搜索资源列表
bearigout
- 轴承外环故障诊断,故障设置为外环局部剥落,故障特征频率为外环通过频率或倍频理论计算得到475.6Hz.-Bearing outer ring fault diagnosis, fault set to the outer ring local spalling, the failure characteristic frequency for the outer ring through the frequency or frequency theoretical calculations 47
xiaobosuanfa
- 采样频率 fs=10000 轴承外环故障信号 fid=fopen( bearingout.dat , r ) 故障 N=1024 xdata=fread(fid,N, int16 ) fclose(fid) xdata=(xdata-mean(xdata))/std(xdata,1) 时域波形 figure(1) plot(1:N,xdata) xlabel( 时间 t/n ) ylabel( 电压 V/v )
bearing-fault-frequency-calculation
- 故障频率计算程序,计算轴承各部件的故障频率-Failure rate calculation program to calculate the bearing parts of the fault frequency
nnt
- 应用遗传算法进行电机运行故障检测,分别为电机轴承滚珠故障、电机轴承内圈故障、电机轴承滚珠和内圈组合故障,其中以40组数据为训练样本,4组数据为测试样本。-Motor fault detection based on Genetic Algorithms,Motor ball bearing failure, the the motor bearing inner ring failure, the motor bearing balls and inner ring combination fa
f14_1xiugai
- 轴承外圈故障——利用小波变换检测轴承外环故障-Bearing outer ring failure- using wavelet transform outer bearing fault detection
332
- 齿轮箱早期的故障信号往往十分微弱,信噪比低,这大大限制了已有诊断方法在早期诊断中的应用,因此如何获取真实的振动信号是提高齿轮箱早期故障诊断质量的关键,独立分量分析(ICA)为此提供了一种新的思路。文 中研究了ICA在齿轮箱故障早期诊断中的应用,首先分析了齿轮箱的混合振动信号模型,然后针对具体的轴承故障进行了实验,并使用快速ICA算法分离出轴承的振动信号-The early gearbox fault signal is often very weak, low signal-to-noise
mainn
- 用于绘制滚动轴承故障的频谱图和包络解谱图,从而判断轴承故障-Used to draw the rolling bearing fault frequency spectrum and spectral envelope solutions, in order to determine bearing failure
Bearing_failure_analysis
- 共振解调,轴承故障分析程序,对故障信号进行小波分析,获取轴承故障信息-Demodulated resonance, bearing failure analysis program, the fault signal wavelet analysis for bearing fault information
kpca
- 核主成分分析,用于轴承故障,人面识别,水位分布等的数据非线性提取。-Kernel principal component analysis for data bearing failure, human face recognition, water distribution and other non-linear extraction.
Fast-Kurtogram
- 轴承故障谱峭度分析,打开直接运行,包含包络谱分析-Bearing failure analysis of spectral kurtosis, open directly run, including envelope spectrum analysis
bearing-envelope-analysis-
- 对轴承振动信号进行滤波和包络频谱分析,可通过包络谱发现轴承故障,也可用于其他故障诊断的研究,程序已调试通过-Bearing vibration signal filtering and envelope spectrum analysis, bearing failure can be found through the envelope spectrum can also be used to study other troubleshooting procedures have been d
lly1
- 针对滚动轴承故障信号具有非平稳、非高斯的特点,提出了将时域分析与小波分析相结合的方法对滚动轴承进行故障诊断。在研究不同信号分析方法理论的基础上,以滚动轴承外圈故障振动信号为例,采用多种信号处理方法进行了分析。结果表明,各种分析方法在分析轴承故障时的特点各不相同,在实际使用中,可将时域分析与小波分析综合使用,实现轴承状态的实时监测与故障的准确定位。-For rolling bearing fault signals have non-stationary, non-Gaussian, we pro
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 power spectrum simulation map
q
- 文件为matlab程序段,为轴承外圈脉冲故障情况下的时频信号-File matlab program segment, the bearing outer ring pulse frequency signal in case of failure
fx
- 常用的信号频域分析程序,如自相关分析,包络解调,轴心轨迹绘制等程序。附加轴承故障数据。-Commonly used frequency domain signal analysis program, such as auto-correlation analysis, envelope demodulation, Orbit drawing and other procedures. Additional bearing failure data.
pinpu_xcorr
- 此程序主要用于处理轴承和齿轮故障,先进行傅里叶变换,然后在信号频域内做频谱自相关,通过频谱自相关,可以识别频谱中的周期性调制信息-This procedure is mainly used for processing the bearing and gear failure, Fourier transform first, and then the signal in the frequency domain spectrum autocorrelation, through spectru
Rolling bear
- 采用PCA白化和K均值对轴承故障进行聚类分析(Clustering analysis of bearing failure by PCA whitening and K mean)
bearingFaultDiagnosisa
- 包含轴承故障数据,来源于MFPT(Machinery Failure Prevent Technology)论坛,分四组训练数据和测试数据; 数据可直接做频谱分析,效果很好(contain bearing faults data sets, 4 train datas and 4 test datas, can be used for FFT/envespectrum analysis, and you will get perfect effects.)
fangzhen
- 利用MATLAB程序仿真轴承内圈不同故障程度信号。仿真信号X由故障信号 与白噪声r两部分构成(Use MATLAB program to simulate the signal of different failure degree of bearing inner ring. Simulation signal X consists of two parts: fault signal and white noise r)