苯胺技术及市场分析

概述了苯胺产品硝化工艺、还原工艺及催化剂;对国内外苯胺装置技术有消耗进行了比较;阐述了国内外苯胺生产及消费;对吉化苯胺装置优势作了重点论述。     

因子分析对水泥生产企业环境影响评价的探讨

我国水泥工业的生产特点是资源和能源消耗较高、环境负荷较大。如何进行环境负荷的合理分析评价，这对企业实施清洁生产和循环经济运行非常重要。作者采用因子分析方法，选取10家不同生产工艺（立窑、湿法窑和新型干法窑）的水泥生产企业，进行了环境负荷的特点分析和综合评价研究。结果表明：（1）用因子分析方法对水泥企业进行环境影响的分析评价是可行的；（2）从生产技术、资源消耗、环境酸化和人体健康等主要反映环境负荷影响的综合指数方面的分析表明．新型干法工艺具有显著的优势．而湿法窑和立窑工艺则明显处于不利的地位。     

化工槽车自动化洗涤装置失效原因分析及对策

对化工槽车自动化洗涤装置失效及其原因进行了分析,指出洗槽机的冲洗和抽水不匹配、洗涤工艺不满足设计要求、硬件出现故障及化学品性质的影响是导致洗涤失效的主要原因,提出了完善现场流程、优化工艺操作、使用自动化控制技术、加强设备维护和保养等解决失效的措施。     

The influence of grinding technique on the liberation of clinker minerals and cement properties

This paper describes a study of the relationship between the physical, chemical and mineralogical parameters of cement products obtained by different grinding mechanisms namely high pressure grinding rolls (HPGR) and ball milling, and their effects upon the properties of cements prepared from the ground clinker. Samples were prepared as narrow size fractions and also as distribution samples. Characterization parameters were ascertained by using XRF, laser sizing, Blaine and BET surface area and image analysis methods. HPGR grinding resulted in higher degrees of liberation of clinker phases arising from the intergranular breakage along the grain boundaries compared to ball mill grinding. As for service properties, water demand of HPGR products was higher than ball mill products resulting from high micro fissured structure. Despite high liberation of particularly alite mineral in HPGR grinding, the compressive strength of ball mill products was slightly higher than HPGR products for narrow size samples. Finally, particle size distribution effect on strength was more obvious for distribution samples; generally ball milling gave higher strength values.     

有限长矩形压力容器的应力分析法

对有限长承受内压的矩形压力容器，本文提出了同时考虑矩形容器６个面相互作用的分析计算方法。用所编制的程序计算了一个实际的矩形容器，得到了满意的结果。     

Experimental design in soap manufacturing for optimization of fuzzified process capability index

In manufacturing industries, the quality of a product depends on the combined effect of multiple input variables working singly or together and therefore attention has been given on process capability indices to shift from single to multivariate domain. In case of multivariable domain the capability to incorporate uncertainties at the time of decision making becomes necessary. Fuzzy system is introduced to take care of this requirement. In this article the process parameters of soap manufacturing industries have been analyzed. The process capability is determined using Fuzzy Inference System rule editor based on a set of justified if then statements as applicable for the process. The data has been collected in linguistic form to derive its process capability, using a set of justified rules and the effect of each factor has been determined using Design of Experiments (DoE) and analysis of variance technique (ANOVA) for improving the soap quality from perspective of its softness. This article ventures to propose a new methodology by integrating Fuzzy with DoE providing better result followed by DoE and Fuzzy Inference system in isolation.     

涂料用稀土催干剂中稀土金属含量分析研究

在一定条件下，以ＥＤＴＡ为络合剂，以二甲酚橙为指示剂，用络合滴定法测定了涂料用稀土催干剂中稀土金属的含量。     

Efficient fault-tolerant collision-free data aggregation scheduling for wireless sensor networks

This paper investigates the design of fault-tolerant TDMA-based data aggregation scheduling (DAS) protocols for wireless sensor networks (WSNs). DAS is a fundamental pattern of communication in wireless sensor networks where sensor nodes aggregate and relay data to a sink node. However, any such DAS protocol needs to be cognisant of the fact that crash failures can occur. We make the following contributions: (i) we identify a necessary condition to solve the DAS problem, (ii) we introduce a strong and weak version of the DAS problem, (iii) we show several impossibility results due to the crash failures, (iv) we develop a modular local algorithm that solves stabilising weak DAS and (v) we show, through simulations and an actual deployment on a small testbed, how specific instantiations of parameters can lead to the algorithm achieving very efficient stabilisation.     

A virtual actuator and sensor approach for fault tolerant control of LPV systems

In this paper, a fault tolerant control (FTC) strategy using virtual actuators and sensors for linear parameter varying (LPV) systems is proposed. The main idea of this FTC method, initially developed for LTI systems, is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator/sensor is modified adding the virtual actuator/sensor block that masks the actuator/sensor fault. The suggested technique is an active FTC strategy that reconfigures the virtual actuator/sensor on-line taking into account faults and operating point changes. The stability of the reconfigured control loop is guaranteed if the faulty plant is stabilizable/detectable. The LPV virtual actuator/sensor is designed using polytopic LPV techniques and linear matrix inequalities (LMIs). A two-tank system simulator is used to assess the performance of the proposed method. In particular, it is shown that the application of the proposed technique results in an improvement, in terms of performance, with respect to the LTI counterpart.     

Fault identification for process monitoring using kernel principal component analysis

In this research, we develop a new fault identification method for kernel principal component analysis (kernel PCA). Although it has been proved that kernel PCA is superior to linear PCA for fault detection, the fault identification method theoretically derived from the kernel PCA has not been found anywhere. Using the gradient of kernel function, we define two new statistics which represent the contribution of each variable to the monitoring statistics, Hotelling's T²and squared prediction error (SPE) of kernel PCA, respectively. The proposed statistics which have similar concept to contributions in linear PCA are directly derived from the mathematical formulation of kernel PCA and thus they are straightforward to understand. The main contribution of this work is that we firstly suggest a fault identification method especially applicable to process monitoring using kernel PCA. To demonstrate the performance, the proposed method is applied to two simulated processes, one is a simple nonlinear process and the other is a non-isothermal CSTR process. The simulation results show that the proposed method effectively identifies the source of various types of faults.