动力炉控制系统故障监测和诊断系统的设计与实现

发布时间：2018-06-16 09:00

本文选题：动力炉 + 故障诊断　；参考：《电子科技大学》2012年硕士论文

【摘要】：动力炉是公司生产链中重要的一环，其主要任务是提供合格品质的蒸汽。随着科学技术的不断提高，公司生产技术也快速步入自动化，智能化。动力炉自动化发展更是迅速，其正向高集成化、高智能化方向发展，控制回路多，程序复杂，由此对故障诊断技术应用的迫切性与日俱增。本论文是动力炉故障诊断研究领域中面向对象方法和人工智能技术综合应用方向分支的深入研究，并在此基础上设计开发动力炉故障诊断与监测系统。首先在知识获取、知识表达和知识库的构建中都采用了较新的构建方式，知识库建立采用了领域深知识和经验浅知识有机结合的方式，建立了基于结构与功能的层次分解模型，并在知识表达和存储中大力采用数据库技术；其次，，本文通过对前人有关动力炉故障诊断方法模型的学习与分析，采用数据库技术、PLC控制以及面向对象的编程语言，设计以神经网络与专家知识为推理策略的控制系统，实现对动力炉故障检测、诊断及排除。
[Abstract]:Power furnace is an important link in the production chain of the company, its main task is to provide qualified quality steam. With the continuous improvement of science and technology, the company's production technology also quickly into automation, intelligent. The development of power furnace automation is more and more rapid. It is developing in the direction of high integration, high intelligence, many control loops and complex program. Therefore, the application of fault diagnosis technology is becoming more and more urgent. This paper is an in-depth study on the application of object-oriented method and artificial intelligence technology in the field of power furnace fault diagnosis. On this basis, a fault diagnosis and monitoring system for power furnace is designed and developed. First of all, a new construction method is adopted in knowledge acquisition, knowledge expression and knowledge base construction. The knowledge base is built by combining domain deep knowledge with experience shallow knowledge, and a hierarchical decomposition model based on structure and function is established. Database technology is used in knowledge expression and storage. Secondly, through the study and analysis of the previous models of power furnace fault diagnosis, the database technology is used to control PLC and object-oriented programming language. A control system based on neural network and expert knowledge is designed to detect, diagnose and eliminate power furnace faults.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH165.3

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