往复式压缩机状态综合监控系统的研究
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摘要
往复式压缩机是工业生产的关键设备,广泛应用于石油、化工、机械、冶金、食品等工业生产领域,由于它的工业环境恶劣,结构复杂,激励源众多,压缩机在运行过程中往往发生很多未知的故障,不但给压缩机的监测和控制带来了很大的困难,而且给工业生产造成重大的经济损失。为此,压缩机在线工况监测和故障诊断成为国内外专家研究的热点课题。
论文首先介绍了往复式压缩机的分类、组成、特点以及工作原理,并对压缩机的理论工作循环和实际工作循环做了分析和比较,为后续示功图的绘制奠定了理论基础。其次,分析往复式压缩机的常见故障类型以及它们的表现形式,找到合适的监测方法,确定了能够全面表征压缩机工作状态和故障信息的检测量,针对往复式压缩机的振动信号的处理难点,采用时域、频域分析方法以及小波变换方法对检测信号进行处理。本文借鉴专家对往复式压缩机故障诊断的知识和经验,提出了压缩机故障诊断专家系统设计思路。在知识的获取上,采用了故障树的分析方法,并在压缩机故障树分析的基础上,通过产生式表示法构建了往复式压缩机故障诊断专家系统的知识库。最后,综合应用了计算机技术、检测技术、电子技术等技术,设计并研制了往复式压缩机状态综合监控系统,开发了基于组态软件的系统监控软件,给出了示功图的推算和绘制方法,实现了对往复式压缩机运行状态的监控和常见故障诊断。
监控系统经实际运行表明,本系统实现了对往复式压缩机工作状态的实时监控和故障诊断,为进一步研究往复式压缩机在线状态监控及故障诊断系统提供了理论依据,积累了实际经验,具有一定的参考价值。
Reciprocating compressor is the industrial production key equipment, widely applies in industrial production domains and so on petroleum, chemical industry, machinery, metallurgy, food.Its working conditions are highly poor,a great many stimulating sources are exit in the compressor,and the structure of reciprocating compressor is quite complex, thus,the compressor often breaks down unknown in the movement process, not only has brought the very major difficulty for compressor's monitor and the control, moreover creates the heavy economic loss for the industrial production. Therefore, the compressor online operating mode monitor and the failure diagnosis into domestic and foreign experts study hot spot topic.
First of all,the thesis introduced the reciprocating compressor classification,the composition,the characteristic as well as the principle of work,and has made the analysis and the comparison to compressor's theory operating cycle and the practical work circulation,has laid the rational for the following indicating diagram.Secondly,the paper analyzed the reciprocating compressor common breakdown type as well as their manifestation,found the appropriate monitoring method, had determined can attribute the compressor active status and the breakdown information examination quantity comprehensively.In view of the reciprocating compressor vibration signal processing difficulty,uses the time domain,the frequency range analysis method as well as the wavelet transform method carries on processing to the detection signal.Then,this article profits from the expert to the reciprocating compressor failure diagnosis knowledge and the experience,proposed the compressor failure diagnosis expert system design mentality.In the knowledge gain,has used fault tree's analysis method,and in the compressor fault tree analysis's foundation,has constructed through the production rules reciprocating compressor failure diagnosis expert system's knowledge library.Finally, the comprehensive application of computer technology, examination technology, electronic technology, designed and developed the reciprocating compressor condition integrated monitor and control system, has developed based on the configuration software's system monitoring software, has given P-V indicating diagram calculation and the plan method, the realization of reciprocating compressors running status monitoring and fault diagnosis.
The supervisory system indicated after the actual movement that this system has realized to the reciprocating compressor active status real-time monitoring and the failure diagnosis, to further study the reciprocating compressor on-line state monitoring and the failure diagnosis system has provided the theory basis, gained in the practical experience, had certain reference value.
论文首先介绍了往复式压缩机的分类、组成、特点以及工作原理,并对压缩机的理论工作循环和实际工作循环做了分析和比较,为后续示功图的绘制奠定了理论基础。其次,分析往复式压缩机的常见故障类型以及它们的表现形式,找到合适的监测方法,确定了能够全面表征压缩机工作状态和故障信息的检测量,针对往复式压缩机的振动信号的处理难点,采用时域、频域分析方法以及小波变换方法对检测信号进行处理。本文借鉴专家对往复式压缩机故障诊断的知识和经验,提出了压缩机故障诊断专家系统设计思路。在知识的获取上,采用了故障树的分析方法,并在压缩机故障树分析的基础上,通过产生式表示法构建了往复式压缩机故障诊断专家系统的知识库。最后,综合应用了计算机技术、检测技术、电子技术等技术,设计并研制了往复式压缩机状态综合监控系统,开发了基于组态软件的系统监控软件,给出了示功图的推算和绘制方法,实现了对往复式压缩机运行状态的监控和常见故障诊断。
监控系统经实际运行表明,本系统实现了对往复式压缩机工作状态的实时监控和故障诊断,为进一步研究往复式压缩机在线状态监控及故障诊断系统提供了理论依据,积累了实际经验,具有一定的参考价值。
Reciprocating compressor is the industrial production key equipment, widely applies in industrial production domains and so on petroleum, chemical industry, machinery, metallurgy, food.Its working conditions are highly poor,a great many stimulating sources are exit in the compressor,and the structure of reciprocating compressor is quite complex, thus,the compressor often breaks down unknown in the movement process, not only has brought the very major difficulty for compressor's monitor and the control, moreover creates the heavy economic loss for the industrial production. Therefore, the compressor online operating mode monitor and the failure diagnosis into domestic and foreign experts study hot spot topic.
First of all,the thesis introduced the reciprocating compressor classification,the composition,the characteristic as well as the principle of work,and has made the analysis and the comparison to compressor's theory operating cycle and the practical work circulation,has laid the rational for the following indicating diagram.Secondly,the paper analyzed the reciprocating compressor common breakdown type as well as their manifestation,found the appropriate monitoring method, had determined can attribute the compressor active status and the breakdown information examination quantity comprehensively.In view of the reciprocating compressor vibration signal processing difficulty,uses the time domain,the frequency range analysis method as well as the wavelet transform method carries on processing to the detection signal.Then,this article profits from the expert to the reciprocating compressor failure diagnosis knowledge and the experience,proposed the compressor failure diagnosis expert system design mentality.In the knowledge gain,has used fault tree's analysis method,and in the compressor fault tree analysis's foundation,has constructed through the production rules reciprocating compressor failure diagnosis expert system's knowledge library.Finally, the comprehensive application of computer technology, examination technology, electronic technology, designed and developed the reciprocating compressor condition integrated monitor and control system, has developed based on the configuration software's system monitoring software, has given P-V indicating diagram calculation and the plan method, the realization of reciprocating compressors running status monitoring and fault diagnosis.
The supervisory system indicated after the actual movement that this system has realized to the reciprocating compressor active status real-time monitoring and the failure diagnosis, to further study the reciprocating compressor on-line state monitoring and the failure diagnosis system has provided the theory basis, gained in the practical experience, had certain reference value.
引文
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[2]刘卫华.涡旋式、滚动活塞式、往复式压缩机比较.家用电器科技,1996, (6)：2-4
[3]王勇等.世界石化工业100起特大财产毁损事件.石油规划设计,1994,(1)：57-59
[4]翁新华,杨汝清,王春香.一种基于工控机-PLC的动态建筑实时监控系统.机床与液压,2003,(3)：74-77
[5]盛兆顺,尹琦岭.设备状态监测与故障诊断技术及应用.北京：化学工业出版社,2002
[6]刘卫华,郁永章.往复压缩机故障诊断方法的研究.压缩机技术,2001,(1)：3-5
[7]金涛,童水光等.往复式压缩机故障监测与诊断技术.流体机械,1999,(11)：28-31
[8]裴峻峰,杨其俊.机械故障诊断技术.山东：石油大学出版社,1977
[9]M.P.Kozochkin,N.A.Kochinev,F.S.Sabirov.Diagnostics and monitoring of complex production processes using measurement of vibration-acoustic signals.Springer New York,2006,49(7):672-678
[10]Kotani M.,Matsumoto H.,Kanagawa T.Acoustic diagnosis for compressor with hybrid neural network.in:International Joint Conference on Neural Networks.Seat-le,WA USA.1991,251-256
[11]Youmin Zhang,Jin Jiang,Flatley M.et al.Condition monitoring and fault detection of a compressor using signal processing techniques. in:American Control Confe-ence.Arlington,VA USA.2001,4460-4465
[12]程道来,仪垂杰,郭健翔等.基于Wigner-ville分布和Wavelet时间尺度的飞机非平稳抖杆背景声分析.机械工程学报,2007,43(5)：150-154
[13]Spanjaard J.M.,Sherman P.J.,White L.B.et al.Periodic autoregressive time-frequenc analysis for monitoring of rotating machinery with variable period.in:Internatio-a 1 Symposium on Time-Frequency and Time-Scale Analysis.Paris,France.1996,465-468
[14]Vokurka K.Time-frequency statistical characteristics of cyclostationary signal.Proce-edings of the IEE-SP International Symposium on Time-Frequency and Time-Sc ale Analysis,London,1998
[15]Youfu WU,Jun SHEN.Moving object detection using orthogonal Gaussian-Hermite moments.Visual Communications and Image Processing 2004.841-849
[16]Jun Shen,Wei Shen.Comparison study of geometric and orthogonalmoments.SPIE, 1998,42-53
[17]Marios M.Polycarpou.Fault Accommodation of a Class of Multivariable Nonlinea Dynamical Systems Using a Learning Approach.IEEE Transactions on Auto-mati c Control,2001,46(5):736-742
[18]黄文虎,夏松波,刘瑞岩等.设备故障诊断原理、技术及应用.北京：科学出版社,1996
[19]王荣杰,胡清.基于知识的故障诊断方法的发展现状与展望.微计算机信息,2006,32(7)：218-220
[20]路亚峰,张涛,张贤等.机载电子设备故障诊断专家系统的设计与实现.电子测量技术,2010,33(1)：118-120
[21]C.James Li,Xueli Yu.High pressure air compressor valve fault diagnosis using feedforward neural networks.Mechanical Systems and Signal Processing,1995,9(5): 527-536
[22]王金东,张嘉钟,刘树林.应用神经网络识别往复式压缩机指示图.振动、测试与诊断,2003,23(3)：217-219
[23]Peter Tse,D.D.Wang.A Hybrid Neural NetWorks based Machine Condition Forecas-ter and Classifier by using Multiple Vibration Parameters.in:International Joint Conference on Neural Networks.Washington,DC USA.1991,2096-2100
[24]Kotani M.,Ochi M.,Ozawa S.et al.Evolutionary discriminant functions using geneti c algorithms with variable-length chromosome.in:International Joint Conference on Neural Networks.Washington,DC USA.2001,761-766
[25]Pawlak Z.,Rough sets.International Journal of Information and Computer Science, 1982,11(5):341-356
[26]Francis E.H.Tay,Lixiang Shen.Fault diagnosis based on rough set theory.Engineeri-ng Applications of Artificial Intelligence,2003(16):39-43
[27]Shulin Liu,Wengang Shi.Rough set based intelligence diagnostic system for valve in reciprocating pumps.in:IEEE International Conference on Systems,Man,and Cybernetics.Tucson,AZ USA.2001,353-358
[28]刘卫华,郁永章.往复式压缩机故障分析及智能诊断系统.压缩机技术,2000,(4)：27-28
[29]郁永章,高秀峰.国内外压缩机学术研究近况.压缩机技术,2003,(4)：14-17
[30]Company Bently Nevada.Bently Nevada expands reciprocating compressor monitor-ing solutions.Bently Nevada's News Release.http://www.bently.com/
[31]Johann Lenz.Condition monitoring for compressors.Hydrocarbon,1992,(2):1-5
[32]沈祥兴.用于压缩机动态数据采集与处理的计算机辅助测试系统.压缩机技术,1986, (4)：40-47
[33]高洪涛,黄钟岳,王一兵等.汽轮机压缩机组在线热力性能诊断系统.化工机械,1998,(3)：149-151
[34]汪家铭.往复式压缩机运行状态的在线监测.压缩机技术,1994,(2)：25-27
[35]刘卫华,郁永章.往复式压缩机故障分析及智能诊断系统.压缩机技术,2000,(4)：28-30
[36]黄海鹏.往复式压缩机组在线监测与诊断系统CMD-3N的研制.硕士学位论文,杭州：浙江大学,2004
[37]Piero P Bonissone,Chen Yuto.Kai Goebeletal.et al.Hybrid Soft Computing System Industrial and Commercial Applications.Pooc.The IEEE,1999,87(9):1647-1667
[38]潘永密,李斯特.化工机器(上册).北京：化学工业出版社,1980
[39]李俊.往复式压缩机状态监测系统研究.硕士学位论文,武汉：华中科技大学,2004
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