中央空調(diào)故障檢測研究

電氣自動化論文編號:ZD1017    論文字?jǐn)?shù):20839,頁數(shù):43

中文摘要  II
Abstract  III
1 緒 論 1
1.1  選題的背景與意義 1
1.2 空調(diào)制冷系統(tǒng)常見故障分析 2
2 中央空調(diào)故障檢測研究現(xiàn)狀及技術(shù) 4
2.1  中央空調(diào)故障檢測研究現(xiàn)狀 4
2.2 故障檢測主要技術(shù)內(nèi)容 4
2.3 故障檢測技術(shù)的幾種主要方式方法 4
3 中央空調(diào)基于神經(jīng)網(wǎng)絡(luò)的故障檢測 7
3.1  基于神經(jīng)網(wǎng)絡(luò)的方法 7
3.2 神經(jīng)網(wǎng)絡(luò)故障檢測的內(nèi)容 7
3.3  人工神經(jīng)網(wǎng)絡(luò)的基本概念 8
3.3.1 神經(jīng)網(wǎng)絡(luò)的基本特性 10
3.3.2 典型神經(jīng)網(wǎng)絡(luò)的模型 10
3.4基于神經(jīng)網(wǎng)絡(luò)的知識獲取 11
3.5 空氣處理器故障分析 11
3.6 BP神經(jīng)網(wǎng)絡(luò)的結(jié)構(gòu) 13
3.7模糊神經(jīng)網(wǎng)絡(luò)在中央空調(diào)故障檢測中的應(yīng)用 17
3.8 基本模糊神經(jīng)元 17
3.9 基于模糊神經(jīng)網(wǎng)絡(luò)故障診斷 18
3.9.1模糊邏輯理論的基本概念 18
3.9.2 隸屬函數(shù) 18
3.9.3模糊神經(jīng)網(wǎng)絡(luò)的構(gòu)造 19
3.10基于模糊神經(jīng)網(wǎng)絡(luò)的中央空調(diào)故障檢測實例 23
4 基于專家系統(tǒng)的故障檢測 25
4.1  蒸汽壓縮式循環(huán)制冷原理及應(yīng)用 25
4.2 影響壓縮機性能的因素 26
4.3故障對應(yīng)的特征參數(shù)變化及其對制冷機性能的影響 27
4.4機組運行狀態(tài)對應(yīng)的特征參數(shù)變化特征 29
4.5 專家系統(tǒng)的基本結(jié)構(gòu)及功能 31
4.6 專家系統(tǒng)的基本特征 34
4.7故障檢測軟件 35
5 總  結(jié) 37
致    謝 38
參考文獻(xiàn) 39

摘     要
 隨著科學(xué)技術(shù)的不斷發(fā)展和工業(yè)自動化水平的快速提高，工業(yè)和舒適性中央空調(diào)的應(yīng)用日趨增多，致使制冷系統(tǒng)內(nèi)部結(jié)構(gòu)越來越復(fù)雜，系統(tǒng)故障的潛在發(fā)生點增多了，這對及時發(fā)現(xiàn)和診斷系統(tǒng)的故障發(fā)生部位提出了更高的要求。傳統(tǒng)的人工診斷方式已經(jīng)不能滿足實際的要求，因此，計算機故障診斷技術(shù)逐漸成為目前研究的熱門，隨著應(yīng)用的不斷深入，其經(jīng)濟價值也逐漸得以體現(xiàn)。
 本論文通過神經(jīng)網(wǎng)絡(luò)的方法和專家系統(tǒng)的方法對空調(diào)故障診斷技術(shù)中進行了研究。
 在神經(jīng)網(wǎng)絡(luò)的方法中對模糊信息處理的神經(jīng)網(wǎng)絡(luò)方法、基本模糊神經(jīng)元和模糊神經(jīng)網(wǎng)絡(luò)模型進行了簡要的介紹。然后構(gòu)造了基于模糊神經(jīng)網(wǎng)絡(luò)的中央空調(diào)空氣處理器的故障診斷模型。該模糊神經(jīng)網(wǎng)絡(luò)共有4層，對每一層神經(jīng)元的確定做了詳細(xì)的介紹，并給出了5類故障現(xiàn)象的隸屬度函數(shù)。最后利用MATLAB對該模糊神經(jīng)網(wǎng)絡(luò)進行仿真。
 專家系統(tǒng)的方法先分析了壓縮式制冷循環(huán)的原理，分析了制冷機的工作特性，從理論上得出了冷水機組常見故障的表現(xiàn)特征。對專家系統(tǒng)結(jié)構(gòu)和特性做了介紹。然后在理論上對深淺知識的表示、獲取方式做了論述，并對知識庫的構(gòu)建和管理以及推理控制方式都做了說明。

關(guān)鍵詞：中央空調(diào)，人工神經(jīng)網(wǎng)絡(luò)，專家系統(tǒng)，故障診斷

Abstract
With the continuous development of technology and industrial automation, the using of industrial and comfortable central air-conditioning increased quickly. The refrigeration system get more and more complicated than before. As a result, the latency trouble points increased, it demands more ability in the system’s trouble shooting. At present, the trouble shooting by manual work is no longer met the actual needs. so the computer aided trouble shooting technology gets more and more pop and gets much economic value by its widely used.
 In this paper, the method through neural network and expert system approach to fault diagnosis of air-conditioning technology is studied.     In the neural network approach for fuzzy information processing in the neural network method, the basic fuzzy neurons and fuzzy neural network model for a brief introduction. And then construct a fuzzy neural network based on the central air-conditioning air processor fault diagnosis model. The fuzzy neural network a total of 4 layers of neurons in each layer to determine a detailed introduction, and given the phenomenon of category 5 fault membership function. Finally, the MATLAB simulation of fuzzy neural networks.     Expert system approach to analysis of the compression refrigeration cycle principle, an analysis of operating characteristics of the refrigerator, cold water drawn from the theoretical unit of the performance characteristics of common faults. On the structure and characteristics of expert system is introduced. And then the depth of theoretical knowledge that has been done on ways to obtain and build the knowledge base and inference control and management have done that way.
Keywords: Centralair-eondition，ANN，Expert system，F(xiàn)ailurediagnose