基于自适应谐振理论的特征频率提取与融合  

Feature Frequency Extraction and Fusion Based on Adaptive Resonance Theory

作　　者：赵学智[1] 曾作钦[1] 叶邦彦[1] 陈统坚[1] 

机构地区：[1]华南理工大学机械与汽车工程学院,广州510640

出　　处：《振动．测试与诊断》2010年第1期33-38,共6页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(编号:50305005)

摘　　要：借鉴自适应谐振理论的一些处理思想,提出了一种特征频率提取、融合和增强算法。通过对频谱向量进行多次归一化处理,并插入非线性阈值函数来抑制小幅度噪声频率,同时用适当的正反馈使特征频率进一步增强,且不同频谱之间的融合也被嵌入到其中,形成一种闭环迭代运算。对空调电机3种振动噪声频谱的处理结果表明,该算法有效抑制了原始频谱中的随机干扰频率,对频谱中有用的成分进行了较大幅度的增强。对于每一种振动噪声,该算法都从多个频谱中准确地获取了一个清晰可靠的特征频谱,效果优于平均谱。An algorithm on feature frequency extraction and fusion,in which some ideas of adaptive resonance theory are referred to,is proposed.In this algorithm,multi-normalization for spectrum vectors is made and a nonlinear threshold function is inserted into this normalization operation to suppress the interference frequencies caused by noises.Simultaneously,some proper positive feedbacks are used to strengthen the feature frequencies,and the fusion computation of different spectrums is also embedded in,all these proessing measures form a closed iterative computation loop,by which the feature frequencies can be extracted,fused and strengthened from the multiple spectrums,while those interference frequencies can be greatly suppressed.Three kinds of vibration noise spectrums of the electromotor of an air-conditioner are processed by this algorithm.The results show that for each kind of noise,a clear and accurate feature spectrum is obtained from the multiple spectrums,and its effectiveness is much better than that of the average spectrum method.

关 键 词：特征频率 融合与增强 自适应谐振理论 归一化 频谱分析 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TK267[自动化与计算机技术—控制科学与工程]