摘要
为了利用多源信息、融合多种评判结果,设计利用性能参数、热力学参数进行模糊诊断,基于LabVIEW提取振动信号的小波包子带能量特征进行神经网络模式识别,领域专家通过权值系数对诊断策略进行调整和评估,由模糊评价进行综合诊断的系统框架,在应用中取得了较好的效果。
To use information of different sources and mix multiple results, a scheme of using performance character and thermodynamics parameter is proposed. In this scheme, the wavelet packet sub-band energy of vibration signal is achieved based on LabVIEW and the neural net pattern reorganization is implemented based on performance character. Experts of each domain adjust the diagnosis strategy using weight coefficient, and the final conclusion is combined through fuzzy evaluation. The proposed method has been used successfully.
出处
《自动化应用》
2013年第10期7-9,12,共4页
Automation Application
基金
总装通保部项目资助
关键词
故障诊断
小波包分析
神经网络
知识工程
fault diagnosis
wavelet packet analysis
neural net
knowledge engineering