集成传感器的高速滚动轴承状态监测装置研制
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摘要
滚动轴承是高速航空主轴轴系中最关键的部件,也是危险系数最高的零部件之一。航空主轴系统很多故障都与滚动轴承状态有关,在航空极端苛刻环境下,轴承缺陷会导致严重异常振动和噪声,甚至造成严重的人民生命财产损失。因此研究高速滚动轴承状态监测和故障诊断技术就具有非常重要的意义。为提高监测过程中传感器拾取轴承状态信号的准确性,提高测试信号的信噪比,本文采用集成化思想,实现传感器和轴承的结构集成,使信号采集点距离故障发生位置尽量接近,从而拾取到更准确的轴承运转状态信号及故障信号。利用相应数据处理算法,判断轴承是否出现故障及其故障特性和严重程度。这种集成多传感器的轴承状态监测方法提高了轴承故障诊断的可靠性,具有信息容错性、互补性、实时性等优点。
本文针对轴承的常见故障类型,完成了传感器的选型、安装、标定以及高速滚动轴承传感器集成设计和研究,分析了集成结构的性能特点,并用ANSYS对集成结构进行了有限元分析。根据传感器不同性能设计了相对应的数据采集系统,编写了VB软件,与组态王共同完成数据采集任务。
根据轴承的故障机理与故障信号特征,分析了所用时域分析和频域分析所用的数据处理算法,并用MATLAB编写了能够完成对应功能的程序。完成了相应的故障诊断算法,实现了利用多传感器的信息融合技术使系统能够完成轴承状态检测和故障诊断的功能。
最后进行了轴承状态监测装置考核实验。通过带有预设特定故障的轴承,检验轴承状态监测系统对轴承故障类型判断是否准确;通过对有故障和无故障的滚动轴承的对比测试,检验了此系统的可靠性和实用性。最后通过转速和载荷这两个参数的变化,对振动,应变,温度随转速和载荷的变化进行了相关实验,得出了相应结论。
The rolling bearing is one of the most important mechanical parts in the High-Speed spindle system, and is vulnerable to damage. Because of the awful condition, the faults can result in abnormal vibration and noise of machines, equipment damage and personal casualty. Therefore, it is important to study fault diagnosis of rolling bearings. For improving the veracity and the S/N Ratio of the bearing’s signal which the sensor picked up, Integration was been exerted, actualizing the integration between bearings and sensors, making the distance from fault point to testpoint shorter and the signal more accurate. According the potential bearing faults, applying appropriate data processing algorithms, the occurrence and extent of bearing faults can be determined This way advanced the reliability of fault diagnosis of rolling bearings. It possessed the characteristic of forgiving, complementarity and real-timing.
It accomplished the mission of choos ing and installing sensors, demarcating the sensors, and integrated design of the bearings and sensors. It used the ANSYS software to analysed the strengths and weaknesses of the integrated design. Later it designed data acquisition system on the basis of the different characteristics of the sensor. A Visual Basic software was developed, which can complete data acquisition with configuration software(Kingview 6.5)together.
In this paper, the data processing algorithm used to analyse in time-domain and frequency-domain was introduced according to the failure mechanism and signal characteristic. A MATLAB program which can accomplish corresponding function was developed. Using this, it made the system could monitor bearing’s state and diagnose failures.
At last, it carried abundant experiments through to examine the device. One of the intention was that by means of the bad bearing which was damaged with a special failure, testing the system can judge the type of the bearing rightly or not. Another is that by means of the contrast experiments between bad bearing and well bearing, test ing the reliability and practicability of the system. Changing the rev and loading, it taken relevant experiments, knew how the vibration, strain and temperature changed, and drawn corresponding conclusions.
本文针对轴承的常见故障类型,完成了传感器的选型、安装、标定以及高速滚动轴承传感器集成设计和研究,分析了集成结构的性能特点,并用ANSYS对集成结构进行了有限元分析。根据传感器不同性能设计了相对应的数据采集系统,编写了VB软件,与组态王共同完成数据采集任务。
根据轴承的故障机理与故障信号特征,分析了所用时域分析和频域分析所用的数据处理算法,并用MATLAB编写了能够完成对应功能的程序。完成了相应的故障诊断算法,实现了利用多传感器的信息融合技术使系统能够完成轴承状态检测和故障诊断的功能。
最后进行了轴承状态监测装置考核实验。通过带有预设特定故障的轴承,检验轴承状态监测系统对轴承故障类型判断是否准确;通过对有故障和无故障的滚动轴承的对比测试,检验了此系统的可靠性和实用性。最后通过转速和载荷这两个参数的变化,对振动,应变,温度随转速和载荷的变化进行了相关实验,得出了相应结论。
The rolling bearing is one of the most important mechanical parts in the High-Speed spindle system, and is vulnerable to damage. Because of the awful condition, the faults can result in abnormal vibration and noise of machines, equipment damage and personal casualty. Therefore, it is important to study fault diagnosis of rolling bearings. For improving the veracity and the S/N Ratio of the bearing’s signal which the sensor picked up, Integration was been exerted, actualizing the integration between bearings and sensors, making the distance from fault point to testpoint shorter and the signal more accurate. According the potential bearing faults, applying appropriate data processing algorithms, the occurrence and extent of bearing faults can be determined This way advanced the reliability of fault diagnosis of rolling bearings. It possessed the characteristic of forgiving, complementarity and real-timing.
It accomplished the mission of choos ing and installing sensors, demarcating the sensors, and integrated design of the bearings and sensors. It used the ANSYS software to analysed the strengths and weaknesses of the integrated design. Later it designed data acquisition system on the basis of the different characteristics of the sensor. A Visual Basic software was developed, which can complete data acquisition with configuration software(Kingview 6.5)together.
In this paper, the data processing algorithm used to analyse in time-domain and frequency-domain was introduced according to the failure mechanism and signal characteristic. A MATLAB program which can accomplish corresponding function was developed. Using this, it made the system could monitor bearing’s state and diagnose failures.
At last, it carried abundant experiments through to examine the device. One of the intention was that by means of the bad bearing which was damaged with a special failure, testing the system can judge the type of the bearing rightly or not. Another is that by means of the contrast experiments between bad bearing and well bearing, test ing the reliability and practicability of the system. Changing the rev and loading, it taken relevant experiments, knew how the vibration, strain and temperature changed, and drawn corresponding conclusions.
引文
1苏保定.滚动轴承振动检测与智能诊断系统研究.大连理工大学工学硕士论文. 2008: 1~2
2 Runnels S.R, Eyman L.M. Tribology Analysis of Chemical Mechanical Polishing. J.Electrochem Soc. 1994, (141): 16~98
3 Sundarajan S, Thakurta G.D, Schwendeman D.W, et al. Two Dimensional Wafer Scale Mechanical Planarization Model Based on Lubrication Theory and Mass Transport. J.E lectrochem Soc. 1999,146(2): 761~766
4陈霞.滚动轴承的智能诊断系统研究.湖北工业大学学报. 2007, 22(4): 50～51
5 Paul B.Koeneman, Ilene J.Busch-Vishniac, and Kristin L.Wood. Feasibility of Micro Power Supplies for MEMS. Jourmal of Microelectromechannical Systems, 1999,6(4): 355~356
6谢荣华,罗贵火.航空用高速滚动轴承失效分析.振动与冲击. 2008, (6): 16～17
7舍弗勒集团.滚动轴承失效识别和轴承监测. WL82102/2CN-CN, 2001:5~11
8肖述兵.滚动轴承故障诊断实践.轴承. 2006, (3): 31~33
9 Sundarajan S, Thakurta G.D, Schwendeman D.W, et al. Two Dimensional Wafer Scale Mechanical Planarization Model Based on Lubrication Theory and Mass Transport. J.E lectrochem Soc. 1999,146(2): 761~766
10李兴林,沈云同,潘继康.轴承振动(速度)噪声测试技术现状及发展.现代零部件. 2005, (2): 90～93
11张国远.基于PC机的滚动轴承自动检测与故障诊断系统.浙江大学工学硕士论文. 2005: 6～8
12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. 2003: 50～51
13周瑞峰.滚动轴承故障智能诊断方法的研究与实现.大连理工大学工学硕士论文. 2008: 5
14 Youhong Lu and Joe M.Morris. Gabor Expasion for Adaptive Eeho Cancellation IEEE Signal Proeessing Magazine, Mar.1999: 68～80
15赵联春,马家驹,曹志飞,刘雪峰,刘朝晖.传感器安装方式对轴承振动测量特性的影响.测量与仪器. 2003, (1): 27～28
16赵志峰,张钢,高刚,梁世颇,张彪.速度检测型传感器轴承的设计.测量与仪器. 2007, (11): 13～14
17宁练,周孑民.滚动轴承内部温度状态监测技术.轴承. 2007, (2): 25～26
18 C. P. Fritzen, P. Kraemer. Self-doagnosis of Smart Structures Based on Dynamical Properties. Mechaniacal Systems and Signal Processing, 2009(23):1830-1832
19 Roundy, S, Steingart, D, Frechette, L, Wright, P. K., and Rabaey, J. "Power Sources for Wireless Networks,"Proceedings of the First European Workshop on Wireless Sensor Networks, Berlin,Germany, 2004,7:19～21
20 Yimin SHAO, Liang GE and Jieping FANG. Fault Diagnosis System Based on Smart Bearing. International Conference on Control, Automation and Systems 2008, in COEX, Korea, Oct.14-17,2008: 1184～1085
21 W. Maddox,“Modeling and design of a smart hydrodynamic bearing with an actively deformable surface,”Master’s thesis, Univ. Texas,Austin, TX, 1994.
22 Rodrick K.Draney. High Temperature Sensor for Bearing Health Monitoring. Feasibility of Micro Power Supplies for MEMS. Journal of Microelectro Mechancal Systems, vol. 6, NO. 4, 2008, 1(8): 1165～1166
23 B. T. Holm-Hansen and R. X. Gao. Integrated Microsensor Module for a Smart Bearing with On-Line Fault Detection Capabilities. IEEE Instrumentation and Measurement Technology Conference Ottawa, Canada, May 19-21, 1997
24 R.X. Gao and S. Priyranjan, Structure Analysis of a Sensor Module for the Smart Bearing, Proceedings of the ASV1E Dynamic Systems and ControlDivision, 2007, 8(64): 95～97
25张朝晖. ANSYS11.0结构分析工程应用实例解析.机械工业出版社. 2008, (2): 123～129
26鹿麟,林凌,李刚. ADXL203型双轴加速计在倾斜度测量中的应用.国外电子元器件. 2007, (7). 61~64
27宋广东,刘统玉,王昌,霍佃恒,祁海峰.基于COM组件的VB与MATLAB混合编程实现振动信号处理.山东科学. 2010, 23(1): 32～35
28 Mclnerny SA, Dai Y. Basic vibration singal processing for bearing fault detection. Education, IEEE Transactions on, Volume:46, Issue: 1, Feb, 2003: 149~156
29李昊.基于小波循环自相关分析方法的滚动轴承振动信号处理技术的研究.中南大学硕士学位论文. 2005: 15～17
30 N.Tandon. A Comparison of Some Vibration Parameters for the Condition Monitoring of Rolling Element Bearings. Measurement, 1994, (12):285~289
31 C.Capdessus, M.Sidahmed, and J.L. Lacoume. Cyclostationary Processes: Application in Gearing Faults Early Diagnosis. Mechanical System and Signal Processing. 2000, 14(3):371~385
32 YongXiang Zhang, R.B.Randall. Rolling Element Bearing Fault Diagnosis Based on the Combination of Genetic Algorithms and Fast Kurtogram. Mechanical System and Signal Processing. 2009, (13):1509~1517
33孙苗钟,赵鹏.基于MATLAB的振动信号处理与分析系统设计与实现.电子测试,2008, (10): 88～89
34 Bo Tao, Limin Zhu, Han Ding et al. An alternative time-domain index condition monitoring of rolling element bearings—A comparison study. Reliablity Engineering and System Safety, 2007(92): 660~670
35黄建新.多传感器数据融合技术在轴承故障诊断中的应用研究.武汉理工大学硕士学位论文. 2006: 26～28
36樊淑趁,耿麦香,许建宾.论数字信号处理中加窗的影响及窗函数的选择原则.山西矿业学院学报,1995, 13(4): 347～349
37王济,胡晓编著. MATLAB在振动信号处理中的应用.北京:知识产权出版社,2006:83~84
38 Michael Cerna and Audry F.Harvey. The Fundamenttals of FFT-Based Signal Analysis and Measurement. National Instrument Corporation Application Note, 2000(41):8～39
39郑德志,王黎钦,古乐,魏勇强.航空发动机用高速滚动轴承性能考核及失效分析.润滑与密封. 2006, (7): 51～53
40彭拾义,冯惠芳.减少滚动轴承打滑的方法.机械制造. 1992, (10): 17
2 Runnels S.R, Eyman L.M. Tribology Analysis of Chemical Mechanical Polishing. J.Electrochem Soc. 1994, (141): 16~98
3 Sundarajan S, Thakurta G.D, Schwendeman D.W, et al. Two Dimensional Wafer Scale Mechanical Planarization Model Based on Lubrication Theory and Mass Transport. J.E lectrochem Soc. 1999,146(2): 761~766
4陈霞.滚动轴承的智能诊断系统研究.湖北工业大学学报. 2007, 22(4): 50～51
5 Paul B.Koeneman, Ilene J.Busch-Vishniac, and Kristin L.Wood. Feasibility of Micro Power Supplies for MEMS. Jourmal of Microelectromechannical Systems, 1999,6(4): 355~356
6谢荣华,罗贵火.航空用高速滚动轴承失效分析.振动与冲击. 2008, (6): 16～17
7舍弗勒集团.滚动轴承失效识别和轴承监测. WL82102/2CN-CN, 2001:5~11
8肖述兵.滚动轴承故障诊断实践.轴承. 2006, (3): 31~33
9 Sundarajan S, Thakurta G.D, Schwendeman D.W, et al. Two Dimensional Wafer Scale Mechanical Planarization Model Based on Lubrication Theory and Mass Transport. J.E lectrochem Soc. 1999,146(2): 761~766
10李兴林,沈云同,潘继康.轴承振动(速度)噪声测试技术现状及发展.现代零部件. 2005, (2): 90～93
11张国远.基于PC机的滚动轴承自动检测与故障诊断系统.浙江大学工学硕士论文. 2005: 6～8
12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. 2003: 50～51
13周瑞峰.滚动轴承故障智能诊断方法的研究与实现.大连理工大学工学硕士论文. 2008: 5
14 Youhong Lu and Joe M.Morris. Gabor Expasion for Adaptive Eeho Cancellation IEEE Signal Proeessing Magazine, Mar.1999: 68～80
15赵联春,马家驹,曹志飞,刘雪峰,刘朝晖.传感器安装方式对轴承振动测量特性的影响.测量与仪器. 2003, (1): 27～28
16赵志峰,张钢,高刚,梁世颇,张彪.速度检测型传感器轴承的设计.测量与仪器. 2007, (11): 13～14
17宁练,周孑民.滚动轴承内部温度状态监测技术.轴承. 2007, (2): 25～26
18 C. P. Fritzen, P. Kraemer. Self-doagnosis of Smart Structures Based on Dynamical Properties. Mechaniacal Systems and Signal Processing, 2009(23):1830-1832
19 Roundy, S, Steingart, D, Frechette, L, Wright, P. K., and Rabaey, J. "Power Sources for Wireless Networks,"Proceedings of the First European Workshop on Wireless Sensor Networks, Berlin,Germany, 2004,7:19～21
20 Yimin SHAO, Liang GE and Jieping FANG. Fault Diagnosis System Based on Smart Bearing. International Conference on Control, Automation and Systems 2008, in COEX, Korea, Oct.14-17,2008: 1184～1085
21 W. Maddox,“Modeling and design of a smart hydrodynamic bearing with an actively deformable surface,”Master’s thesis, Univ. Texas,Austin, TX, 1994.
22 Rodrick K.Draney. High Temperature Sensor for Bearing Health Monitoring. Feasibility of Micro Power Supplies for MEMS. Journal of Microelectro Mechancal Systems, vol. 6, NO. 4, 2008, 1(8): 1165～1166
23 B. T. Holm-Hansen and R. X. Gao. Integrated Microsensor Module for a Smart Bearing with On-Line Fault Detection Capabilities. IEEE Instrumentation and Measurement Technology Conference Ottawa, Canada, May 19-21, 1997
24 R.X. Gao and S. Priyranjan, Structure Analysis of a Sensor Module for the Smart Bearing, Proceedings of the ASV1E Dynamic Systems and ControlDivision, 2007, 8(64): 95～97
25张朝晖. ANSYS11.0结构分析工程应用实例解析.机械工业出版社. 2008, (2): 123～129
26鹿麟,林凌,李刚. ADXL203型双轴加速计在倾斜度测量中的应用.国外电子元器件. 2007, (7). 61~64
27宋广东,刘统玉,王昌,霍佃恒,祁海峰.基于COM组件的VB与MATLAB混合编程实现振动信号处理.山东科学. 2010, 23(1): 32～35
28 Mclnerny SA, Dai Y. Basic vibration singal processing for bearing fault detection. Education, IEEE Transactions on, Volume:46, Issue: 1, Feb, 2003: 149~156
29李昊.基于小波循环自相关分析方法的滚动轴承振动信号处理技术的研究.中南大学硕士学位论文. 2005: 15～17
30 N.Tandon. A Comparison of Some Vibration Parameters for the Condition Monitoring of Rolling Element Bearings. Measurement, 1994, (12):285~289
31 C.Capdessus, M.Sidahmed, and J.L. Lacoume. Cyclostationary Processes: Application in Gearing Faults Early Diagnosis. Mechanical System and Signal Processing. 2000, 14(3):371~385
32 YongXiang Zhang, R.B.Randall. Rolling Element Bearing Fault Diagnosis Based on the Combination of Genetic Algorithms and Fast Kurtogram. Mechanical System and Signal Processing. 2009, (13):1509~1517
33孙苗钟,赵鹏.基于MATLAB的振动信号处理与分析系统设计与实现.电子测试,2008, (10): 88～89
34 Bo Tao, Limin Zhu, Han Ding et al. An alternative time-domain index condition monitoring of rolling element bearings—A comparison study. Reliablity Engineering and System Safety, 2007(92): 660~670
35黄建新.多传感器数据融合技术在轴承故障诊断中的应用研究.武汉理工大学硕士学位论文. 2006: 26～28
36樊淑趁,耿麦香,许建宾.论数字信号处理中加窗的影响及窗函数的选择原则.山西矿业学院学报,1995, 13(4): 347～349
37王济,胡晓编著. MATLAB在振动信号处理中的应用.北京:知识产权出版社,2006:83~84
38 Michael Cerna and Audry F.Harvey. The Fundamenttals of FFT-Based Signal Analysis and Measurement. National Instrument Corporation Application Note, 2000(41):8～39
39郑德志,王黎钦,古乐,魏勇强.航空发动机用高速滚动轴承性能考核及失效分析.润滑与密封. 2006, (7): 51～53
40彭拾义,冯惠芳.减少滚动轴承打滑的方法.机械制造. 1992, (10): 17