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cluster_VMDaFCM_casedat
- 为了精准、稳定地提取滚动轴承故障特征，提出了基于变分模态分解和奇异值分解的特征提取方法，采用标准模糊C均值聚类(fuzzy C means clustering, FCM)进行故障识 别。对同一负荷下的已知故障信号进行变分模态分解，利用 奇异值分解技术进一步提取各模态特征，通过FCM形成标准聚类中心，采用海明贴近度对测试样本进行分类，并通过计算分类系数和“卜均模糊嫡对分类性能进行评价，将该方法 应用于滚动轴承变负荷故障诊断。通过与基于经验模态分解的特征提取方法对比，该方法对标准FCM
VMD
- 本文介绍了一种自适应信号分解新方法-变分模态分解，并且针对滚动轴承早期故障识别困难这一问题，提出了基于VMD的诊断方法。-In this paper, a new adaptive signal decomposition method, variational mode decomposition, is introduced. Aiming at the problem of early fault identification of rolling bearing, a diagnosis
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.)
基于小波的VMD程序
- 将小波滤波方法与VMD算法结合，提取故障信息(Wavelet and VMD algorithm are combined to extract fault information)
基于VMD和Teager能量谱的滚动轴承故障特征提取
- 基于VMD和1_5维Teager能量谱的滚动轴承故障特征提取_向玲(To extract _ Ling fault features of rolling bearing VMD and 1_5 dimension Teager based on energy spectrum)
VMD
- VMD方法能够使一个多频带的故障信号，分解出具有单个频带的子信号，然后使用共振解调方法可实现故障信号的诊断。(The VMD method can make a multi band fault signal decompose the subsignal with a single frequency band, and then use the resonance demodulation method to realize the diagnosis of the fault signal
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.)
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.)
一些数据驱动的轴承故障诊断程序
- 一些数据驱动的轴承故障诊断程序，总结不容易，希望大家好好利用。
VMD
- 基于VMD的机车滚动轴承故障，变转速的测量(Measurement of Rolling Bearing Fault and Variable Speed of Locomotive Based on VMD)
VMD优化
- 基于VMD的机车滚动轴承故障，变转速的测量，VMD的优化(Measurement of Rolling Bearing Fault and Variable Speed of Locomotive Based on VMD)
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)
变分模态方法
- 变分模态分解方法能够使一个多频带的故障信号，分解出具有单个频带的子信号，然后使用共振解调方法可实现故障信号的诊断。(VMD method can decompose a multi band fault signal into a single band sub signal, and then use resonance demodulation method to realize fault signal diagnosis.)
灰狼GWOVMD
- 算法是基于灰狼优化算法GWO优化VMD，可以大大提高VMD的分类准确率，提高优化时间。(This algorithm is based on GWO optimization VMD, which can greatly improve VMD classification accuracy and optimization time.)
鸡群CSOSVM
- 本算法是基于鸡群优化算法CSO优化SVM，可以大大提高VMD的分类准确率，提高优化时间。(This algorithm is based on CSO to optimize SVM, which can greatly improve the classification accuracy of VMD and improve the optimization time.)
蝙蝠BASVM
- 本算法是基于蝙蝠优化算法BA优化SVM，可以大大提高VMD的分类准确率，提高优化时间。(This algorithm is based on bat optimization algorithm BA to optimize SVM, which can greatly improve the classification accuracy of VMD and improve the optimization time.)