搜索资源列表
BP-gearbox-fault-2
- 基于BP神经网络的齿轮箱故障模式识别：以双谱分析为基础，对分析的结果进行特征提取，提出了双谱一BP网络故障诊断方法，并以双谱为BP神经网络的输入特征向量，对所提出的方法进行了实验研究，结果表明所提出的双谱-BP诊断方法是判断齿轮葙故障类型的一种有效方法。-BP，gearbox fault diagnosis
Selection-of-Wavelet
- 通过定性与定量的分析, 提出了在对冲击信号进行连续小波变换时选择最佳小波基函数的方法和小波变换 后故障特征提取效果优劣的检验手段, 并且得出了对于冲击性信号的连续小波变换, 小波基函数的最佳选择为 M o rlet函数的结论。-A method for selecting the best wavelet base in cont inuous wavelet transform (CWT) for impulse signals is introduced, and a test fo
1.kdh
- 基于小波包的无刷直流电机匝间短路故障特征提取-Brushless DC motor based on wavelet packet inter-turn short circuit fault feature extraction
convwavepacket_fenjie
- 这是自己编的卷积型小波包的分解程序，用于机械故障特征提取，实现了克服Mallat算法数据量减少和产生虚假频率的缺陷-Own series of convolution type of wavelet packet decomposition procedures for mechanical fault feature extraction to overcome the defects of the the Mallat algorithm decrease in the amount of
advanced-harmonic-wavelet-packet
- 自己编的改进谐波小波包实现程序，实现了信号经过谐波小波包变换后幅值不变，适合于机械故障特征提取-The own series improved harmonic wavelet packet achieve signal amplitude unchanged after harmonic wavelet packet transform, for mechanical fault feature extraction
wavelet-packet-de_re
- 用小波工具箱函数实现小波包的分解与重构，非常适合与机械故障特征提取。-Wavelet packet decomposition and reconstruction, and is ideal for mechanical fault feature extraction using wavelet toolbox functions.
330
- 提出了将信号进行相空间重构后再采用奇异值分解, 对分解后的主成分进行包络分析, 从而提取信号的隐含特 征的方法, 并将该方法应用于齿轮的局部故障振动特征信号的提取中。数值仿真实验结果表明, 该方法能有效提取强背景 信号及噪声中的弱冲击特征信号, 是一种有效的弱信号特征提取方法。采用该方法对齿轮振动信号进行故障特征提取与识 别, 结果与实际情况相符。-Signal implicit characteristic of phase space reconstruction, and th
Fuzzy_entropy_bbd
- 模糊熵， 为解决从信号中提取故障特征难的问题, 介绍了一种新的信号故障特征提取方法—— 多尺度熵( multi-scale entro py, 简称MSE) , 并将样本熵和多尺度熵分别应用于转子故障信号复杂性的度量, 以提取故障特征。试验数据 分析表明, 与样本熵相比, 多尺度熵更能有效地实现转子故障类型的诊断。-A new rolling bearing fault diagnosis approach based onmultiscale permutation entropy (
med2d
- 一种基于最小熵反褶积( ]8+83)3 6+D*(A4 Q20(+W(-)D8(+，]6Q) 的滚动轴承故障特征提取方法: 在利用 /X 模型去除齿轮啮合产生的确定性信号的基础上，对保留信号进行最小熵反褶积，增强冲击信号"该方法避免了传统轴承故障诊断方法中带通滤波器设计的难题，实车测试表明: 与共振解调技术相比，该方法提取的滚动轴承故障特征更加明显，更适合于工程应用"-Based on minimum entropy deconvolution (] 8+83) 3 6+D* (A4 Q20 (
xbbtzztqt
- 故障分为很多种，该程序是利用小波包把故障特征提取出来，用于判断接下来出现的情况是把一种故障-The fault is divided into many, the program is using wavelet packet to extract the fault features out, used to judge the next case to a fault
Choiwilliams
- 计算振动信号的Choi-Williams分布，通过对照轴承故障特性频率可知，轴承的外圈发现了故障，完成了对外圈的故障特征提取。-The Choi-Williams distribution of the vibration signal is calculated. Through the comparison of the bearing fault characteristic frequency, the outer ring of the bearing is found to be f
wave
- 小波变换实例，用于故障特征提取，时域频域分析等-Examples of wavelet transform for fault feature extraction, time domain frequency domain analysis
Wavelet-Packet
- 基于混合信号的小波包分解技术在故障特征提取中的应用-Feature Extraction Using Multisignal Wavelet Packet Decomposition
ConditonIndex
- MTLAB常用故障特征提取函数,包括统计量、小波熵、高阶统计量、尺度熵、相关熵等函数-MATLAB functions of fault feature extraction
p_wavelet
- 小波分解轴承故障诊断代码，包括特征提取，用的数据是西储大学轴承数据(Wavelet decomposition bearing fault diagnosis code, including feature extraction, the data used is the West Park University bearing data)
代码
- 基于emd,eemd的滚动故障特征提取的代码，含完整的emd，eemd算法(Empirical Mode Decomposition)
vmd
- 变分模态分解,用于分解各种信号，可用来故障诊断，特征提取。(Variational mode decomposition, used to decompose various signals, can be used for fault diagnosis and feature extraction.)
order
- matlab实现的阶次分析算法，用于变转速机械故障特征提取，可运行，包含寻找脉冲时刻，等角度时刻，数字跟踪滤波，样条差值等步骤(The order analysis algorithm realized by Matlab is used to extract the fault features of variable speed machinery. It can be operated, including the steps of finding impulse moment, equa
order
- matlab阶次分析，matlab实现的阶次分析算法，用于变转速机械故障特征提取，可运行，包含寻找脉冲时刻，等角度时刻，数字跟踪滤波，样条差值等步骤(Matlab order analysis, the order analysis algorithm realized by MATLAB, is used to extract the fault features of variable speed machinery. It can be operated, including findin
时域特征和频域特征
- MATLAB的轴承故障时域特征和频域特征提取(Bearing fault time domain feature and frequency domain feature extraction)