Design of data feature-driven 1D/2D convolutional neural networks classifier for recycling black plastic wastes through laser spectroscopy

In this study, two types of convolutional neural network (CNN) classifiers are designed to handle the problem of classifying black plastic wastes. In particular, the black plastic wastes have the property of absorbing laser light coming from spectrometer. Therefore, the classification of black plastic wastes remains still a challenging problem compared to classifying other colored plastic wastes using existing spectroscopy (i.e., NIR). When it comes the classification problem of black plastic wastes, effective classification techniques by the laser spectroscopy of Fourier Transform-Infrared Radiation (FT-IR) with Attenuated Total Reflectance (ATR) and Raman to analyze the classification problem of black plastic wastes are introduced. Due to the strong ability of extracting spatial features and remarkable performance in image classification, 1D and 2D CNN through data features are designed as classifiers. The technique of chemical peak points selection is considered to reduce data redundancy. Furthermore, through the selection of data features based on the extracted 1D data with peak points is introduced. Experimental results demonstrate that 2DCNN classifier designed with the help of 2D data feature selection as well as 1DCNN classifier shows the best performance compared with other reported methods for classifying black plastic wastes.     

嵌套式复合型材构件制造技术及其专用机床

嵌套式冷轧复合型材构件制造技术包括平整、加强筋成型、第一辊压模具组成型、冲孔、主截面成型、第二辊压模具组的横截面成型、嵌套合抱、第一构件与第二构件嵌套抱合后成为复合型材构件与第三辊压模具组紧贴等工序组成,在冲孔工序之前先完成加强筋成型工序,保证冲孔加工后的孔距尺寸精度,显著提高产品质量;上述所有工序都是设置在同一条生产线上的专用机床连续自动完成,实现了嵌套式冷轧复合型材构件的自动化生产,节约工时,降低产品成本。     

零能耗太阳能住宅的工业化建造

当前建筑业正处于向工业化发展转型的重要时期,以中国国际太阳能十项全能竞赛(SD 2013)中的北京交通大学"i-Yard"参赛作品为例,重点从建筑部品系统的划分和工业化建造等方面进行解析,为零能耗、可持续建筑的模数化设计和快速工业化生产提供了有益的参考。     

一种基于可预测偏最小二乘法的故障检测方法

将可预测元分析(Fore CA)与偏最小二乘法(PLS)结合用于故障检测,在选取合适的可预测元的基础上,运用偏最小二乘回归,进一步提高模型对系统的预测能力,克服了偏最小二乘回归方法无法反映系统动态时序特性的缺陷,并构造CUSUM统计量和SPE统计量以检测故障是否发生。最后通过TE模型上的仿真实验结果表明:Fore PLS方法能有效检测慢漂移等故障。     

基于主成分分析法的燃料乙醇行业清洁生产水平综合评价

燃料乙醇行业是可再生能源的重要组成部分,但是燃料乙醇行业具有高能耗、高污染等特点,环保压力巨大。文章基于主成分分析法对调研的8家燃料乙醇企业9条生产线进行清洁生产综合评价,找到了不同指标之间的相关性和信息重叠之处,提炼出了不同燃料乙醇企业清洁生产评价中的主要控制指标,得到了主成分表达式及主成分综合评价模型,评价结果与百分制法评价结果基本一致,表明主成分分析法在燃料乙醇清洁生产中的综合评价中是一种客观科学的方法。     

双组分聚氨酯人造草背胶的研制

介绍了一种双组分聚氨酯人造草背胶的制备方法,以聚醚多元醇、异氰酸酯为主体原料,3,3'-二氯-4,4'-二氨基二苯基甲烷(MOCA)为扩链剂,研究了不同聚醚多元醇质量比、扩链剂用量、异氰酸酯质量比、异氰酸酯指数对人造草背胶操作时间、脱粘时间及力学性能的影响。结果表明,当异氰酸根指数为0.99,A组分中聚醚多元醇MN-3050与DL-1000质量份数分别为80、20,A组分中扩链剂MOCA用量为4份,B组分中MDI-50与PM-200质量比为1∶1,当A、B组分按质量比2∶1混合时,操作时间及脱粘时间最佳,人造草背胶的综合力学性能达到最好。     

Lurgi MTP工艺循环烃组分分布研究

采用气相色谱仪对德国Lurgi MTP工艺的C4循环烃进行分析,并从MTP催化剂运行周期方向考察了循环烃的组分变化规律。分析结果表明,C4循环烃主要组分是烷烃,约占其总物质的量的57%,其余组分为烯烃和少量的甲醇、二甲醚;其中,各组分含量大小为:异丁烷异丁烯正丁烷1-丁烯反-2-丁烯。     

蜂窝陶瓷负载锰酸锶镧基催化剂制备及性能

采用不同浓度硝酸和草酸溶液,对堇青石蜂窝陶瓷载体进行预处理,考察了酸处理对载体失重率、吸水率及压缩强度的影响。采用催化剂粉体浆料涂覆法,制备了堇青石蜂窝陶瓷负载锰酸锶镧基La0.8Sr0.2Mn0.4Al0.4Zn0.2O3-δ(LSMAZ)整体式催化剂,运用X射线衍射(XRD)、扫描电镜(SEM)等手段对催化剂进行表征,并在管式反应器上进行甲烷催化燃烧活性测试。结果表明,酸处理能增大载体比表面积和吸水率;相同条件下草酸对载体的侵蚀效果优于硝酸;提高草酸浓度能增强侵蚀效果,但过高浓度的酸处理会使载体压缩强度过小而无法应用。经1050℃煅烧5 h后,所制备的整体式催化剂具有适宜的脱落率,无明显载体-LSAMZ界面反应,并具有最高的甲烷燃烧催化活性。     

Mixture semisupervised principal component regression model and soft sensor application

Traditionally, data‐based soft sensors are constructed upon the labeled historical dataset which contains equal numbers of input and output data samples. While it is easy to obtain input variables such as temperature, pressure, and flow rate in the chemical process, the output variables, which correspond to quality/key property variables, are much more difficult to obtain. Therefore, we may only have a small number of output data samples, and have much more input data samples. In this article, a mixture form of the semisupervised probabilistic principal component regression model is proposed for soft sensor application, which can efficiently incorporate the unlabeled data information from different operation modes. Compared to the total supervised method, both modeling efficiency and soft sensing performance are improved with the inclusion of additional unlabeled data samples. Two case studies are provided to evaluate the feasibility and efficiency of the new method. © 2013 American Institute of Chemical Engineers AIChE J 60: 533–545, 2014