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对轴承故障振动信号的matlab小波分析程序
- 对轴承故障振动信号的matlab小波分析程序，能完成对故障特征频率的提取,Of bearing fault vibration signals matlab wavelet analysis procedures, can finish on the fault characteristic frequency extraction
Wavelet.rar
- 小波包变换分析信号的MATLAB程序，可用于提取故障特征向量,Wavelet packet transform analysis of signals in MATLAB procedures, can be used to extract fault feature vector
bear
- 这个是直升机齿轮箱故障特征提取的程序。用的是小波变化加上hilbert包络的方法，简单实用，对大型旋转设备的故障检测有很广泛的应用！-This is a Helicopter Gearbox Fault Feature Extraction procedures. Changes using a wavelet plus hilbert envelope method is simple and practical, on large rotating equipment fault detec
Extractionoffaultfeaturevector
- 用小波包提取故障特征向量并归一化，很实用，论文里的部分程序-Extracted using wavelet packet fault eigenvector and normalized, it is useful, some of the procedures in the thesis
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- 三篇关于小波变换的文章，主要用在故障诊断领域的主要利用小波变换来提取故障特征。（本文档需要用CAJViewer打开）-Three articles on the wavelet transform, is mainly used in the field of fault diagnosis using wavelet transform to extract the main fault feature. (This document will need CAJViewer open)
Untitled
- 利用小波变换实现对故障信号的特征提取 构造特征向量-Wavelet transform feature extraction of fault signals structural feature vector
xsj
- 基于小波变换的碰磨故障信号的特征提取，可以画出信号原图，轴心轨迹，频谱图以及多层小波变换的重构信号-Based on wavelet transform rubbing fault signal feature extraction, the signal can be drawn artwork, orbit, spectrum and signal reconstruction wavelet multi-
xiaobobao-BPwangluo
- 小波包和BP神经网络在齿轮箱故障诊断中的应用，本文对齿 轮箱振动信号应用小波包分解提取故障特征向量，进一步用特征向量训练前向传播BP人工神经网络。-xiaobobao、BP、gearbox fault detection
xiaobobao-BP-zhoucheng-zhenduan-
- 基于小波包特征向量与神经网络的滚动轴承故障诊断。：基于故障轴承的特征提取，提出了将小波包分析与神经网络结合的滚动轴承故障诊断方法。对滚动轴承信号进行3层小波包分解，构造小波包特征向量作为故障样本，用训练好的BP神经网络进行故障诊断，试验结果表明，该方法能够有效地诊断出滚动轴承的故障类型。-Fault Diagnosis of Rolling Bearings Based on W avelet Packet Energy Eigenvector and Neural Network
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
guzhangzhenduan
- 这是一本介绍旋转机械故障诊断的论文，采用小波变换方法提取故障特诊，我导师的一个项目就是用的这种特征提取方法，比较成功。-this is a book that introduce the matheds of error dector and we have tested it in our project.
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.
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
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
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)
基于小波包提取轴承故障
- 基于小波包变换对信号进行分解，提取机器轴承故障的特征信号进行损伤识别，(The signal is decomposed based on wavelet packet transform, and the characteristic signals of machine bearing faults are extracted to identify the damage,)
xiaobo
- 对故障数据的小波包分解与信号重构、小波包能量特征提取 暨 小波包分解后实现按频率大小分布重新排列，并进行降噪处理。(After wavelet packet decomposition and signal reconstruction, wavelet packet energy feature extraction and wavelet packet decomposition, the fault data can be rearranged according to the frequ