Data sharing mechanism of various mineral resources based on blockchain

Basins with various mineral resources coexisting and enriching often occupy an important strategic position. The exploration of various mineral resources is repetitive at present due to unshared data and imperfect management mechanism. This situation greatly increases the cost of energy exploitation in the country. Traditional data-sharing mode has several disadvantages, such as high cost, difficulty in confirming the right of data, and lack of incentive mechanism, which make achieving real data sharing difficult. In this paper, we propose a data-sharing mechanism based on blockchain and provide implementation suggestions and technical key points. Compared with traditional data-sharing methods, the proposed data-sharing mechanism can realize data sharing, ensure data quality, and protect intellectual property. Moreover, key points in the construction are stated in the case study section to verify the feasibility of the data-sharing system based on blockchain proposed in this paper.     

A novel bio‐based phthalonitrile resin derived from catechin: synthesis and comparison of curing behavior with petroleum‐based counterpart

The development of bio‐based thermosetting resins with good thermal stability can potentially afford sustainable polymers as replacements for petroleum‐based polymers. We report a practical route to a novel catechin‐based phthalonitrile resin precursor (CA‐Ph), which contains free phenolic hydroxyl groups that result in ‘self‐curing’ at elevated temperatures to afford a thermostable polymer. Comparison of the performance of this CA‐Ph resin with that of a conventional petroleum‐based bisphenol A phthalonitrile resin (BPA‐Ph; containing 5 wt% of the curing agent 4,4′‐diaminodiphenylsulfone) revealed that CA‐Ph exhibits a lower melting point and curing temperature. Cured CA‐Ph resin retains 95% of its weight at 520 °C under a nitrogen atmosphere, which compares favorably with results obtained for BPA‐Ph resin that retains 95% of its weight at a lower temperature of 484 °C. Kinetic results indicated that the curing reactions of both CA‐Ph and BPA‐Ph systems follow an autocatalytic mechanism. These results suggest that catechin is a useful bio‐based feedstock for the preparation of self‐curing and thermally stable phthalonitrile resins for advanced technological applications. © 2017 Society of Chemical Industry     

汽车空调的操作和应用分析

2013年国内汽车产销量超过2000万台,汽车正在快速进入中国的千家万户,但大部分车主还缺乏对汽车空调知识的了解,夏天又是空调故障多发期,如果车主了解相关汽车空调知识,在实际应用中会达到事倍功半的效果,因此介绍了一般车型的空调结构、工作原理以及特殊气候下的调节。     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

深度学习识别光网络单元故障的设计与应用

为解决依赖装维上门鉴别光网络单元故障带来的不便,可以从机器视觉入手实现自动化故障识别。近年,ImageNet挑战赛的成功推动了物体识别技术的跨越式发展,特别是基于卷积的深度学习技术在视觉识别方面已经达到人类水平,为光网络单元故障的自动识别提供了技术基础。文章对识别光网络单元的工作状态进行了研究,将设备工作状态分为7个场景,提出了利用手机APP采集图片识别故障的解决方案并投入了实际生产;重点阐述了深度学习模块的设计与实现,提出一种通过算法整合的方式综合运用物体检测和图像分类算法,分3阶段逐步求精,解决了图片过滤,光网络单元型号和状态识别等问题,实现了基于计算机视觉自动识别光网络单元故障。从数据上看产品的端到端准确率超过84%,识别速度达到10 FPS,月均提供服务超过1万人次,在减少用户等待的同时节约了人力资源。     

Adaptive Finite-time Tracking Control for Class of Uncertain Nonlinearly Parameterized Systems with Input Delay

International Journal of Control, Automation and Systems - In this paper, the tracking problem for a class of uncertain nonlinearly parameterized systems with input delay based the adaptive...     

采煤机行走轮参数化分析软件设计

针对电牵引采煤机渐开线行走轮在ANSYS分析中存在的问题,提出运用APDL语言命令直接建模,并通过VB与ANSYS的交互运行途径,设计了基于VB界面和程序的软件,实现了利用VB界面直接输入参数并调用ANSYS对行走轮自动建模、加载和计算的有限元分析。验证结果表明,该软件减少了设计人员的重复劳动,提高了行走轮的设计效率和水平,具有一定的工程实用价值。     

基于关键水平的水下采油树预防性维修决策方法

为解决电液复合水下采油树在运行过程中工作环境恶劣且复杂、系统要求可靠性高、维修难度大且费用高的问题,建立基于伽马退化过程的水下采油树组件可靠度退化模型和考虑维修花费、停产损失在内的维修成本模型,建立水下采油树系统预防性维修优化目标体系,基于多目标粒子群优化算法对维修策略进行优化。建立的模型可有效描述水下采油树系统的工作特性,最优解能够满足在低维修成本的前提下系统高可靠性的工作要求。