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| 汽轮发电机组轴心轨迹特征的自动提取及辨识 | |
| 引用本文： | 张新江,李奕,杨建国.汽轮发电机组轴心轨迹特征的自动提取及辨识[J].热能动力工程,1999,14(6):487-488. |
| 作者姓名： | 张新江 李奕 杨建国 |
| 作者单位： | 1. 哈尔滨工业大学 2. 长春热电一厂生技处 3. 辽宁工程技术大学 |
| 摘 要： | 根据汽轮发电机组转子轴心轨迹的特点，利用信号与噪声的小波变换模极大值随尺度变化的截然不同的性质可达到消噪地的目的的特点，提纯轴心轨迹 种新的平面图形可变等长度压缩编码方法，用该方法可使降噪后的轴心轨迹图形编码得到较大压缩，从而使轴心轨迹神经网络识别系统的输入得到减少，加快了网络的训练速度。也使神经网络识别系统的准确率和稳定性得以提高。 |
| 关 键 词： | 汽轮发电机组 轴心轨迹 小波迹换 神经网络 |
The Automatic Extraction and Identification of the Shaft Centerline Locus Characteristics of a Turbogenerator Set |
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| Zhang Xinjiang,et al.The Automatic Extraction and Identification of the Shaft Centerline Locus Characteristics of a Turbogenerator Set[J].Journal of Engineering for Thermal Energy and Power,1999,14(6):487-488. | |
| Authors: | Zhang Xinjiang |
| Abstract: | On the basis of the specific features of a turbogenerator rotor shaft centerline locus and by utilizing the totally different character of the variation with scale of wavelet transformation modulus maximum value of signal and noise to eliminate noise, the authors conducted an extraction of shaft centerline locus. Moreover, a new type of variable equi length compression coding of plane graphics is proposed. With the help of this method it is possible to achieve a relatively sizable compression of the shaft centerline locus graphics coding after the noise abatement. This has led to a decrease in output of the identification system of the shaft centerline locus neural network, thus increasing the network training speed. Meanwhile, the accuracy and stability of the neural network identification system undergo a simultaneous enhancement. |
| Keywords: | turboogenerator set shaft centerline locus wavelet transformation neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
