基于LabVIEW的旋转机械故障诊断可视化系统的设计

【作者】 冯今朝；

【导师】 王仲生；

【作者基本信息】 西北工业大学 ， 载运工具运用工程， 2007， 硕士

【摘要】 旋转机械在机械装备中占有举足轻重的地位，它们大多为生产企业中的关键设备，因此，保证旋转机械的安全可靠运行对企业和国民经济有重要的意义。论文针对以往旋转机械故障诊断的复杂过程，设计了一套基于LabVIEW7.1可视化编程软件的旋转机械故障诊断可视化系统，对旋转机械的故障诊断过程进行可视化图形显示，不仅提高了用户操作的直观性和友好性，而且提高了的工作效率。 论文在对旋转机械典型故障特征、传统特征分析方法和非平稳信号的时频分析技术进行了详细介绍的基础上，采用当今计算机测试领域比较流行的虚拟仪器，通过虚拟式监测，对旋转机械的不同振动故障，进行了时域波形分析、频谱分析，利用小波包分析进行故障信号的特征频率提取，最后，比较目前故障诊断领域常用的几种先进诊断方法，选择具有高度的非线性、高度容错和联想记忆的功能的神经网络(LM优化算法)进行故障的分类识别，得出诊断结果。实验结果表明，所研究和设计的系统的有效性和实用性。更多还原

【Abstract】 Rotating machinery takes up the major part in all machinery equipments and plays an important role in industry enterprises. It is very important to ensure the running safety of rotating machinery for both enterprises and our society. In order to salve the problem that process of fault diagnosis is too complex, this dissertation design a fault diagnosis visualization system of rotating machinery. It is based LabVIEW 7.1 and fault diagnosis process of rotating machinery is displayed by visual figures. Not only visualization and friendly were improved in user operation, but also efficiency.This dissertation introduces particularly representative fault characters, traditional character’s analysis methods and the time-frequency analysis for non-stationary signals, Moreover; it introduces the virtual instrument technology, which is popular in the field of Computer Aided Technology. Through virtual monitoring mean, both time domain and frequency domain methods can be used to analyze several sorts of fault vibration signal of rotating machinery. Wavelet packet was used to extract fault characteristic value. Finally, ANN (LM optimization algorithm) was chose from several advanced diagnosis methods to identify fault type because of its good performance on non-linear, fault-tolerant and associative memory. Then the result of fault diagnosis can be gained. The experiment testifies the effectiveness and practicability of this designed system.更多还原