局部线性嵌入法(locally linear embedding,LLE)是一种典型的流形学习算法。在分析LLE算法的基本计算思路的基础上,提出了一种基于最佳分类效果的k和d综合参数选择方法。此方法综合考虑了故障类内和类间的离散度,并以此作为LLE算法特征...局部线性嵌入法(locally linear embedding,LLE)是一种典型的流形学习算法。在分析LLE算法的基本计算思路的基础上,提出了一种基于最佳分类效果的k和d综合参数选择方法。此方法综合考虑了故障类内和类间的离散度,并以此作为LLE算法特征压缩效果的评价依据。根据LLE算法的局部线性特征保持的基本特点,提出了一种增量式LLE算法用于柴油机机械故障特征压缩与诊断中。以平均子带能量法构造特征向量空间,子带数目的确定以同种故障类型特征参数间方差最小为准则。实验中,分别使用基于最佳参数选择的LLE算法、传统的主成分分析(principal component analysis,PCA)、增量式LLE算法对柴油机特征向量进行压缩,并对这三种算法的特征压缩结果运用K近邻算法(K-nearest neighborm,KNN)进行故障诊断与分类。结果表明基于最佳参数选择的LLE算法的诊断分类效果要优于传统的PCA方法,增量式LLE算法也取得良好的分类效果。实验表明,对LLE算法进行有关改进可以很好地应用到机械故障特征压缩与诊断中。展开更多
In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is propose...In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is proposed in this paper.The animal sound is turned into spectrogram to show the energy,time and frequency characteristics.The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution(SPD)and sub-band division.Radon transform(RT)and discrete wavelet transform(DWT)are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature.The E-F feature is formed by combining the SPD feature and sub-band energy value feature.The classification is achieved by support vector machine(SVM)classifier.The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.展开更多
基金Supported by the National Natural Science Foundation of China(No.61075022)
文摘In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is proposed in this paper.The animal sound is turned into spectrogram to show the energy,time and frequency characteristics.The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution(SPD)and sub-band division.Radon transform(RT)and discrete wavelet transform(DWT)are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature.The E-F feature is formed by combining the SPD feature and sub-band energy value feature.The classification is achieved by support vector machine(SVM)classifier.The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.
