基于云计算的设备状态维护关键技术研究

发布时间：2018-05-28 10:24

本文选题：云计算 + 设备状态维护　；参考：《西安科技大学》2017年硕士论文

【摘要】：设备维护作为提升现代化企业核心竞争力的重要因素,是企业生产效益和经济效益的重要保证,如何制定设备的维修计划以及采取何种维修行动是企业进行设备维护需要解决的关键性问题。设备运行低故障甚至零故障的期望,使得企业更加注重运用先进的检测、诊断技术保证设备的健康运行,与此同时也产生了大量的设备运行、故障等方面的信息。针对上述问题,本文将云计算技术和设备维护技术相结合,提出了基于Hadoop的设备状态维护云平台,为现代企业进行设备维护提供了一种新方法和新思路。首先,基于Hadoop技术,建立设备状态维护云平台的体系架构,对网络各层进行布局,并进一步设计设备状态维护服务层在设备维修管理方面的功能模块,根据各功能模块的作用对其进行详细论述。其次,研究以期望平均维护总费用最小为目标的设备状态维护模型,综合分析考虑设备失效率、最小修理费用和停机造成的损失等因素对模型的影响,在此基础上,提出一种基于遗传算法的决策模型优化求解方法,并进行实例验证。最后,为了提高和优化计算速度,研究基于MapReduce计算模型和遗传算法相结合的快速求解方法,提高求解效率,并开发程序和验证。通过对基于云计算的设备状态维护关键技术研究,可以有效的为设备维护行动提供决策建议,并且具有求解速度快,资源利用合理等优势,很好的满足了企业的需要也促进了设备维护技术的进步。
[Abstract]:As an important factor to enhance the core competitiveness of modern enterprises, the maintenance of equipment is an important guarantee for the production and economic benefits of enterprises. How to make maintenance plan and how to take maintenance action are the key problems to be solved. The expectation of low fault or zero fault makes the enterprise pay more attention to the application of advanced detection and diagnosis technology to ensure the healthy operation of the equipment. At the same time it also produces a lot of equipment operation fault and other aspects of information. Aiming at the above problems, this paper combines cloud computing technology with equipment maintenance technology, and puts forward a state maintenance cloud platform based on Hadoop, which provides a new method and a new idea for modern enterprises to carry out equipment maintenance. First of all, based on the Hadoop technology, the system architecture of the equipment state maintenance cloud platform is established, and the layout of each layer of the network is carried out, and the function module of the equipment state maintenance service layer in the equipment maintenance management is further designed. According to the function of each functional module, it is discussed in detail. Secondly, the paper studies the equipment state maintenance model, which aims at the minimum average total maintenance cost, and comprehensively analyzes the effects of the failure rate, the minimum repair cost and the loss caused by downtime on the model. A decision model optimization method based on genetic algorithm is proposed and verified by an example. Finally, in order to improve and optimize the calculation speed, a fast solution method based on the combination of MapReduce computing model and genetic algorithm is studied to improve the efficiency of the solution, and develop the program and verify it. Through the research on the key technology of equipment state maintenance based on cloud computing, it can effectively provide decision advice for equipment maintenance, and has the advantages of fast solution, reasonable utilization of resources and so on. Very good to meet the needs of enterprises and promote the progress of equipment maintenance technology.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP3;TP18

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