra data was pre-processed using the moving average method (MA11), the Savitzky-Golay method (SG9), the adaptive iteratively reweighted penalized least squares method (airPLS), the normalization method (Nor), the multiplicative scatter correction method (MSC), and the standard normal variant and standard normal variant transformation de-trending method (SNV-DT). Then, optimized characteristic variables were selected using the competitive adaptiive reweighted sampling method (CARS-SPA) and the backward interval partial least squares method (BiPLS). Based on that, a model for identification of edible oil was established using the support vector classification method (SVC). The results revealed that the SVC model established can accurately identify and classify eight different edible oil (soybean oil, peanut oil, rapeseed oil, tea seed oil, rice oil, corn oil, sunflower oil, and palm oil). The prediction accuracy for samples in calibration set and prediction set by the proposed model can be 100%, which is superior to that of conventional single-spectra model. The proposed model exhibits excellent generalization capability. Additionally, the study suggests that the Raman-NIR fusion shows improved efficiency in identification of edible oil and great potential for practical application.
会议论文集名称：
DEStech Transactions on Computer Science and Engineering
关键词：
Raman;Near infrared;Chemometrics;Edible oil;Iodine value
摘要：
Based on Raman and near infrared spectroscopy (NIR), the modeling of edible-oil iodine value was conducted following chemometrics and support vector machine regression (SVR). The Raman and NIR spectral data of 44 oil samples were collected and preprocessed. The preprocessed spectral data at characteristic wavelengths were extracted with CARS and iPLS methods. Parameter optimization was performed following the grid search algorithm (GS), for the SVR iodine value prediction models. The results show that all the models built could predict the iodine values to some extent. An NIR-MSC-iPLS-SVR model exhibited the greatest stability and its correlation coefficient R of the prediction set reached 97.69%. The results show that NIR has more advantages in the fast prediction of iodine values and can be utilized to manufacture portable spectral instruments for edible-oil iodine-value determination. Vegetable oils can afford human body unsaturated fatty acids, vitamins, and other nutrients [1]. Wherein, the unsaturated fatty acids can ensure the physiological function of cells, reduce cholesterol contents, and perfect blood circulation [2]. The unsaturated fatty acid content can be indicated by unsaturation degree and iodine value (iodine number). The iodine value refers to the grams of iodine consumed in the addition reaction of 100 g of oil. The higher the iodine value is, the greater the unsaturation degree is, and the higher the unsaturated fatty acid content is. The iodine value determination methods include Wijs method (national standard), high-performance liquid chromatography (HPLC) method, and so forth [3-4]. Wherein, the Wijs method is precise and commonly used. Nevertheless, because the sample and titrant solution are immiscible, at the end point of titration, the color change is too slow. And, the method is tedious and requires a large amount of hazardous organic solvents [5-6]. Compared with the Wijs method, the spectral method is fast, efficient, and free of sample pretreatment. Hence, it has been increasingly used in oil and food industries [7]. Yu Yanbo et al. [8] used near infrared spectroscopy (NIR) technology to build a prediction model for the prediction of contents of 4 fatty acids in vegetable oils. Maria A. Carmona et al. [9] identified oils and determined iodine values based on Raman spectroscopy.
