皮革剪板机设计说明书.doc

皮革剪板机设计【6张CAD图纸】【优秀】

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皮革剪板机设计

36页 14000字数+说明书+任务书+外文翻译+6张CAD图纸【详情如下】

下刀架.dft

下刀架.dwg

下托板.dft

下托板.dwg

任务书.doc

外文翻译--部分频谱与齿轮缺陷发现相互关系的实际应用.doc

总装配.dwg

横梁.dft

横梁.dwg

横梁固定件.dft

横梁固定件.dwg

牌坊架.dft

牌坊架.dwg

皮革剪板机设计说明书.doc

目录

摘要………………………………………………………………………………………1

1 绪论……………………………………………………………………………………3

1.1 研究的背景、目的和意义…………………………………………………………3

1.2 剪板机的分类及应用………………………………………………………………3

1.3 设计的意义…………………………………………………………………………4

1.4 剪板机设计步骤……………………………………………………………………5

2 皮革剪板机总体结构…………………………………………………………………6

2.1 皮革剪板机设计要求………………………………………………………………6

2.2 配个剪板机总体布局………………………………………………………………6

2.3 主要部件的设计……………………………………………………………………7

3 剪板机基本性能参数…………………………………………………………………10

3.1 剪切力确定…………………………………………………………………………10

3.2 压料力的确定………………………………………………………………………11

3.3 剪切角的确定………………………………………………………………………11

3.4 上刀片的行程量……………………………………………………………………12

4 剪板机机械设计………………………………………………………………………13

4.1 整体设计……………………………………………………………………………13

4.2 机架…………………………………………………………………………………15

4.3 刀架…………………………………………………………………………………16

4.4 刀具…………………………………………………………………………………18

5 液压部分设计…………………………………………………………………………20

5.1 基本方案……………………………………………………………………………20

5.2供油方式卸荷回路…………………………………………………………………21

5.3 液压系统性能的验算………………………………………………………………23

5.4 液压系统的调试……………………………………………………………………29

5.5 液压系统的维护及注意事项………………………………………………………30

6 结论……………………………………………………………………………………32

参考文献…………………………………………………………………………………33

摘  要

  本文设计了一台简易剪板机,能够实现对厚度10mm,宽度700mm行剪切,剪断时间小于10s,重点就机架、刀架等重要部件进行了设计,在设计中通过对比国内外剪板机,力求设计出结构简单,操作简便,同时经济、合理的剪板机,具体设计思路上:减少了剪切的时间并且提高了剪切精度。采用人工送料以降低成本。近年来,随着模具技术和冲压技术的发展,剪板机的应用范围在不断地扩大,数量在不断地增加。预计不久的将来,剪板机在冲压用剪板机中的比例将会愈来愈大。    

  关键词 机架; 刀架; 剪切精度

Abstract

   This text designed to the infrastructure design of guillotine shear, can carry out to shear to slice the plank material thickness 10 mm, the width 700mm, clipping time is smaller than 10 second, the point carried on a design for the parts with important etc. of the machine, knife and passed contrast to the infrastructure design of guillotine shear at home and abroad in the design and tried hard for to design structure simple, operate simple, economic in the meantime, reasonable of the infrastructure design of guillotine shear, for the put type knife formely and connect the pole type knife carried on innovation: consumedly reduced to shear to slice of time and raised to shear to slice accuracy.In recent years, along with molding tool technique and hurtle to press a technical development, the infrastructure design of guillotine shear at constantly extension, amount at constantly increment.Anticipate near future, the infrastructure design of guillotine shear at blunt press to use to shear the comparison in the infrastructure design of guillotine shearr will be bigger and bigger.    

 Keywords  Machine;Knife;hear to slice accuracy.

绪 论

研究的背景、目的和意义

      随着我国制造业的发展,剪板机床的发展越来越成为机械制造行业的中流砥柱,通用型高性能剪板机,广泛适用于航空、汽车、农机、电机、电器、仪器仪表、医疗器械、家电、皮具、五金等行业。

   锻压机械是指在锻压加工中用于成形和分离的机械设备,1842年,英国工程师史密斯创制第一台蒸汽锤,开始了蒸汽动力锻压机械的时代。1795年,英国的布拉默发明水压机,但直到19世纪中叶,由于大锻件的需要才应用于锻造。随着电动机的发明,十九世纪末出现了以电为动力的机械剪板机和空气锤,并获得迅速发展。二十世纪初,锻压机械改变了从19世纪开始的向重型和大型方向发展的趋势,转而向高速、高效、自动、精密、专用、多品种生产等方向发展。于是出现了每分种行程2000次的剪板机。所谓剪板机一般是指每分钟的行程次数为普通剪板机的5—10倍的剪板机。剪板机是带有自动送料装置,可完成板料高效率、精密加工的机械剪板机,具有自动、高速、精密三个基本要素。  

   近十多年来,随着对发展先进制造技术的重要性获得前所未有的共识,冲压成形技术无论在深度和广度上都取得了前所未有的进展,其特征是与高新技术结合,在方法和体系上开始发生很大变化。计算机技术、信息技术、现代测控技术等冲压领域的渗透与交叉融合,推动了先进冲压成形技术的形成和发展。  冷冲压生产的机械化和自动化,为了满足大量生产的需要,冲压设备已由单工位低速剪板机发 展到多工位剪板机。一般中小型冷冲件,既可在多工位剪板机上生产,也可以在剪板机上采用多工位级进模加工,是冷冲压生产达到高度自动化。      

   在汽车、航空航天、电子和家用电器领域,需要大量的金属板壳零件,特别是汽车行业要求生产规模化、车型个性化和覆盖件大型一体化。进入21 世纪,我国汽车制造业飞速发展,面对这一形势,我国的板材加工工艺及相应的冲压设备都有了长足的进步。

  1.2剪板机的分类及应用

      剪板机属于直线剪切机类,主要用于剪裁各种尺寸金属板材的直线边缘。在轧钢、汽车、飞机、船舶、拖拉机、桥梁、电器、仪表、锅炉、压力容器等各个工业部门中有广泛应用。    

   剪板机种类较多,按其工艺用途和结构类型可以分为:

1.平刃剪板机  剪切质量好,扭曲变形小,但剪切力大,耗能大。机械传动的较多。该剪板机上下两刀刃彼此平行,常用于轧钢厂热剪切初轧方坯和板坯;按其剪切方式又可分为上切式和下切式。

2.斜刃剪板机剪板机的上下两刀片成一个的角度,一般上刀片是倾斜的,其倾斜角一般为1°~6°。斜刃剪板机剪切力比平刃剪板机小,故电机功率及整机重量等大大减小,实际应用最多,剪板机厂家多生产此类剪板机。该类剪板机按刀架运动形式分闸式剪板机和摆式剪板机;按主传动系统不同分为液压传动和机械传动两类。

3.多用途剪板机:  

   (1)板料折弯剪切机:即在同一台机械上可完成剪切和折弯两种工艺。  

   (2)联合冲剪机:即可完成板材的剪切,又可对型材进行剪切,多用于下料工序。

4.专用剪板机:  

   (1)板材开平线剪板机:用于板材开卷校平线上,为配合生产线速度快剪切要求而设计的高速剪板机,厚板线上多为液压高速剪板机,薄板线上多配气动剪板机;高速线上配有飞剪机,连续生产,效率高。      

   (2)钢结构生产线剪板机:多用于角钢、H型钢自动生产线完成剪断工序。      

   (3)冷弯成型线剪板机:例如汽车纵梁冷弯线、车厢侧挡板生产线、彩钢板成型线等生产线上配置的专用剪板机等。

  1.3设计的意义和设计步骤

  毕业设计和毕业论文是本科生培养方案中的重要环节。学生通过毕业论文,综合性地运用几年内所学知识去分析、解决一个问题,在作毕业论文的过程中,所学知识得到疏理和运用,它既是一次检阅,又是一次锻炼。通过这次检验,不但可以提高学生的综合训练设计能力、科研能力(包括实际动手能力、查阅文献能力,撰写论文能力)、还是一次十分难得的提高创新能力的机会,并从下个方面得到训练:  

   1.学会进行方案的比较和可行性的论证;

   2.了解设计的一般步骤;  

   3.正确使用各种工具书和查阅各种资料;

   4.培养发现和解决实际问题的能力。

   利用所学的机械各方面的知识,我选择这个课题为我的毕业设计,进行大胆的尝试。设计中主要以课本和各种参考资料作为依据,从简单入手,循序渐进,逐步掌握设计的一般方法,把所学的知识形成一个整体,以适应以后的工作需要。当然,初次设计,知识有限,经验不足,一些问题考虑不周,也可能存在有某些错误和遗漏,恳请各位老师批评指正。  

  剪板机是各类机械产品的一种,设计时着手于其原理和主要部件的计算校核,了解剪板机的工作状态,以此为基础设计刀架、机架等各类零部件,液压部分可以采用简单的单缸液压系统,主要考虑保证液压平衡性能。

   1.3 剪板机设计步骤

  设计中一般采用三阶段法,即总体设计、部件设计和零件设计或者初步设计、技术设计与工艺设计。在实验设计与计算机辅助设计(CAD)中,多采用既分阶段又与平行兼顾的设计,以便相互协调.  

  总体设计程序为:

  1.明确设计思想

  2.分析综合要求  

  3.收集资料、对剪板机进行学习研究

  4.设计剪板机总体方案

  5.对剪板机各零件进行三维建模

  6.剪板机总体三维图,并导出工程图

  7.画出剪板机主要零件图

  8.撰写设计说明书。

2 皮革剪板机总体结构

2.1皮革剪板机设计要求  

  设计要求是进行每项工程设计的依据。在制定基本方案并进一步着手剪板机各部分设计之前,必须把设计要求以及与该设计内容有关的其他方面了解清楚。  

  1.主机的概况:用途、性能、工艺流程、作业环境、总体布局等;

  2.剪板机的工作过程及其各部件的配合形式;

    3.各动作机构的载荷大小及其性质;  

  4.对调速范围、运动平稳性、转换精度等性能方面的要求;

  5.对防尘、防爆、防寒、噪声、安全可靠性的要求;

  6.对效率、成本等方面的要求。

  2.2 皮革剪板机总体布局

     剪板机的总体布局是设计剪板机时影响全局性的决策部署。在总体布局确定后,才能确定部件之间的相对位置及运动关系,进一步具体设计剪板机。总体布局的影响是多方面的,其中,刀具的剪切轨迹是首要决定的。刀具的剪切轨迹确定后,剪板机的布局、传动、结构及外形等就可以初步决定。被加工工件的尺寸、重量和技术要求与剪板机的布局有密切关系。总体布局还需要考虑人的因素,能够满足操作要求,必须有利于减轻操作者的劳动强度,以提高工作   

参考文献

   1、刘灏   机械设计手册    北京; 机械工业出版社,2002                

   2、朱龙根    简明机械零件设计手册    北京; 机械工业出版社,2004      

   3、吴宗泽 罗圣国    机械设计课程设计手册   北京; 高等教育出版社,1992

   4、郭爱莲    新编机械工程技术手册    北京; 经济日报出版社,1991      

   5、林石     剪切机设计计算方法(一)、(二)   机械工业出版社,2003    

6、洪得纯  于志宏  祝悦红   国外锯切机的新进展   吉林; 吉林林学院1994

7、王知行  刘廷荣    机械原理   北京; 高等教育出版社,2000          

8、南京林业大学主编    木材切削原理与刀具   北京; 中国林业出版社,1997

9、庞庆海    剪板机械设备   北京; 化学工业出版社,2005              

10、孙桓  陈作模   机械原理   北京; 高等教育出版社,2001            

11、濮良贵  纪名刚    机械设计   北京; 高等教育出版社,2001          

12、王世刚  张春宜  徐起贺   机械设计实践    哈尔滨; 哈尔滨工程大学出版社,2001

13、张慧光    剪板机设计    沈阳; 沈阳锻压机床厂,1978

14、王三民  诸文俊    机械原理与设计     北京; 机械工业出版社,2000

15、姜继海   宋锦春   高常识     液压与气压传动     北京; 高等教育出版社,2000

16、李兴中  陈启松  朱福元     液压设备管理维护手册     上海; 上海科学技术出版社,1996

17、单丽云    工程材料     徐州; 中国矿业大学出版社,2000            

18、丁德全     金属工艺学      北京; 机械工业出版社, 2000          

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湘潭大学兴湘学院 毕业设计任务书论文设计题目: 皮革剪板机设计 学号:2010963123 姓名:任意飞 专业:机械设计制造及其自动化 指导教师:吴继春 系主任:签名 一、主要内容及基本要求 毕业设计的主要内容应包括文献综述、任务提出、方案论证、设计思想、设计计算或理论分析、实验结果、技术分析、结论等,并要有相应的设计图纸和设计说明书 1、学生完成的毕业设计书面材料应包括:(1)开题报告(单独装订)。(2)封面内容:湘潭大学学生毕业设计,中英文题目,所属学院,项目组成员,指导教师,专业,年级(班级),起止日期,制表日期。(3)中英文摘要:论文摘要以浓缩的形式概括研究课题的内容,具有独立性,即不阅读毕业设计报告全文即可获得其主要信息,主要说明毕业设计的内容、研究方法、成果、价值和结论,字数控制在800字以内,英文摘要应与中文摘要基本相对应。(4)中英文关键词:关键词为毕业设计报告中使用到的重要词语,各关键词中间用分号隔开,最后一个关键词后不用标点符号,关键词一般为58个。(5)中英文摘要和关键词的排列顺序为:中文摘要(标识为摘要)、中文关键词(标识为关键词)、英文摘要(标识为Abstract)、英文关键词(标识为Keywords),四部份内容独立成页,顶格排版。(6)目录:各标题及附件目录。(7)正文:毕业设计报告字数一般在1000015000字之间,毕业论文在800015000字。(8)标题:标题应层次清晰,以“1”、“2.2”、“3.2.1”等层次标注标题序号。(9)附录:对正文内容提供支撑的相关材料,如必要的数据、图表、源程序、图片等。(10)参考文献:毕业设计20篇及以上,连续编号 (11)致谢:对完成本设计(论文)提供帮助的人员表示感谢,独立成页。2、 毕业设计的书面成果使用A4或A3复印纸双面打印或复印,按以上顺序装订。3、毕业设计的书面成果正文、附录、参考文献、致谢等统一编写页顺序号。 二、重点研究的问题 1、设计皮革剪板机的机械结构,尤其对机械部分作为主要研究内容;2、确定皮革剪板机的数控加工工艺和控制系统方案;采用Solid Edge 制图软件对皮革剪板机建模 三、进度安排序号各阶段完成的内容 完成时间1查阅资料、熟悉课题、熟悉solid st4软件2013年2月末2撰写开题报告、制订设计方案2013年3月初3撰写设计计算说明书2013年3月中4画图设计分析2013年3月末5写出初稿2013年4月初6修改,写出第二稿2013年4月中7写出正式稿2013年5月8答辩2010年6月四、应收集的资料及主要参考文献1、刘灏 机械设计手册 北京; 机械工业出版社,2002 2、朱龙根 简明机械零件设计手册 北京; 机械工业出版社,2004 3、吴宗泽 罗圣国 机械设计课程设计手册 北京; 高等教育出版社,1992 4、郭爱莲 新编机械工程技术手册 北京; 经济日报出版社,1991 5、林石 剪切机设计计算方法(一)、(二) 机械工业出版社,2003 6、洪得纯 于志宏 祝悦红 国外锯切机的新进展 吉林; 吉林林学院1994 7、王知行 刘廷荣 机械原理 北京; 高等教育出版社,2000 8、南京林业大学主编 木材切削原理与刀具 北京; 中国林业出版社,1997 9、庞庆海 剪板机械设备 北京; 化学工业出版社,2005 10、孙桓 陈作模 机械原理 北京; 高等教育出版社,2001 11、濮良贵 纪名刚 机械设计 北京; 高等教育出版社,2001 12、王世刚 张春宜 徐起贺 机械设计实践 哈尔滨; 哈尔滨工程大学出版社,2001 13、张慧光 剪板机设计 沈阳; 沈阳锻压机床厂,197814、王三民 诸文俊 机械原理与设计 北京; 机械工业出版社,2000 15、姜继海 宋锦春 高常识 液压与气压传动 北京; 高等教育出版社,200016、李兴中 陈启松 朱福元 液压设备管理维护手册 上海; 上海科学技术出版社,199617、单丽云 工程材料 徐州; 中国矿业大学出版社,2000 18、丁德全 金属工艺学 北京; 机械工业出版社, 2000 湘潭大学兴湘学院毕业论文(设计)评阅表学号 2010963123 姓名 任意飞 专业 机械设计制造及其自动化 毕业论文(设计)题目: 皮革剪板机 评价项目评 价 内 容选题1.是否符合培养目标,体现学科、专业特点和教学计划的基本要求,达到综合训练的目的;2.难度、份量是否适当;3.是否与生产、科研、社会等实际相结合。能力1.是否有查阅文献、综合归纳资料的能力;2.是否有综合运用知识的能力;3.是否具备研究方案的设计能力、研究方法和手段的运用能力;4.是否具备一定的外文与计算机应用能力;5.工科是否有经济分析能力。论文(设计)质量1.立论是否正确,论述是否充分,结构是否严谨合理;实验是否正确,设计、计算、分析处理是否科学;技术用语是否准确,符号是否统一,图表图纸是否完备、整洁、正确,引文是否规范;2.文字是否通顺,有无观点提炼,综合概括能力如何;3.有无理论价值或实际应用价值,有无创新之处。综合评 价任意飞同学的毕业设计为皮革剪板机,论文选题符合培养目标要求,能体现学科专业特点,达到了综合训练的目的。该生具有较强的文献查阅、资料综合归纳整理的能力,能在设计工作中较熟练运用所学知识,毕业设计技术方案可行,工作量适当,设计思路较清晰,研究内容具有一定的实际应用价值,论文质量一般,同意参加答辩。评阅人: 2014年5月28日 湘潭大学兴湘学院 毕业论文(设计)鉴定意见 学号:2010963123 姓名:任意飞 专业 机械设计制造及其自动化 毕业设计说明书(论文) 33 页 图 表 6 张论文(设计)题目:皮革剪板机 内容提要: 本文从各个方面对剪板机进行了分析与设计,从剪板机的分类,到总体结构设计与计算,再到剪板机的基本性能参数,最后对液压系统进行了设计与计算 通过打印机接口与PC机直接连接,实现PC机直接数控。从而去掉了传统数控 设备中的工控机。 其次,分析了影响剪板机裁剪质量的因素。通过对刀具的选着设计,剪切力, 及刀具运动行程的计算,确定刀具的选择与剪切方式。从总体上,尽量使结构 简单,剪切更精确。指导教师评语 任意飞同学的毕业设计题目是皮革剪板机,设计原理基本正确,结构设计合理,图纸完成质量一般。毕业设计说明书条理较清楚、计算基本正确,文字基本流畅。整个毕业设计工作量适当。同意其参加答辩,建议成绩评定为中等。指导教师: 2014年5月28日 答辩简要情况及评语 根据答辩情况,答辩小组同意其成绩评定为中。答辩小组组长: 2014年 5 月 28 日答辩委员会意见经答辩委员会讨论,同意该毕业论文(设计)成绩评定为答辩委员会主任: 2014年5月28日附录一 英文参考文献Application of slice spectral correlation density to gear defect detectionG Bi, J Chen, F C Zhou, and J He The State Key Laboratory of Vibration, Sound, and Noise,Shanghai Jiaotong University, Shanghai,Peoples Republic of China The manuscript was received on 16 October 2005 and was accepted after revision for publication on 3 May 2006.DOI: 10.1243/0954406JMES206 Abstract: The most direct reflection of gear defect is the change in the amplitude and phase modulations of vibration. The slice spectral correlation density (SSCD)method presented in this paper can be used to extract modulation information from the gear vibration signal; amplitude and phase modulation information can be extracted either individually or in combination. This method can detect slight defects with comparatively evident phase modulation as well as serious defects with strong amplitude modulation. Experimental vibration signals presenting gear defects of different levels of severity verify to its character identification capability and indicate that the SSCD is an effective method, especially to detect defects at an early stage of development. Keywords: slice spectral correlation density, gear, defect detection, modulation 1 INTRODUCTION A gear vibration signal is a typical periodic modulation signal. Modulation phenomena are more serious with the deterioration of gear defects. Accordingly, the modulation sidebands in the spectrum get incremented in number and amplitude.Therefore, extracting modulation information from these sidebands is the direct way to detect gear defects. A conventional envelope technique is one of the methods for this purpose. It is sensitive to modulation phenomena in amplitude, but not in phase. A slight gear defect often produces little change in vibration amplitude, but it is always accompanied by evident phasemodulation. Employing the envelope technique for an incipient slight defect does not produce satisfactory results. In recent years, the theory of cyclic statistics has been used for rotating machine vibration signal and shows good potential for use in condition monitoring and diagnosis 13. In this article, spectral correlation density (SCD) function in the second-order cyclostationarity is verified to be a redundant information provider for gear defect detection. It simultaneously exhibits amplitude and phase modulation during gear vibration, which is especially valuable for detecting slight defects and monitoring their evolution.The SCD function maps signals into a two-dimensional function in a cyclic frequency (CF) versus general frequency plane (af). Considering its information redundancy 4 and huge computation,the slice of the SCD where CF equals the shaft rotation frequency is individually computed for defect detection,which is named slice spectral correlation density (SSCD). The SSCD is demonstrated to possess the same identification capability as the SCD function. It can be computed directly from a time-varying autocorrelation with less computation and, at the same time, has clear representation when compared with a three-dimensional form of the SCD. 2 SECOND-ORDER CYCLIC STATISTICS A random process generally has a time-varying autocorrelation5Where is the mathematic expectation operator and t is the time lag. If the autocorrelation is periodic with a period T0, the ensemble average can be estimated with time averageThe autocorrelation can also be written in the Fourier series because of its periodicityWhereCombining with equation(2), its Fourier coefficients can be given as 5Where is the time averaging operation, is referred to as the cyclic autocorrelation (CA),and a is the CF. SCD can be obtained by applying Fourier transform of the CA with respect to the time lag tThe SCD exhibits the characteristics of the signal in af bi-frequency plane. All non-zero CFs characterize the cyclostationary (CS) characters of the signal. 3 THE GEAR MODEL The most important component in gearbox vibration is the tooth meshing vibration, which is due to the deviations from the ideal tooth profile. Sources of such deviations are the tooth deformation under load or original profile errors made in the machining process. Generally, modulation phenomena occur when a local defect goes through the mesh and generates periodic alteration to the tooth meshing vibration in amplitude and phase. To a normal gear, the fluctuation in the shaft rotation frequency and the load or the tiny difference in the teeth space also permits slight amplitude modulation(AM) or phase modulation (PM). Therefore, the general gear model can be written as 6, 7where fx is the tooth meshing frequency and fs is the shaft rotation frequency. am(t) and bm(t) denote AM and PM functions, respectively. The predominant component of the modulation stems from the shaft rotation frequency and its harmonics; other minute modulation components can be neglected.AM and PM, either individually or in combination,cause the presence of sidebands within the spectrum of the signal. Band-pass filtering around one of the harmonics of the tooth meshing frequency is the classical signal processing for the detailed observation of the sidebands. The filtered gear vibration signal can be expressed as followswhere fh denotes one of the harmonics of the tooth meshing frequency. The subscript m is ignored for simplification in this equation and in the following discussion. The study emphasis of this paper is the filtered gear vibration signal model in equation (7),and its carrier is a single cosine waveform and modulated parts are period functions. 4 CS ANALYSIS OF THE GEAR MODEL According to the analysis mentioned earlier, the gear vibration signal can be simplified as a periodic signal modulated in amplitude and phase. The modulation condition reflects the severity extent of potential defect in gear. In this section, AM and PM cases are studied individually, and the CS analysis of the gear model is developed on the basis of their results. 4.1 AM case The model of AM signal is derived from equation (7)The analytic form of x(t) in equation (8) can be written asSubstitution of x(t) into equation (4) can deduce the CA of x(t)Where is the envelope of is equal to as a provider of modulation information.It is the Fourier transform of according to equation (11). In addition, the Fourier transform of with respect to the time lag is the corresponding SCD .thus can be computed using twice Fourier transform of with respect to time t and time lag t,respectivelyAccording to integral transform, becomeswhere H(v) is the Fourier transform of a(t)After substituting H(v) into equation (13) and uncoupling f and a using the properties of d function, the final expression of an be obtainedhas a totally symmetrical structure in four quadrants. Equation (15) is just a part of it in the first quadrant, and others are ignored for simplification. According to equation (15), is composed of some discrete peaks. In addition, these peaks regularly distribute on the af plane. Despite the comparatively complex expression, the geometrical description of is simple. These peaks nicely superpose the intersections of the cluster of lines. Then, these lines can also be considered as the character lines of .4.2 PM case PM signal derived from equation (7) isThe CA of its analytic form can be represented asThe CA in the PM case also has the envelopecarrier form, as in the AM case. Therefore, the envelope of the CA is used to extract modulation information from the signal. Its corresponding SCD is also denoted as .The PM part, b(t), comprises finite Fourier series.The CS analysis of the PM case starts with the sinusoidal waveform .Bessel formulais employed in the computation. The final result of this simple case can be expressed asThe geometrical expression of equation (18) is also related to lines,and is nonzero only at their intersections. The number of the lines does not depend on the number of harmonics in the modulation part, but is infinite in theory even for a single sinusoidal PM signal. In fact, Bessel coefficients limit discrete peaks in a range centring around the zero point of af. The amplitude of other theoretical character peaks out of the range is close to zero with the distance far away from the zero point.When the PM function comprises several sinusoidal waveforms as shown in equation (16), components of it can be expressed as bi(t), where i is Application of SSCD to gear defect detection 1387 from 0 to I. The envelope of CA can be written asWhere equals unity. According to the two-dimensional convolution principle, the corresponding SCD ofcan be represented bywhere the sign means the two-dimensional convolution on the bi-frequency plane. The expression of is shown in equation (18) with fs replaced byifs and B by Bi and b by bi. Despite more complex expression of the SCD in the multiple sinusoidal modulation case, the result of the two-dimensional convolution between has the same geometrical distribution, as it does in the single sinusoidal modulation case. The distance between the character lines of along the general frequency axis is the fundamental frequency fs. Therefore, convolution does not create new character peaks, but changes their amplitude. Equation (18) also represents the SCD of the signal in equation (16), although the coefficients Cln are changed by the two-dimensional convolution. 4.3 CS analysis of the gear vibration signal The second-order CS analysis of the general gear model in equation (7) is developed on the basis of the AM and PM cases. The CA of the analytic signal also has the envelopecarrier form, and the envelope of the CA is expressed as followsTwo parts in the sign . in equation (21) are relatedto AM and PM functions, respectively. Therefore, the corresponding SCD of has the form of two dimensional convolution of two components issued from AM and PM functionsThe expressions of and are given in equations (15) and (18). The two-dimensional convolution between and just causes the superposition of the character peaks in and , as it does in the PM case. Owing to the same geometrical characters, the convolution can not change the distribution, but involves change in the number and amplitude of the effective character peaks (whose amplitude is larger than zero). Therefore,the CS characters of the gear model are also represented by lines , as it does in the AM and PM cases. 4.4 SSCD analysis of the gear vibration signal and its realization Three modulation cases have a uniform CS character, according to the above analysis. Lines f = on the bi-frequency plane are their common character lines.Figure 1 shows its distribution.Only the part in the first quadrant is displayed because of the identical symmetry of in four quadrants. The number of these discrete points and the amplitude of the spectrum peaks reflect the modulation extent of the signal.The SCD provides redundant information for gear modulation information identification. In fact, some slices of it are sufficient for the purpose. For the AM case, the slice of , where CF is (in the first quadrant), can be derived from equation (15)The slice contains equidistant character frequencies,and the distance between them is fs. The PM case and the combination modulation case have the similar result, which can also be expressed by equation (23), whereas the coefficients Cl have different expressions. Therefore, , where is composed of discrete peaks All these character spectrum peaks correspond toodd multiples of the half shaft rotation frequency.The number and amplitude of the peaks reflect the modulation extent, thereby reflecting the severity extent of the potential defect in the gear.Similar situations will be encountered when analysing other Fig. 1Diagram of CS character distribution slices of the SCD where CF equals the integer multiples of the shaft rotation frequency.The information redundancy of the SCD function always becomes an obstacle to its practical application in the gear defect detection. The sampling frequency must be high enough to satisfy the sampling theorem. Simultaneously, identifying modulation character relies on the fine frequency resolution.Long data series are needed because of these two factors.Therefore, huge matrix operations bring heavy burden to the computation.Moreover, sometimes it is hard to find a clear representation for the redundant information in the three-dimensional space.Therefore, the SSCD, as shown in the above analysis,is presented as a competent substitute for the SCD in detecting gear defects. In this article, the SSCD is specialized to the slice of the SCD where CF equals a certain character frequency. The SSCD can be acquired directly from the time-varying autocorrelation without computing the CA matrix and other subsequent matrix operations. Its realization is detailed as follows: (a) use the Hilbert transform to get the analytic signal x(t); (b) compute the time-varying autocorrelation of the analytic signal as described in equation (2); (c) select the CF a0, which equals a certain prescient character frequency, and then compute the slice of the CA (a0 equals fs for gear defect detection); (d) compute the envelope of the slice CA . It cannot be attained directly from the slice CA,therefore, a technique is involved for another form of Utilizing the equation, arrive at the squared modulus of ; (e) apply the Fourier transform of with respect to the time lag t and obtain the final result of the SSCD.The SSCD can be computed according to the steps listed above. Nevertheless, the manipulation of replacing the envelope slice CA by the squared modulus of it will change the spectrumstructure. Original half character frequencies are converted into integer form (lfs) together with the appearance of some inessential high frequency components.These changes do not impact the character identification capability of the SSCD, on the contrary,it gives more obvious representation. 5 SIMULATION Two modulated signals are used to identify the capability of the SCD and the SSCD in modulation character identification. All modulation functions of these signals are finite Fourier series. Figure 2 shows the AM case simulated according to equation(8). The AM function a(t) comprises three cosine waveforms, representing 10 Hz and its double and triple harmonics and amplitude of 1, 0.7, and 0.3 units, respectively. All initial phases in the model are randomly decided by the computer. The carrier frequency is 100 Hz, sampling frequency 2048 Hz,and the data length 16 384. Figure 3 shows the case of the combination of AM and PM simulated according to equation (7). The PM function b(t) comprises two sinusoidal waveforms with the frequency of 10 and 20 Hz and amplitude of 3 and 1 units,respectively. Other parameters are identical to the AM case.Figures 2(a) to (c) show the time waveform, the contour of its SCD analysis, and the SSCD where CF is equal to 10 Hz, respectively. Only the results of the SCD in the first quadrant are given because of its symmetry. All character points in the contour of the SCD are at the intersections of the lines f =. Their distribution is regular in the AM case. TheFig. 2 One simulated AM signal: (a) the time waveform, (b) the contour of its SCD, and (c) the SSCD at 10 HzSSCD in Fig. 2(c) comprises Fig. 2 One simulated AM signal: (a) the time waveform, (b) the contour of its SCD, and (c)the SSCD at 10 Hzand its integer multiples and reflects themodulation condition in this signal as the SCD. Fig. 3 Another simulated modulated signal with modulation phenomena in amplitude and phase: (a) the time waveform, (b) the contour of its SCD, and (c) the SSCD at 10 Hz Figure 3 shows the case of the combination of AM and PM.All character points in the contour of the SCD are also at the intersections of the character lines 10 Hz. In addition, the SSCD also comprises 10 Hz and its several integer multiples.When PM is involved, the results from the PM part interact with those from the AM part by the two dimensional convolution. The number of the character peaks manifestly increases when compared with the original AM case in the contour of the SCD. The number of character peaks in the SSCD also augments.Therefore, according to the SCD or the SSCD, the same conclusion can be drawn: the second simulated signal is strongly modulated when compared with the first.Simulation results indicate that either the SCD or the SSCD has the capability of identifying the present and the extent of the modulation, disregarding its existence in amplitude or phase. The SSCD possesses the virtues of less computation and clear representation.These two factors seem to be indifferent for simulated signals, but are valuable when encountering very long data series in practice. 6 EXPERIMENTAL RESULTS Three experimental vibration signals employed in this section came from 37/41 helical gears. They represented healthy, slight wear (wear on addendum of one tooth of 41 teeth gear), and moderate wear status (wear on addendum of one tooth profile of 41 teeth gear and two successive tooth profiles of 37 teeth gear), respectively. The shaft rotation frequency of the 37 teeth gear minutely fluctuates 16.6 Hz. Signals were sampled at 15 400 Hz under the same load. The data length was 37 888. Before the SSCD analysis, all experimental signals were band-pass filtered around four-fold harmonics of the tooth meshin frequency in order to identify the change in themodulation sidebands in different defect status.These filtered signals are analysed by a conventional envelope technique and the SSCD. The comparison between their results dedicates the effect of theSSCD.Figure 4 shows the case of the healthy status.Figures 4(a) to (c) are the time waveform of the experimental signal, its envelope spectrum, and its SSCD analysis at the shaft rotation frequency of the 37 teeth gear, respectively. The envelope spectrum and the SSCD have the similar spectrum structure Fig. 3 Another simulated modulated signal with modulation phenomena in amplitude and phase: (a) the time waveform, (b) the contourof its SCD, and (c) the SSCD at 10 HFig. 4 First experimental gear signal: (a) the time waveform, (b) the envelope spectrum, and (c)the SSCDcomprising the rotation frequency and several negligible harmonics. Demodulated sidebands in these two spectra are few and low because there are some modulation phenomena during the gears normal operation. The fluctuation in the load, the minute rotational variation, and the circular pitch error in the machining process are the possible sources of the slight modulation. There is no comparability between numeric values of the envelope spectrum and the SSCD because of different computing procedures. The slight wear case is shown in Fig. 5. Wear on one tooth profile of one of the helical meshing gears does not result in significant deviation from its normal running. Therefore, there is a little increment in amplitude in the time waveform plot. In the envelope spectrum, compared with the normal case, the amplitude of these demodulated sidebands augments a little, and the extent seems to enlarge. The increment in number and amplitude of the sidebands is attributed to the modulation condition of the signal. However, the alteration is too slight to provide enough proof for the existence of some defect in the gear. In fact, a slight defect evidently always modulates the phase of the gear vibration signal and produces little change in the amplitude.Therefore, the envelope spectrum is not sensitiveto a slight gear defect due to its fail to the PMphenomena.Figure 5(c) shows the SSCD analysis of the slightlywearing gear. More sidebands are demodulated by the SSCD when compared with the normal case in Fig. 4(c). Moreover, the amplitude isapproximately tenFig. 5 Second experimental gear signal: (a) the time waveform, (b) the envelope spectrum, and (c)the SSCDtimes that of the normal case. Changes between the status of these two operations in the SSCD are so remarkable that a conclusion of the existence of a certain gear defect can be affirmed. Different from the neglect of envelope spectrum to PM, the SSCD treats AM and PM equally. It picks up AM and PM characters simultaneously, that is to say,the SSCD is a whole embodiment of all modulation phenomena in the system. Therefore, this is an effective and reliable method for slight gear defects.The moderate wear case is shown in Fig. 6. Wear on one tooth profile of one of the meshing gears and two neighbouring tooth profiles of the other impact the running of the meshing gears. According to the time waveform, the vibration is more violent than the two cases mentioned eaerlier. In the Fig. 5 Second experimental gear signal: (a) the time waveform, (b) the envelope spectrum, and (c)the SSCDFig. 6 Third experimental gear signal: (a) the time waveform, (b) the envelope spectrum, and (c)the SSCDApplication of SSCD to gear defect detection 1391 envelope spectrum, the amplitude and the number of the sidebands continue to increase. The obvious changes, compared with the normal case, indicate the abnormality of the system. The sidebands demodulated by the SSCD also increase in amplitude and number. The SSCD is indicative of more serious defects, whereas AM phenomena are the major reflection of the moderate wear. Therefore, the envelope spectrum and the SSCD both reflect the severity extent of the modulation in the signal. Both fit to the detection of moderate gear defects. 7 CONCLUSION Gear vibration signal is a typical modulated signal.The changes of the modulation condition indicate the existence and the development of defects. The SSCD is introduced in this article as a valuable method to detect gear defects. It is verified to be a whole reflection of the modulation phenomena in gear vibration and is able to pick up AM and PM information simultaneously. Experimental results show the defect detection capability of the method not only for moderate gear defects, but also for slight defects. Therefore, the SSCD method has a bright future in identifying the presence of gear defects and monitoring their evolution. ACKNOWLEDGEMENTS This research was supported by the National Natural Science Foundation of China (no. 50175068) and the Key Project of the National Natural Science Foundation of China (no. 50335030). Experimental data came from the Department of Applied Mechanics of University Libre de Bruxelles. REFERENCES 1 Dalpiaz,G. and Rivola, A. Effectiveness and sensitivity of vibration processing techniques for local fault detection in gears. Mech. Syst. Signal Process., 2000, 14(3), 387412. 2 Capdessus, C. and Sidahmed, M. Cyclostationary processes:application in gear faults early diagnosis. Mech.Syst. Signal Process., 2000, 14(3), 371385. 3 Antoni, J. and Daniere, J. Cyclostationary modeling of rotating machine vibration signals. Mech. Syst. Signal Process., 2004, 11(18), 12851314. 4 Gardner, W. A. Exploitation of spectral redundancy in cyclostationary signals. IEEE Signal Process. Mag., 1991,8, 1426. 5 Gardner, W. A. Introduction to random processing with applications to signals and systems, 1990 (McGraw-Hill, New York). 6 McFadden, P. D. and Smith, J. D. A signal processing technique for detecting local defects in a gear from the signal average of the vibration. Proc. Instn Mech. Engrs,Part C: J. Mechanical Engineering Science, 1985, 199(C4), 287292. 7 Randall, R. B. A new method of modeling gear faults. J. Mech. Des., 1982, 104, 259267. 附录二 英文文献翻译部分频谱与齿轮缺陷发现相互关系的实际应用G Bi, J Chen、 F C Zhou 和 J He 中华人民共和国,上海,上海交通大学,国家震动、声音和噪音重点实验室 原稿于2005年10月16日完成,经修改后于2006年5月3日发表 DOI:10.1243|0954406 JMES206 摘要:振幅和振动调制相位的变化能最直接的反映出齿轮的缺陷。部分频谱密度关系 (SSCD)方法在本文中被用来从齿轮震动信号中提取调制数据;振幅和调制阶段数据能个别地或在组合中被提取。 这一个方法能用比较仪明显的发现调制相位的细微的缺陷和通过放大的调制振幅发现严重的缺陷。实验不同严苛的等级下当前齿轮缺陷的振动信号,证实了它的特性,鉴别能力,表明了SSCD是一种有效的方法,特别是在发展早期发现缺陷。 关键字:部分频谱密度相互关系,齿轮,发现缺点,调制 1介绍 齿轮震动信号是一个典型的周期调制信号。调制现象随着齿轮缺陷的恶化更加严重。因此,调制在光谱中的边频带中的数量和振幅会增加。因此从边频带中提取调制信号是最直接发现齿轮缺陷的方法。传统的包络技术是实现这个意图方法中的一种。它对振幅中的调制现象很灵敏,但是不是在相位中。微小的齿轮缺陷经常导致振动振幅的小的变化,但是它也经常同时伴随着明显的相位调制。开始的微小缺陷使用包络技术不能产生满意的结果。 近年来,循环统计理论被用在旋转机器振动信号,并且在控制条件和诊断结论13上表现出了好的潜力。在本文中,波谱密度关系(SCD)在二阶循环平稳度分析法中的功能对齿轮缺陷的发现被证实是一个多余的信息提供者。它在齿轮震动中同时显示出振幅和调制相位,对于检测微小的缺陷和监视它们的演变尤其有价值。SCD系统将绘制的信号发送到循环频率(CF)对一般频率(-f)的二维功能中。考虑到其信息冗余 4 和巨大的计算,SCD部分在缺陷发现时循环频率即轴旋转频率是独立的计算,叫做部分频谱密度关系 (SSCD)。SSCD结果显示,它和SCD号功能拥有相同的鉴定能力。它可以用很少的计算从时间自变量直接计算,并在同一时间,与SCD的三维形式明确对比。 2二阶循环统计 一个随机过程一般有一个时间自变量 5 其中E ( . )是数学期望函数,T是时间差。如果自变量是以T0为周期的周期变量,那整体平均值约即时间平均值。自变量因为它的定期性也可以写成傅立叶函数。 结合等式2,它的傅立叶系数给5。t是平均运行时间,R(t)被称为循环变量(CA),是循环频率。SCD能够由循环变量里傅立叶积数的变换和时间差t得到。SCD在一般频率双频率间展示出信号的特性。所有非零循环频率是以周期平稳信号(CS)的特征为特征的。 3齿轮模型 变速箱振动中最重要的组成元件是齿啮合振动,这是因为偏离了理想的齿形。这种偏离的来源是齿加工过程中负载或原始配置错误下的变形。一般来说,调制现象发生在局部缺陷通过啮合并产生周期性的变化使齿啮合在振幅和相位发生振动。正常齿轮,波动轴旋转频率和负载或微小差异的牙齿空间还允许轻微调幅(AM)或相位调制(PM) 。因此,一般齿轮模型可写为 6 , 7 Fx是齿啮合频率和Fs是轴旋转频率。 am ( t )和bm(t)分别表示调幅和相位。 主要调制部分源于轴旋转频率及其谐波;其他分钟调制部分可以忽略不计。AM和PM,无论是单独或合并,都会导致信号光谱边频带的出现。带通滤波周围之一谐波的齿啮合频率是传统的信号处理,用来提供对边频带的详细观察。齿轮振动的过滤信号可表示如下:Fh是指齿啮合频率的谐波之一。下标m是为简化该方程和下面讨论时被忽略。这项研究的重点是本文过滤齿轮振动信号模型的方程( 7 ) ,它的传输是一个单一的余弦波形和调制部分是阶段功能。 4 齿轮模型的周期平稳信号(CS)系统 根据之前的分析,齿轮振动信号能够在调整振幅和相位后被简化成一个周期信号。调制条件反映了齿轮潜在的严重的缺陷。在本节,调幅(AM)或相位调制(PM)将独立学习,齿轮模型的周期平稳信号(CS)系统在它们结果的基础上发展。 4.1调幅(AM) 该模型的调幅信号来自方程式( 7 )等式(8)中的x(t)的解析式可以写为将替换进等式(4)能够推出循环变量(CA)是包络值是提供调制数据。它是通过等式(11)的傅立叶变换,另外, 的傅立叶变换时间差与SCD的相一致。于是 能够用两次傅立叶变换 的时间t和时间差计算得到。通过整体变换变成H(v)是a(t)的傅立叶变换在H(v)替换进等式(13)后解开f,用函数的值,最后表达式 就能得到有四个完全对称的结构。等式(15)只是其中的一个象限,其他的简化忽略不 计。通过等式(15), 是一连串不连贯的波峰,另外,这些波峰规律的分配在 af 平面。尽管表达比较复杂,但是的几何描述是简单的。这些波峰重叠交叉成组和线。这些线也可以被认为是的线性特征。 4.2 相位调制(PM) 相位调制信号由等式(7)得到CA分析可以表示成CA在PM中也有像AM中的包络传输。因此,CA包络被用来从信号中提取调制数据。它和SCD一样也用表示。PM部分,b(t),由连续的傅立叶函数构成。PM中的CS分析从正弦曲线波形开始,贝塞尔公式在计算中使用。最终结果可以表示为等式(18)的几何表达也可以表达成,只在它们的交叉处非零。这 些式子的值不只靠调制部分的谐波值,在无限理论上甚至为PM 信号的一正弦曲线 。事实上,贝塞尔系数在 af 的零点的周围限定了分离波峰。其他理论上的振幅波峰特征距离离零点远,超出了范围接近零。 PM功能包括像等式(16)中的一些正弦曲线波形,它的组成可以表达成,i是从 0到I,CA包络可以写成等式统一。通过二维卷积原则,相应SCD的可表达为符号表示双频率平面的二维卷积。的表达在等式(18)中用取代,用B表示Bi,b取代bi。尽管SCD在多重正弦曲线调制情形中表达更加复杂,中的二维 卷积结果有相同的几何分配,正如它在单一正弦曲线的情形。线性特征和一般频率轴之间的距离是基本的频率Fs。因此,卷积不能得出新的 波峰特征,但是改变了它们的振幅,方程式(18)也在方程式(16)中表达了SCD信号,尽管系数被二维卷积改变。 4.3 齿轮振动信号的CS分析 二位普通齿模型轮CS分析在等式
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