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Untitled2
- 基于小波变换的电机轴承故障诊断的应用与开发-Application and development of motor bearing fault diagnosis based on wavelet transfor
AAA
- 轴承故障信号的诊断方法，时延相关预处理对振动信号做预处理，可以起到解调的作用-Diagnosis bearing fault signal delay associated pretreatment on the vibration signal preprocessing, can play a role demodulated
guzhangzhenduan
- 之前写的关于单盘转子和轴承故障诊断的小程序-Before writing about the single-disc rotor and the bearing fault diagnosis applet
LMD
- 自己变成的LMD算法，用于轴承故障诊断方向的诊断信号进行分析。能实现对轴承故障信号进行有效提取，分为多个IMF分量和参与分量。-LMD algorithms themselves into, the diagnostic signals for the direction of the bearing fault diagnosis are analyzed. Bearing fault signal can be achieved effectively extracted into a pl
svd
- svd算法用于滚动轴承故障诊断中，该算法通过对故障信号进行重构，能够有效提高故障频率。-svd algorithm for ball bearing fault diagnosis, fault signal by the algorithm to reconstruct, can effectively improve the fault frequency.
MATLAB
- MATLAB希尔伯特Hilbert变换求包络谱用于滚动轴承故障检测，对于滚动轴承故障信号进行包络普分析，确定其故障类型。-MATLAB Hilbert Hilbert transforms envelope spectrum for rolling bearing fault detection, fault signal for Rolling Cape envelope analysis to determine which type of fault.
Fault-Data-Sets
- matlab做的，关于滚动轴承振动信号故障诊断很重要的数据库，做机器学习的朋友可以看看啊！-Matlab do, on the rolling bearing vibration signal fault diagnosis is very important , machine learning friends can see ah!
BearingAnalysis
- bearing fault toolbox
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
harmonic
- 该功能主要是计算harmoonic小波变换的旋转设备状态监测的基于振动的轴承故障诊断。-The function basically is for computing Harmoonic wavelet transform for condition Monitoring of rotating equipments by vibration based bearing fault diagnosis.
Bearing-frequency-calculate
- 所写的Labview程序可一次性计算出轴承的故障特征频率，方便实用-Written Labview program can calculate a one-time fault characteristic frequency of the bearing, convenient and practical
failure-diagnosis-method
- 文章描述的是EEMD、Renyi熵和SVM结合的滚动轴承的故障诊断过程。-The article describes the EEMD, Renyi entropy and SVM combination of rolling bearing fault diagnosis process
gongzhenjiantiao
- 用于对于轴承振动信号的共振解调程序，便于对轴承故障信号进行分析-Used for resonant demodulation of bearing vibration signals for easy analysis of bearing fault signals
VMD-Parameter-Estimation
- 变分模态分解在信号分解精度和噪声鲁棒性方面具有明显优势，但需预先确定模态数K，而目前K 只能靠先验知识进行预估，如果预估的K 与实际信号存在差异，会导致分解误差较大。针对以上问题，利用EMD 不需预先设定模态数的自适应分解特点，通过对EMD 分解结果的分析，进行VMD 分解模态数的估计，并通过仿真信号分析及滚动轴承故障信息提取-Variational modal decomposition has obvious advantages in signal decomposition accura
EEMD
- 信号处理，轴承故障，matlab，EMD，EEMD，故障，经验模态分解-Signal processing，Bearing fault，emd，eemd
pinyutezheng
- 一维信号频域特征提取，可用于轴承故障诊断和趋势预测-Wherein the one-dimensional frequency domain signal extraction, can be used to predict bearing Fault Diagnosis and
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)
轴承故障频率计算器V3.0_2017.5.23
- 对于轴承故障频率的计算，皮肤界面的修改，相应的计算器软件算法(Calculation of bearing fault frequency)
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)
motor emd
- 小波变换及经验模式分解方法在电机轴承早期故障诊断中的应用(Study on the method of incipient motor bearing fault diagnosis based on wavelet transform and EMD)