No abstract

In this research, a statistical classification algorithm based on sparse coding is presented to classify the defects on E-glass fiber fabrics adaptively. First, all images are preprocessed by being convolved with the MR8 filter banks to obtain the filter responses. For the filter response space of each type of image, we will learn a Class-specific dictionary, and all the Class-specific dictionaries are concatenated to form a complete dictionary. Then, the reconstructed contribution rate of each atom of the complete dictionary to the image filter response is counted to obtain two types of histogram features of each image. Finally, the improved sparse representation classification is used to classify test defect images based on the histogram features. The proposed adaptive classification method has achieved an average classification accuracy of 96.67% on the dataset collected onsite. The results validate the superiority of the proposed method to E-glass fiber fabrics.

Cooking fume(CF) with harmful pollutants and heat is paid more attention to by many peple. Physical and mathematical model are established on the basis of standard kitchen, and flow field characteristics(FFC) of the exhaust hood(EH) is simulated by CFD. Simulation of flow field of the EH indicates that, reasonable air exhaust rate(AER) is made for emissions of pollutants in kitchen; the effect of grille on flow field of the EH is obvious; the EH height selected correctly is beneficial to enhance the capture efficiency, and the exhaust effect will be strengthened. Air conditioning treatment should be applied in the kitchen and will be beneficial to decrease the indoor temperature of the kitchen and control pollutant concentration.

Mineral sepiolite as inorganic carrier, lauric acid(LA)-stearic acid(SA)as binary PCM(phase change material), CTAB as modifier, ethanol as solvent, mineral energy storage residential composite was prepared by intercalation, and the properties of composites were characterized using thermogravimetry(TG)/differential thermal analysis(DTA),scanning electron microscope(SEM),X-ray diffraction(XRD).Orthogo-nal experimental results show that the optimum proportion of composite materials is A3B2C1D3, the initial phase change temperature is 31.44 °C, phase transition peak temperature is 35.25°C, a wide range of endothermic peak is between 30.0~40.0°C, scope of phase change temperature is 3.81. LA-SA eutectic mixture could be retained by adding into 42.3 wt% porous sepiolite, treated at 80 °C. The weight loss of the composites is no more than 2% when melting/freezing cycling within 100°C, so it has good thermal reliability when applied to building material. Mainly due to relatively high content of mineral impurity, high temperature and CTAB can significantly help improve adsorption rate of mineral sepiolite. Sepiolite as a carrier material has features with low cost, broad sources, non-toxic and non-pollution. The composite material is a healthy residential energy-saving material, and it provides a good prospect for the realization of building energy efficiency, regulating room temperature in summer, and improving human comfort.

It is of great importance to study the impact of the cooking generated contaminants on the indoor air quality in the kitchen since cooking is regarded as the main source of indoor contaminants. This study aims investigate and analysis the indoor air quality of kitchen with using CFD numerical analysis method via the velocity, temperature, humidity CO2 concentration .It is concluded that The temperature distribution are large difference in the kitchen and the maximum value is up to 324K on the work area which near the cooking ,and the CO2 concentration which is close to the stove is 1420ppm,1370ppm, 1470ppm respectively, and it is more than the acceptance criteria (CO2<1000ppm) 42%,37% and 47% respectively. It is serious impact on the staff's physical health.