智能农业机械装备在我国扶贫事业中的影响

从长远来看,开发智能农业机械是全球的灯塔.近年来,智能农业机械在中国发展迅速.着眼于优化产业升级,促进农业发展,加快"美丽乡村"工程的发展,结合智能农业机械的发展和自身的脱贫特点,协助有针对性地脱贫.     

利用RIL群体对水稻再生力及相关农艺性状的QTL分析

以粳糯稻品种糯89-1与籼型重穗型杂交稻骨干恢复系蜀恢527杂交构建的籼粳交F₇代RIL群体的169个家系为作图群体,构建了一张含105个微卫星(SSR)标记的分子连锁图谱。定位了水稻正季7个农艺性状的QTL 15个,分布在第1、第2、第3、第5、第6、第7、第10染色体上,LOD值介于2.10~7.51,贡献率3.77%~25.37%,其中贡献率10.0%以上的QTL 7个,单个性状的QTL 1~4个;定位了水稻再生季7个农艺性状的QTL 19个,分布在第1、第2、第3、第4、第5、第6、第7、第10染色体上,LOD值介于2.17~18.34,贡献率3.23%~37.66%,其中贡献率10.0%以上的QTL 7个,单个性状的QTL1~5个;定位了影响水稻再生力(最终再生率)的QTL 2个(qRa4,qRa5),分别在第4和第5染色体上,贡献率分别为8.17%和7.09%,加性效应分别为0.32和-0.39,贡献率和加性效应均较小,属微效基因。共检测到两季农艺性状QTL 36个,同一性状被重复检测的QTL 8个。水稻再生力与正季稻有效穗呈极显著负相关;水稻再生力与再生稻有效穗呈极显著正相关,与每穗总粒数和着粒密度呈显著负相关。QTL定位结果揭示了有效穗是影响再生力的主要因素。     

Design of nondestructive test system for plasma clots

One of the most important measures that are used to guarantee blood transfusion safety is to detect clots in the plasma before transfusion. To overcome the disadvantages of manual detection method, this research designs a nondestructive testing (NDT) system for plasma clots inspection based on machine vision technique and artificial neural networks. The key technology for system design are studied and presented. Image acquisition is performed by custom-designed software based on MATLAB platform, and the methods of image cut, reverse color, median filter as well as gray cutting are adopted to preprocess image. The use of fisher discrimination method, combined with iterative threshold segmentation method and the selection of connected domain, can successfully eliminate the interference of air bubble and correctly extract the image of plasma clots. Plasma clots are discriminated by a recognition model based on artificial neural network BP algorithms. The results of clinical contrast experiment shows that the system can effectively detect whether plasma contains plasma clots and the new system shows a much higher degree of repeatability and stability. From the image acquisition and processing to the recognition of plasma clots, the detecting time of a sample is no more than 1 min.     

Online MW-MSPCA data-driven fault diagnosis

To track the non-stationary dynamics of the process which contains time-varying and multi-scale data, an online moving window multi-scale principal component analysis（MW-MSPCA） data-driven-based fault diagnosis method is proposed. In this data-driven diagnosis technique, wavelet threshold denoising is used to solve the conflict between the statistical model deviation and data correlation decreasing. The statistical models are updated by using moving window principal component analysis in various scales. The contribution of individual process variable to the process behavior change is illustrated in a 3-dimensional contribution chart. A quantitative evaluation mechanism is also given to evaluate the diagonising accuracy. The numerical experimental results for 6135D diesel demonstrate that the proposed method can diagnose sensor fault better in terms of false rejection, false alarm and diagnosing accuracy for fault diagnosis upon comparing with conventional multi-scale principal component analysis（MSPCA） and adaptive multi-way principal component analysis（AMPCA） modeling.     

A valve camshaft load torque calculation and camshaft vibration control analysis

Aiming at the overhead camshaft valve mechanism,the theoretical and numerical solutions of camshaft load torque are calculated respectively by a derived formula and transient finite element analysis. The two solutions show good agreement,thus the correctness of the transient finite element model is verified. By combining with camshaft instantaneous constraint modal analysis and vibration response with consideration of gas pressure,it is found the position of camshaft which easily excites resonance and the main influence factors of camshaft vibration. Then the effect of the width of bearing seat on the camshaft vibration is investigated and the results show that the vibration of camshaft is mainly bending vibration,appropriate width of bearing seat can effectively control the camshaft vibration.     

Multi-scale optical flow estimation of the video based on gradient optimization

A new algorithm based on gradient optimization is proposed for optical flow estimation of video images with different motion ranges. The original video images are transformed by using Loggabor filtering on phases and measures,and then the spatio-temporal gradient is calculated by using the obtained feature images. The optical flow is calculated with the spatio-temporal gradient. The video images are layered and processed with coarse-to-fine image pyramid method. The theoretical analysis and experimental results show that the algorithm is suitable for the video optical flow motion estimation of the significant range. It can not only obtain the video images following the human visual resolution characteristics, but also optimize the spatio-temporal gradient, while the optical flow calculation is more accurate. Besides, the time complexity of this algorithm is equivalent to that of the traditional optical flow method, and the accuracy of the algorithm is superior to the methods suggested by Horn-Schunck, Duan,et al.     

茶叶渣对水溶液中Cu2+的吸附研究

为研究茶叶渣对水溶液中Cu2+的吸附及其机理,利用台湾高山茶叶渣对水溶液中Cu2+进行了吸附实验,考察pH、吸附时间、反应温度、Cu2+初始浓度等因素对吸附效能之影响。实验结果表明：台湾高山茶叶渣对Cu2+有很好吸附效果,吸附平衡时间约为60 min;随着反应温度增加,对Cu2+的吸附效能逐渐提高。在固定初始Cu2+浓度、吸附时间、震荡转速及反应温度下,pH会影响茶叶渣对Cu2+的吸附效能,pH 4时吸附效果最佳。对Cu2+的吸附效能均可使用Langmuir与Freundlich等温吸附方程式进行推估,但比较相关系数,前者较后者有更佳的推估能力;分别计算30、40和50℃下的吸附热力学参数,对应的吉布斯自由能(ΔG0)均为负,表明该反应自发进行;焓变(ΔH0)＞0,证实该反应为吸热反应;熵变(ΔS0)＞0,说明该吸附反应是熵增的过程;茶叶渣吸附前后的红外谱图分析,表明物理吸附为茶叶渣吸附Cu2+的主要机制。     

陆地棉背景下海岛棉第18染色体片段置换系的培育及相关农艺性状QTL定位

Sub18是以陆地棉遗传标准系TM-1为背景, 含海岛棉3-79第18染色体的置换系材料。本研究以TM-1为受体亲本, 置换系Sub18为供体亲本, 借助分子标记辅助选择技术培育了一套以TM-1为背景, 含海岛棉3-79第18染色体不同长度片段的置换系。这套置换系由45个株系构成, 共78个置换片段。其中27个株系导入单片段, 占总株系的60%; 9个株系导入2个片段, 占20%; 9个株系导入3个及以上片段, 占20%。导入片段总长度为467.6 cM, 约为该染色体遗传长度的4倍, 每个株系内被替换的染色体片段长度不完全相同, 平均遗传长度为5.99 cM, 最短的为0.9 cM, 最长的20.35 cM。其中13个株系表现开放花蕾性状, 涉及的最短导入片段长5.05 cM。对TM-1、Sub18以及培育的45个导入系进行农艺性状调查和QTL联合定位分析, 鉴定出纤维强度(qFS-C18-1)、整齐度(qFU-C18-1)、马克隆值(qFMi-C18-1)、成熟度(qFMa-C18-1)、皮棉重(qLW-C18-1)、籽指 (qSI-C18-1)和衣分 (qLP-C18-1) 7个加性QTL和5个上位性效应QTL。研究结果为进一步精细定位目标QTL、克隆QTL以及重要性状分子设计育种奠定了基础。     

Lighting quality indicators with space sense for urban lighting environment

In order to find out a space sense indicator that can present the real appearance of human and natural in urban lighting environment, three common used indicators are studied, which are ratio of vertical illuminance to semi cylindrical illuminance, ratio of vertical illuminance to horizontal illuminance and ratio of average cylindrical illuminance to horizontal illuminance.An on site test is taken at Three Gorges Square Pedestrian Street of Chongqing. The variation law of ratio of vertical illuminance to horizontal illuminance is approximate to ratio of average cylindrical illuminance to horizontal illuminance, which varies with the changing of measure point location and reach maximum at the axial central section of pedestrian street between two streetlamps. The change of ratio of vertical illuminance to semi cylindrical illuminance is small correspondingly and it is more appropriate to be as a lighting quality indicator with space sense for urban illuminance environment.     

Analysis of shift schedule for the automatic transmission vehicle based on fuzzy neural network

The advantages and disadvantages of present methods for shift schedule analysis of automatic transmission vehicle are analyzed. An optimum shift schedule method based on fuzzy neural network is proposed. The structure and algorithm with Takagi-Sugeno mode is studied. Fuzzy logic rules with two parameters and membership functions for shift schedule are established according to the skilled driver’s experience and expert’s knowledge. The membership functions and fuzzy logic rules are modified through train mechanism of artificial neural network based on experiment sample. The fuzzy neural network is trained and simulated. The simulation results indicate that this shift schedule method based on fuzzy neural network of Takagi-Sugeno model is feasible and correct.