Prediction maintenance integrated decision-making approach supported by digital twin-driven cooperative awareness and interconnection framework

Predictive maintenance is one of the important technical means to guarantee and improve the normal industrial production. The existing bottlenecks for popularization and application are analyzed. In order to solve these problems, a cooperative awareness and interconnection framework across multiple organizations for total factors that affect prediction maintenance decision-making is discussed. Initially, the structure and operation mechanism of this framework are proposed. It is designed to support the sharing of data, knowledge and resources. As a key supporting technology, the digital twin is also integrated into it to improve the accuracy of fault diagnosis and prediction and support making a maintenance plan with higher accuracy and reliability. Then, under this framework, an integrated mathematical programming model is established with considering the parameter uncertainty and an NSGA-II hybrid algorithm is utilized to solve it. Moreover, an adjustment strategy for a maintenance plan is discussed in response to the dynamic characteristics of the actual maintenance environment. Finally, a case, prediction maintenance decision-making for bearings in grinding rolls of the large vertical mill, is studied. Analysis results verify the advantage of the integrated solving mechanism based on the proposed framework. The framework and integrated decision-making approach can guide the implementation of predictive maintenance with higher accuracy and reliability for industrial enterprises.     

基于主曲线的书法字动态重现算法

如何高效逼真地动态重现书法作品的创作过程日益成为亟需解决的问题,因此文中提出基于主曲线的书法字动态重现方法,解决当前细化算法在提取骨架时存在的无效分支较多、不能保证笔画的连续性和准确性的问题.结合书法字自身结构对主曲线算法进行改进和优化.对书法图像进行骨架提取、骨架追踪、笔顺获取等处理,结合骨架信息和二值图像实现笔画宽度复原,针对笔画宽度存在的“肿瘤”问题,提出“角点剔除法”进行修正,结合HTML5的Canvas绘图技术进行书法字动态书写过程.在模拟数据集上的实验表明,文中算法的书法动态重现取得较好效果.     

A new realization scheme for dynamic PFSCL style

In this paper, a new scheme of logic function realization in dynamic positive feedback source-coupled logic (D-PFSCL) style is proposed. The existing scheme implements only NOR/OR based realization of a logic function. Thus, a complex function in D-PFSCL has high gate count which degrades the overall circuit performance measured in terms of power and delay. This paper therefore aims to resolve the issue by proposing a scheme which modifies the structure of a D-PFSCL gate. The modified gate exhibits AND/OR functionality and is used to realize various functions. Simulations have been carried out by implementing various functions and comparing their performance with the existing schemes at 1 GHz. The results of performance comparison with existing schemes indicates significant reuduction in gate count resulting in overall performance improvement.     

6061铝合金均匀化过程中AlMnSi弥散颗粒的析出尺寸对再结晶行为的影响

利用力学性能测试、光学显微镜、扫描电镜、透射电镜和能谱分析技术等手段研究了均匀化过程中AlMnSi弥散颗粒的析出尺寸对6061铝合金再结晶行为的影响。结果表明:AlMnSi弥散颗粒在均匀化过程中沿着铝基体[001]晶带轴析出长大,晶体结构为体心立方结构。随着均匀化温度的升高,弥散颗粒的析出尺寸逐渐增大,当AlMnSi弥散颗粒平均尺寸由0.07 μm增长到0.42 μm,最大尺寸由0.21 μm增大到1.12 μm时,力学性能则是先升高后降低。6061铝合金T6态组织仍为变形组织;AlMnSi弥散颗粒尺寸增大到1.12 μm,6061合金T6态组织中出现粗大再结晶,力学性能急剧降低。     

Postsynthesis of hierarchical core/shell ZSM-5 as an efficient catalyst in ketalation and acetalization reactions

Hierarchical core/shell Zeolite Socony Mobil-five (ZSM-5) zeolite was hydrothermally postsythesized in the solution of NaOH and diammonium surfactant via a dissolution-reassembly strategy. The silica and alumina species were firstly dissolved partially from the bulky ZSM-5 crystals and then were in situ reassembled into the MFI-type nanosheets with the structure-directing effect of diammonium surfactant, attaching to the out-surface of ZSM-5 core crystals. The mesopores thus were generated in both the core and shell part, giving rise to a micropore/mesopore composite material. The micropore volume and the acidity of the resultant hybrid were well-preserved during this in situ recrystallization process. Possessing the multiple mesopores and enlarged external surface area, the core/shell ZSM-5 zeolite exhibited higher activity in the ketalation and acetalization reactions involving bulky molecules in comparison to the pristine ZSM-5.     

680m~3浮选机工业化应用过程中的动力学性能测试与分析

680m~3浮选机投入生产试运行已一年有余,表现出卓越的设备稳定性和分选性。本文从浮选流体动力学角度出发,对680m~3浮选机在带矿运行过程中的充气性能、矿浆循环悬浮性能和气泡大小及其负载性能进行了测试分析。结果表明,680m~3浮选机充气量可以达到1.1m~3/(m~2·min)以上,能够满足一般硫化矿大气量的生产需求,空气分散度在7以上,平均气含率约7%;不同深度浮选槽内矿浆浓度和粒级分布较为均匀,无明显分层现象。气泡表面积通量可达39.20s-1,随着气泡的上浮,气泡负载呈现上升趋势,最高可达3.37g/L。优越的浮选流体动力学特性充分地保障了680m3浮选机良好的分选效果。     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.     

Generation expansion planning in electricity markets: A novel framework based on dynamic stochastic MPEC

This paper presents a novel framework for generation expansion planning (GEP) of restructured power systems under uncertainty in a multi-period horizon, which includes generation investment from a price maker perspective. The investment problem is modeled as a bi-level optimization problem. The first level problem includes decisions related to investment in order to maximize total profit in the planning horizon. The second level problem consists of maximizing social welfare where the power market is cleared. Rival uncertainties on offering and investment are modeled using sets of scenarios. The bi-level optimization problem is then converted to a dynamic stochastic MPEC and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a typical six-bus power network, MAZANDARAN regional electric company (MREC) transmission network as an area of IRAN interconnected power system and IEEE RTS 24-bus network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the behavior of investments in electricity markets.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.