智能冷柜视情维修系统的设计与实现

发布时间：2018-02-15 14:44

本文关键词： 智能冷柜视情维修故障树分析 FMEA 灰色预测模型　出处：《华中科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着物联网的发展和制造业的兴盛，家电类产品逐渐朝着智能化的方向发展，这对产品的维护提出了严峻的考验。采用视情维修系统，实时诊断产品工作中的故障并实现故障预测，对于提高维修效率和准确性、保证产品的可靠性、降低维护成本都具有重要的意义。本论文以中山美科冷冻类设备有限公司的智能冷柜产品为例，开发了一套基于无线射频识别（RFID）技术的视情维修系统。论文主要的研究工作如下：针对智能冷柜产品故障复杂、难以直接进行故障诊断的特点，采用故障树分析法和FMEA（故障模式与影响分析法）对智能冷柜进行分析。分别从机械、控制和电气三方面建立智能冷柜制冷功能的故障树模型，并在故障树分析的基础上，对智能冷柜各故障模式建立详细的FMEA故障表，作为故障诊断的知识库。针对智能冷柜状态参数变化趋势不确定、系统复杂、容易受工况和人为操作的影响等特点，根据冷柜产品运行过程中采集的状态数据建立智能冷柜灰色预测模型，利用MATLAB软件编程实现模型建立和预测。实验表明，采用改进的新陈代谢灰色预测模型能实现智能冷柜状态数据的预测，且模型的预测精度较高，，能预测未来时刻可能存在的潜在故障，避免严重事故的发生。根据系统的需求分析完成了智能冷柜整套视情维修系统的原型实现，并在中山美科公司生产的冷柜产品上进行了测试。测试表明，整套系统可以正常可靠的运行，智能板卡系统能实现产品状态数据的采集传输、实时故障诊断与定位，智能维护系统能实现产品全生命周期的维护管理，可以提高维修效率、降低成本。
[Abstract]:With the development of the Internet of things and the prosperity of the manufacturing industry, household appliances are gradually developing towards the direction of intelligence, which puts forward a severe test for the maintenance of the products. In order to improve the efficiency and accuracy of maintenance and ensure the reliability of the product, the real-time fault diagnosis and fault prediction are realized. It is of great significance to reduce the cost of maintenance. This paper takes the intelligent freezer products of Zhongshan Meike Refrigeration equipment Co., Ltd as an example. A view condition maintenance system based on radio frequency identification (RFID) technology is developed. The main research work of this paper is as follows:. In view of the complex faults of intelligent freezer products and the difficulty of fault diagnosis directly, fault tree analysis and FMEA (fault mode and impact analysis) are used to analyze intelligent freezers. The fault tree model of the refrigeration function of intelligent freezer is established in three aspects of control and electricity. On the basis of fault tree analysis, a detailed FMEA fault table is established for each fault mode of intelligent freezer, which is used as the knowledge base for fault diagnosis. In view of the characteristics of uncertain state parameters of intelligent freezer, complex system and easy to be affected by working condition and artificial operation, the grey prediction model of intelligent freezer is established according to the state data collected during the operation of the product. The experiment shows that the improved metabolic grey prediction model can predict the state data of the intelligent freezer, and the prediction accuracy of the model is high. Ability to predict potential future failures and avoid serious accidents. According to the requirement analysis of the system, the prototype of the whole system of the intelligent freezer maintenance system is completed, and the test is carried out on the freezer products produced by Zhongshan Meike Company. The test results show that the whole system can run normally and reliably. The intelligent card system can realize the collection and transmission of product state data, real-time fault diagnosis and location, intelligent maintenance system can realize the maintenance management of the whole product life cycle, can improve the maintenance efficiency and reduce the cost.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM925.07

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