《机电工程》杂志,月刊( 详细... )
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船舶推进轴系扭振数据采集及处理系统*
作者:胡海刚,曹磊,冯志敏 日期:2008-12-26/span> 浏览:3356 查看PDF文档
船舶推进轴系扭振数据采集及处理系统*
胡海刚,曹磊,冯志敏
(宁波大学 海运学院, 浙江 宁波 315211)
摘要:从验证扭振信号采集和故障监测的准确性和可靠性的目的出发,设计了一套船舶推进轴系扭振数据采集及处理系统。同时,以齿盘和光电开关组合为传感器,NI的信号调理箱、数据采集卡等为主要器件实现了扭振信号采集;并采用Visual C++编程开发了故障监测与分析软件,实现了对扭振信号的实时采集和处理。实验研究结果表明,该方案实现了设计的目标,较好地满足了教学和科研的需求。
关键词:船舶推进轴系;扭振;数据采集;故障监测
中图分类号:TP274文献标识码:A文章编号:1001-4551(2008)11-0024-03
Data collecting and processing system of torsional vibration of ship propulsion shafting
HU Haigang, CAO Lei, FENG Zhimin
(The Faculty of Maritime, Ningbo University, Ningbo 315211, China)
Abstract: In order to verify the accuracy and reliability of the signal collecting of torsional vibration and fault monitoring, a set of data collecting and processing systems of torsional vibration of ship propulsion shafting was designed. At the same time, using combination of gear and photoelectric switch for the sensors, the signal conditioning box of National Instruments(NI) Corporation and data collecting card as the main devices, the signal collecting of torsional vibration was completed. In addition, a software of the fault monitoring and analysis was developed with Visual C++. The signal real time collecting of torsional vibration and processing were realized. Experimental results indicate that aim of the design is achieved, which satisfies the needs of teaching and scientific research.
Key words: ship propulsion shafting; torsional vibration; data collecting; fault monitoring
参考文献(References):
[1]冯志敏,王颖.智能化故障诊断系统的研究与开发[J].中国航海,2003(1):13-17.
[2]胡海刚,冯志敏,蒲龙云.基于虚拟仪器的扭振检测仪设计[J].机床与液压,2003(6):289-291.
[3]陈锡恩.船舶轴系扭振计算和测试实例分析[J].船舶工程,2002(1):22-26.
[4]王祺.内燃机轴系扭转振动[M].大连:大连理工大学出版社,1991.
[5]PLATT J C. Large margin DAGs for multiclass classification[C]//Advances in Neural Information Processing Systems. Cambridce, MA: MIT Press,2000:547-553.
[6]史晓敏.船舶螺旋浆的偏振和抗冲击稳定性研究[J].机电工程,2007,24(9):17-19.
[7]KRESSEL U. Pairwise classification and support vector machine[C]//B. Scholkopf, ed. Advance in Kernel Methods Support Vector Learing, Cambridge, Massachusetts. MIT Press,1999:255-268.
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