基于FTA和FNN的液压系统故障诊断方法研究

游张平; 叶晓平; 朱银法; 胡笑奇

基于FTA和FNN的液压系统故障诊断方法研究

1.
丽水学院机械工程学系, 丽水 323000

基金项目:

国家科技支撑计划项目(2013BAC16B02)

浙江省自然科学基金重点项目(LZ12F02001)

丽水市公益性技术应用项目(2012JYZB34)

机械设计及理论浙江省重中之重学科

浙江理工大学重点实验室基金项目(ZSTUMD2011A005)资助

详细信息

作者简介:
游张平(1978-)，讲师，博士，研究方向为设备智能故障诊断和机电液控制技术，youzping@163.com

计量
- 文章访问数: 224
- HTML全文浏览量: 35
- PDF下载量: 8
- 被引次数: 0
出版历程
- 收稿日期: 2012-09-12
- 刊出日期: 2015-06-10

A Hydraulic System Fault Diagnosis Method Based on FTA and FNN

1.
Department of Mechanical Engineering, Lishui University, Lishui 323000

摘要

摘要: 针对液压系统故障的复杂性和不确定性等特点,传统的故障推理方法难以满足液压系统故障诊断的要求,提出了基于故障树分析和专家经验知识的模糊神经网络故障诊断方法。以起重设备液压系统为研究对象,建立故障树模型,基于故障树信息和专家经验知识,建立模糊神经网络诊断模型及并提取训练数据,在此基础上,运用统计参数法确定模糊预处理所需的模糊隶属函数。将训练好的网络模型应用于实例诊断,实验结果验证了该方法的实用性和有效性。
- 液压系统 /
- 故障诊断 /
- 故障树分析 /
- 神经网络
Abstract: The hydraulic system fault diagnosis method based on fuzzy neural networks( FNN),fault tree analysis( FTA) and expertise knowledge is proposed to overcome the shortcomings of the traditional fault diagnosis methods because of the complexity coupling and uncertainty of hydraulic system fault. Taking lifting equipment's hydraulic system as study object,a fault tree model is set up,and the fault tree information and expertise knowledge are employed to establish the FNN structure and extract training data. The fuzzy membership functions,which are needed in fuzzy pre-processing,are confirmed by using the statistical parameter method. Finally,the trained FNN model is applied to examples; the application results show that the hydraulic system fault diagnosis method based on FTA and FNN is effective and practicable.
- efficiency /
- failure analysis /
- fault tolerance /
- fuzzy neural networks ( FNN)

HTML全文

参考文献(9)

[1]	周汝胜,焦宗夏,王少萍. 液压系统故障诊断技术研究现状与发展趋势[J].机械工程学报,2006,(09):6-14.
[2]	Ma C,Wang K S,Sun J H. Fault diagnosis to mid-size excavator hydraulic system based on fault tree analysis[A].2010.
[3]	向长城. 基于可拓学的智能故障诊断与状态监测的理论及应用研究[D].重庆:重庆大学,2008.
[4]	He X Y,Shao Y M,He S H. Fault diagnosis of hydraulic system using dynamic GRNN[J].ICIC Express Letters,2011,(8A):2617-2623.
[5]	陈炜,吴志良. 故障诊断专家系统结合故障树技术的结构研究[J].航海技术,2005,(06):43-44.
[6]	Pisu P. Hierarchical model-based fault diagnosis with application to vehicle systems[A].Barcelora,spain,2002.
[7]	张敬芬,孟光,赵德有. 基于模糊神经网络的薄板不同指标裂纹诊断[J].机械工程学报,2006,(03):145-149.
[8]	Yznaga B I,Sun D,He Y K. Neural-fuzzy technique for inverter faults diagnosis in PMSM DTC system[J].Electric Machines and Control,2008,(03):132-139.
[9]	Pltkeisheim F. The three sigma nule[J].The American Statistician,1994,(02):88-91.