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时间:2018-07-16
《球磨机常见故障及处理方法》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、西安工业大学继续教育学院毕业(设计)论文西安工业大学继续教育学院毕业论文球磨机常见故障及处理方法院、系(站)学科专业:学生:学号:指导老师:2010年9月30日27西安工业大学继续教育学院毕业(设计)论文目录摘要··························································11绪论························································2一、背景分析···············································3(1)、故障诊断技术的发展过程以
2、及经济意义···············4(2)、对球磨机进行故障诊断的必要性·····················5二、设备机械故障概述······································6(1)、设备故障分类····································7(2)、设备27西安工业大学继续教育学院毕业(设计)论文故障原因分析································8(3)、设备故障机理分析································9(4)、设备故障的规律···············
3、··················10三、运行监测与故障诊断技术的应用与发展现状···············11(1)、国外运行监测与故障诊断技术的应用与发展现状·····12(2)、国内运行监测与故障诊断技术的应用与发展现状·····13四、球磨机运行监测与故障诊断技术的发展及应用·············14(1)、国内外研制成功的部分计算机预测维修系统·········15(2)、大型球磨机开发的故障诊断系统···················162球磨机轴承故障诊断·········································17一、27西安工业大学
4、继续教育学院毕业(设计)论文引言··················································18二、球磨机轴承故障特征····································19三、球磨机轴承监测、诊断方法·····························2027西安工业大学继续教育学院毕业(设计)论文(1)、振动诊断法···································21(2)、光纤监测技术·································22(3)、接触电阻法···········
5、························23四、小结···············································243球磨机齿轮传动系统状态检测与故障诊断·····················25一、齿轮异常的基本形式及振动特点························26(1)、齿轮异常的基本形式····························27(2)、齿轮振动及其特点······························28二、齿轮传动系统故障诊断方法····························292
6、7西安工业大学继续教育学院毕业(设计)论文(1)、振动分析法····································30(2)、频谱分析法····································31(3)、小波诊断方法··································32(4)、基于载荷识别和信息融合的齿轮传动系统诊断方法··33三、球磨机齿轮传动系统故障诊断实验······················34(1)、球磨机振动标准的确定··························35四、小结·················
7、·······························365结论·····················································37参考文献···················27西安工业大学继续教育学院毕业(设计)论文································3827西安工业大学继续教育学院毕业(设计)论文摘要现代化生产日益向着大规模化、系统化、自动化方向发展,机械故障诊断越来越受
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