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wavelet-in-signal-processing
- 小波变换在信号处理中的应用,包括分解，去噪，以及检测传感器故障等-Wavelet transform in signal processing applications, including decomposition, denoising, and detection of sensor failure, etc.
EMD
- LABVIEW下实现自动的EMD分解，广泛应用于故障诊断系统-LABVIEW automatically under the EMD decomposition is widely used in fault diagnosis system
18-7
- 利用小波包分解4种不同间隙的局部碰磨故障，可查看故障的频谱。-The use of wavelet packet decomposition of 4 different partial gap Rubbing failure, failure to see the spectrum.
wavelet
- matlab小波分析源程序，包含小波分解去噪，奇异点检测，实际工程中的故障检测，图像处理-matlab
EMD-Toolbox
- EMD的Toolbox及使用方法 经验模态分解（Empirical Mode Decomposition, 简称EMD）是由美国NASA的黄锷博士提出的一种信号分析方法.它依据数据自身的时间尺度特征来进行信号分解, 无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。正是由于这样的特点, EMD 方法在理论上可以应用于任何类型的信号的分解, 因而在处理非平稳及非线性数据上
WavletDecomposeTheFaultSignalPower
- 选用DB小波对故障电力信号进行分解，从图中可轻易判断出故障点。-DB wavelet used to decompose the fault signal power, from the figure can easily determine the point of failure.
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 Eigen
wvd
- 这是一个轴承故障分解程序，给予小波变换，小波去噪，小波重构与EMD相结合，有时频谱，边际谱，功率谱-This is a to bearing failure decomposition program given wavelet transform, wavelet denoising wavelet reconstruction combined with EMD, sometimes the spectrum, marginal s
xsj
- 关于一个轴承故障分解程序，里面包含小波去噪，重构等，还有EMD模态分解，并且还有各种功率谱仿真图-About a bearing failure decomposition process, which contains the wavelet de-noising, reconstruction, etc., as well as mode decomposition EMD, and there are a variety of p
VMD
- 可以实现滚动轴承的故障采集处理，变分模态分解法很强大(Rolling bearing fault acquisition and processing can be realized, and the variational modal decomposition method is very powerful)
_风力发电机组叶片故障诊断
- 风机叶片的裂纹和断裂是导致风机机组事故的重要因素之一，尽早诊断出风机叶片的 故障部位与故障程度，对安全生产具有意义重大。本文将叶片振动信号作为研究对象，利用小波分解方法对其进行信号分解，并与时域和频域方法处理结果进行对比分析，得出诊断结论。仿真结果表明: 小波分解方法可以更有效的获取故障特征信号，具有较高的故障诊断率。(The crack and fracture of fan blade is one of the importan
VMD.tar
- 将一个信号分解为几个模态分量，并且不会产生模态混叠现象，对信号的分解很清晰，大量应用于故障诊断。(A signal is decomposed into several modal components, and it does not cause modal aliasing. The decomposition of signals is very clear and widely used in fault diagnosis.)
轴承故障
- 轴承故障诊断，用于分析轴承外圈故障的经验模态分解(Bearing fault diagnosis)
故障诊断与容错控制课程设计报告
- 针对滚动轴承这种非平稳振动信号采用的小波包分解的方法来检测故障的存在，运用神经网络来实现故障的分类，还结合D-S理论融合了多个传感器的诊断结果，提高了故障诊断的准确性并通过实验仿真证实。(This course's job is to use the wavelet packet decomposition method for non-stationary vibration signals of rolling bearings t
rParabEmd__L
- 该程序对信号进行经验模式分解，可以用于故障信号处理，还可以与很对方法结合。如，排列熵，emd,vmd,等(This program performs the Empirical Mode Decomposition accordingly to the signal)
Kmeans故障聚类
- C语言做的聚类学习的旋转机械故障诊断，已经经过验证，可以作为参考。(C language clustering learning of rotating machinery fault diagnosis has been verified, and can be used as a reference.)
ITD分解
- 可以对机械故障信号进行分解，分解效果良好(The mechanical fault signal can be decomposed and the decomposition effect is good.)
基于EMD的包络谱进行故障诊断matlab程序实例
- 对原始信号进行EMD分解及包络解调，得出包络解调谱，分析出故障频率(The original signal is decomposed by EMD and demodulated by envelope. The spectrum of envelope demodulation is obtained and the fault frequency is analyzed.)
用于信号的EMD、EEMD、VMD分解
- 用于信号的分解、降噪和重构，实现故障诊断(Used for signal decomposition, noise reduction and reconstruction to realize fault diagnosis)