Output-relevant Variational autoencoder for Just-in-time soft sensor modeling with missing data

Main challenges for developing data-based models lie in the existence of high-dimensional and possibly missing observations that exist in stored data from industry process. Variational autoencoder (VAE) as one of the deep learning methods has been applied for extracting useful information or features from high-dimensional dataset. Considering that existing VAE is unsupervised, an output-relevant VAE is proposed for extracting output-relevant features in this work. By using correlation between process variables, different weight is correspondingly assigned to each input variable. With symmetric Kullback–Leibler (SKL) divergence, the similarity is evaluated between the stored samples and a query sample. According to the values of the SKL divergence, data relevant for modeling are selected. Subsequently, Gaussian process regression (GPR) is utilized to establish a model between the input and the corresponding output at the query sample. In addition, owing to the common existence of missing data in output data set, the parameters and missing data in the GPR are estimated simultaneously. A practical debutanizer industrial process is utilized to illustrate the effectiveness of the proposed method.     

A review of topic modeling methods

Topic modeling is a popular analytical tool for evaluating data. Numerous methods of topic modeling have been developed which consider many kinds of relationships and restrictions within datasets; however, these methods are not frequently employed. Instead many researchers gravitate to Latent Dirichlet Analysis, which although flexible and adaptive, is not always suited for modeling more complex data relationships. We present different topic modeling approaches capable of dealing with correlation between topics, the changes of topics over time, as well as the ability to handle short texts such as encountered in social media or sparse text data. We also briefly review the algorithms which are used to optimize and infer parameters in topic modeling, which is essential to producing meaningful results regardless of method. We believe this review will encourage more diversity when performing topic modeling and help determine what topic modeling method best suits the user needs.     

川西彭州地区雷口坡组潮坪相薄储层辨识机理研究

川西彭州地区三叠系雷口坡组雷四上亚段潮坪相薄储层识别难度极大。围绕如何从复合地震强反射中区分并识别上、下两套储层面临的地球物理难题,采用先“分”后“合”的研究思路,基于实际地层结构及不同储层叠加样式建立正演模型,利用全波场波动方程正演模拟技术,剖析了不同主频条件下薄储层的地震响应特征,通过波形差异化分析,从复合地震响应中“剥离”出了两套储层所引起的地震响应特征及变化规律,明确了两套储层在不同频带下的地震识别标志和识别方法,为该区强反射界面干扰下两套薄互层储层辨识机理分析及精准预测奠定了基础。基于不同频带下薄储层辨识机理的分析结果,定性预测了薄储层平面展布,提出了深层潮坪相薄储层识别和预测难题的解决方案,为该区地震资料品质评价、面向薄储层的地震采集技术设计、地震资料处理及薄储层预测提供了依据和指导。     

基于GFU和分层LSTM的组群行为识别研究方法

提出一种以"关键人物"为核心，使用门控融合单元（GFU，Gated Fusion Unit）进行特征融合的组群行为识别框架，旨在解决两个问题：①组群行为信息冗余，重点关注关键人物行为特征，忽略无关人员对组群行为的影响；②组群内部交互行为复杂，使用GFU有效融合以关键人物为核心的交互特征，再通过LSTM时序建模成为表征能力更强的组群特征.最终，通过softmax分类器进行组群行为类别分类.该算法在排球数据集上取得了86.7%的平均识别率.     

空气弹簧液压悬置动特性及隔振特性研究

研究了具有可变刚度阻尼的发动机空气弹簧液压悬置的动特性和隔振特性。针对影响发动机空气弹簧液压悬置动特性的关键参数上液室等效体积刚度,采用理论和试验方法研究了上液室等效体积刚度的等效值,基于该等效值建立了空气弹簧液压悬置的理论模型,对空气腔开闭两种工况进行了空气弹簧液压悬置动特性的仿真和试验研究。搭建了发动机空气弹簧液压悬置系统试验台架,研究了台架各种激励频率下的空气弹簧液压悬置的隔振特性。结果表明:本研究采用的上液室等效体积刚度进行空气弹簧进行建模是正确、可行的,提高了空气弹簧建模效率和准确性;空气弹簧液压悬置在空气腔开启和关闭两种状态下,峰值动刚度增大幅值达78.5%,峰值阻尼角增大幅值达250%。台架试验表明:当台架激励频率小于25Hz时,悬置采用大刚度大阻尼;当台架激励频率大于等于25 Hz时,悬置采用小刚度小阻尼;悬置隔振率提升明显,不同频率下提升幅值达10%～67%。     

FDM用PETG系列耗材的改性研究

对市售聚对苯二甲酸乙二醇酯-1，4-环己烷二甲醇酯（PETG）丝材及原材料进行研究，选用PETG 2012作为制备熔融堆积成型技术（FDM）用PETG丝材的基体树脂。选用聚碳酸酯（PC）对基体PETG进行增韧增强改性，并制成3D打印高分子丝材进行打印测试，探讨了PC含量对PETG耗材及制件性能的影响。结果表明，在低PC含量下，PETG与PC的相容性较好，PETG与PC制件未出现明显的分层，分布比较均匀；共混物的流动性随着PC含量的增加而降低，且打印件的维卡软化温度和热变形温度随着PC用量的增加而增加；此外，PC材料的加入使得PETG打印件的力学性能得到较大改善：打印件的拉伸强度随着PC用量的增加而增大，缺口冲击强度却随着PC用量的增加呈现先增加后减小的趋势； PETG/PC的配比为1∶1时，可制得力学性能优异的3D打印耗材。     

响应面法优化制备LDHs-CRMA复合改性沥青及其表征

采用熔融共混法，以克拉玛依90^#沥青为原料，Mg-Al水滑石(LDHs)与废橡胶粉(CR)作为改性剂，制备了具有抗紫外老化性能的水滑石/废胶粉复合改性沥青(LDHs/CRMA)，并对其软化点、针入度指数(PI)、延度进行了测试。通过Hassan数学方法将三个指标“归一化”得到总评“归一值”，采用响应面分析法建立总评“归一值”与各因素之间的Box-Behnken数学模型，得到了LDHs/CRMA的最优制备工艺条件为：剪切温度173℃、剪切时间89 min、剪切速率3500 r/min。通过紫外老化模拟实验对复合改性沥青的抗老化性能进行了评价，结果表明，引入水滑石可以减少沥青老化过程中含氧官能团的产生，抗紫外老化性能得到了明显提高。     

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.     

A two-layered cross coupling control scheme for a three-dimensional motion control system

A two-layered modeling and compensation scheme is proposed to reduce the contouring error of a three-dimensional motion control system. In the proposed scheme, the contouring error model of the three-dimensional motion control system is divided into two layers: the top layer and the bottom layer. The proposed multi-layered structure of the contouring error model presents more flexibility in the control system design because the cross coupling controllers in different layers can be designed separately. In this paper, a nonlinear PI controller and a position error compensator are designed in the bottom layer in order to achieve high contouring accuracy in the XY plane, while a unilateral compensator is designed in the top layer to further reduce contouring error in the three dimensional space. Finally, experiments are performed to verify the performance of the proposed two-layered modeling and compensation scheme. Experiment results show that the designed two-layered cross coupling controller can obtain higher contouring accuracy than traditional cross coupling controller both in the XY plane and in the XYZ space.