水泥工业智能化建设的基础与目标

就目前智能化建设的认识,给水泥行业建设方式提供参考,防止水泥用户走入智能化建设的误区,也给智能化建设供应商提供搭建思路和目标,防止过度开发和浪费。目前国内多家水泥厂进行的智能化架设,离真正的智能化还有一定的差距,要推进生产过程网络化、数字化、智能化技术改造,以及共享工厂、大规模个性化定制、行业平台化远程运维服务等新模式,促进企业数字化转型、网络化协同、智能化生产。水泥智能制造正处于起步阶段,云计算、大数据等技术将实现大规模应用。

电气自动控制工程中智能化技术的应用实践

随着我国科学技术的迅速发展,很多新技术得到开发,促进各行业的发展。在电气企业中,将智能化技术应用于自动控制的工作中,能够促进电气行业的持续发展。基于此,本篇文章先对智能化技术进行了阐述,然后对智能化技术的应用优势又进行了探究,最后对电气自动化控制工程中的智能化技术应用进行阐述,以供参考。

智能自动化技术推动石油化工企业数字化转型升级

通过分析我国石化工业在未来5~15年的发展趋势与挑战,聚焦石化企业对数字化转型升级的重大需求。剖析了当前石化企业在信息感知和集成、数据挖掘与分析、生产运行、经营决策和安全环保能效等层面存在的主要问题。首先,提出了基于新一代信息通信技术、物联网、大数据、云计算和人工智能等前沿发展技术,并结合过程自动化技术而产生的“智能自动化”新概念。其次,从工程角度出发,提出了如何利用智能自动化技术,从工程、生产、管理以及营销全过程,优化推进以集约化、高效化、绿色化和智能化为目的的石化企业数字化转型升级的愿景目标、特征和路径。第三,采用需求驱动、应用驱动、问题导向的分析思路,进一步论述了当前亟须研究解决的五大核心工程技术问题,即:①以工业大数据平台为基础的智能工程数字化交付——数字孪生工厂;②生产与运营全过程信息智能感知与集成;③生产过程全流程协同控制与操作优化;④知识驱动的生产过程计划调度优化与经营管理决策;⑤基于自主感知与融合知识的过程风险智能化管理。最后,对智能自动化技术的应用与发展趋势提出了建设性意见。

主动有源电子对抗侦察的原理与应用探析

仅被动接收、不对外辐射电磁信号是传统电子对抗侦察的重要特征,虽然隐蔽性好、生存力强,但随着电子目标向智能化方向发展,这一侦察方式的局限性日渐突出,从被动无源向主动有源转变的迫切需求应运而生。针对这一趋势,分析了主动有源电子对抗侦察的技术原理、工作过程和主要特点,从工程控制论中系统辨识的视角揭示了其重要数理基础,展现了电子对抗侦察从开环向闭环发展的演变过程。在此基础上介绍了主动有源电子对抗侦察的典型应用,并指出了其所面临的重大挑战。这不仅为主动有源电子对抗侦察的理论研究与技术开发提供了牵引,而且也为认知电子战的深化论证与示范应用提供了参考。

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

SGCC Smart Grid Standardization

This paper introduces the progress of State Grid Corporation of China （SGCC） in smart grid standardization, including the smart grid standards system, standards reversion and development, the role of standards system in smart grid demonstration projects, and the situation of SGCC participation in both domestic and international smart grid standardization work.

A multi-objective optimization framework for ill-posed inverse problems

Many image inverse problems are ill-posed for no unique solutions. Most of them have incommensurable or mixed-type objectives. In this study, a multi-objective optimization framework is introduced to model such ill-posed inverse problems. The conflicting objectives are designed according to the properties of ill-posedness and certain techniques. Multi-objective evolutionary algorithms have capability to optimize multiple objectives simultaneously and obtain a set of trade-off solutions. For that reason, we use multi-objective evolutionary algorithms to keep the trade-off between these objectives for image ill-posed problems. Two case studies of sparse reconstruction and change detection are imple- mented. In the case study of sparse reconstruction, the measurement error term and the sparsity term are optimized by multi-objective evolutionary algorithms, which aims at balancing the trade-off between enforcing sparsity and reducing measurement error. In the case study of image change detection, two conflicting objectives are constructed to keep the trade-off between robustness to noise and preserving the image details. Experimental results of the two case studies confirm the multi-objective optimization framework for ill-posed inverse problems in image processing is effective.

Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Pigeon-inspired optimization(PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspired optimization(MPIO) is proposed in this paper. It is also adopted to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors, which has two objective variables, five design variables, and five constraint variables. Furthermore, comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity and superiority of our proposed MIPO algorithm.