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压电类智能层合结构的力学和计算模型综述 总被引:2,自引:0,他引:2
综述了压电类智能层合结构的力学和计算模型。基于大量国内外有关压电类智能层合结构的文献 ,根据各自采用的运动学假设、场变量的近似、压电层的表达法以及曲率和温度的影响 ,对压电层合结构的力学和计算模型进行了分类 ,阐述了各种理论的特点及一般形式。 相似文献
33.
湿敏半导体材料电导率计算方法的研究 总被引:3,自引:0,他引:3
结合修正了的耗尽层理论和多孔湿敏半导体的特点,本文提出了一个简单的物理模型作为n型湿敏半导体特征的一级近似。描述了多孔湿敏半导体的导电机理,并给出了湿度与宏观电导率的关系。 相似文献
34.
JAMES E. SIMON AMOTS HETZRONI BRUCE BORDELON GAINES E. MILES DENYS J. CHARLES 《Journal of food science》1996,61(5):967-970
An electronic sniffer using semi-conductor gas sensors that nondestructively measured aromatic volatile gas emissions from fruit was developed to assess blueberry quality. The sniffer detected soft and damaged fruit in packaged containers at a 5% level of damage and distinguished four of five fruit ripeness classes: (1) mature-green and green-pink; (2) blue-pink; (3) blue; and (4) ripe fruit. Sniffer response increased as fruit ripened, as did total concentration of aromatic volatiles. Sniffer response correlated with berry firmness, pH, titratable acidity, and color, and detected differences among 10 cultivars, as did impact response analysis. The electronic sniffer is rapid, nondestructive and may be used to sort and quality check for presence of unripe or damaged fruit in closed packs of fresh berries. 相似文献
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In this work, we assessed the influence of coagulant residual activity and primary proteolysis on Cremoso Argentino cheese melting properties. For that purpose, we made Cremoso soft cheeses using different amounts of coagulant, and also obtained samples in which milk-clotting enzyme was inactivated. Primary proteolysis correlated with residual activity of coagulant in early stages of cheese ripening; however, it was similar in all cheeses after 30 days. The hydrolysis of caseins did not significantly affect the melting ability of the cheeses, expressed as the area increase after heating samples under standardized conditions. Samples with similar proximate composition showed some changes in meltability; those seemed related to pH evolution during ripening. 相似文献
37.
During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes (freshwater) ice types using the Jet Propulsion Laboratory C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters, were acquired concurrently with Earth Resource Satellite 2 (ERS-2) and RADARSAT Synthetic Aperture Radar (SAR) data. This polarimetric data set, composed of over 20 variations of different ice types measured at incident angles from 0° to 60° for all polarizations, was processed to radar cross-section to establish a library of signatures (look-up table) for different ice types. The library is used in the computer classification of calibrated satellite SAR data. Computer analysis of ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using a supervised classification technique indicates that different ice types in the ice cover can be identified and mapped, and that wind speed and direction can have an influence on the classification of water as ice based on single frequency, single polarization data. Once satellite SAR data are classified into ice types, the ice map provides important and necessary input for environmental protection and management, ice control and ice breaking operations, and ice forecasting and modeling efforts. 相似文献
38.
湖泊藻类叶绿素-α和悬浮物浓度的高光谱定量遥感模型研究 总被引:44,自引:3,他引:41
本文利用地物光谱仪对太湖水体进行了光谱测量和同步采样分析,对获得的数据尝试用光谱分离法进行分析,从中分离出蓝藻和悬浮物的特征波峰,建立波峰高度与同步水质采样得到的叶绿素-α浓度和悬浮物浓度的对应关系,得出其遥感定量反演算法,并实际应用在OMIS成像光谱仪图像上. 相似文献
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Shane Y. Hong 《Journal of Intelligent Manufacturing》1993,4(3):233-241
One major bottleneck in the automation of the drilling process by robots in the aerospace industry is drill condition monitoring. This paper describes a system approach to solve this problem through the advancement of new machine design, sensor instrumentation, metal-cutting research, and intelligent software development. All drill failures can be detected and distinguished: chisel edge wear, flank wear, crater wear, margin wear, corner wear, breakage, asymmetry, lip height difference, and chipping at lips. However, in the real manufacturing environment, different workpiece materials, drill size, drill geometry, drill material, cutting speed, feed rate, etc. will change the criteria for judging the drill condition. The knowledge base used for diagnosing the drill failures requires a huge data bank and prior exhaustive testing. A self-learning scheme is therefore introduced to the machine in order to acquire the threshold history needed for automatic diagnosis by using the same new tool under the same drilling conditions. 相似文献