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Untitled5
- 求峭度，有效值，均方值，还有峰度，是对风力发电机组数据的必要东西-Seeking kurtosis, RMS, mean square value, and kurtosis, the data is necessary for wind turbine things
program-and-data-sets
- 本程序是用于在时域中分析处理轴承故障数据的，提取了各种时域的特征参数，包括均值，有效值，峭度，裕度指标，波形指标等等 适合初学者用于轴承的故障诊断中对参数的提取。（附上轴承故障数据3类共21组 正常、内圈、外圈）-This procedure is used in the time domain analysis of bearing fault data processing to extract the characteristic
Pack-Kurtogram
- 快速计算一维信号的塔式谱峭度图，选择谱峭度最大值区间，方便确定所需滤波器中心频率及带宽。-Computes the fast kurtogram of signal x.This fast algorithm uses a pyramidal decomposition of the signal into a user-specified number of levels (a good choice is nlevel = 8).
MyIndex
- 主要功能是计算均值、标准差、方差、偏斜度、峭度、 峰峰值、方根幅值、平均幅值、峰值、 波形指标、峰值指标、脉冲指标、裕度指标。-The main function is to calculate the mean, standard deviation, variance, skewness, kurtosis, peak to peak, the square root of amplitude, average amplitude,
five
- 计算声发射时域信号特征值：裕值，振幅因子FK、fc，峭度，-Calculation of acoustic emission time-domain signal characteristic values: margin value, the amplitude factor FK, fc, kurtosis,
MyIndex
- 本程序是计算振动信号各种参数的实验程序。 主要功能是计算均值、标准差、方差、偏斜度、峭度、峰峰值、方根幅值、平均幅值、峰值、波形指标、峰值指标、脉冲指标、裕度指标。-This procedure is experimental procedure of the calculation of the various parameters of the vibration signal. The main function is to
LDA_TrainTest_5CV
- 提取数据波形时域特征（绝对幅值、平均值、峭度、过零点）并且用LDA分类-Time-domain waveform data extraction features (absolute amplitude, mean, kurtosis, zero crossing) and classification with LDA
xinhaochuli
- 近期成果，与大家分享：奇异值分解、小波降噪、zoom细化 谱峭度 和滤波器设计，共勉-Recent achievements to share with you: singular value decomposition, wavelet noise reduction, zoom refined spectral kurtosis and filter design, encouragement
shiyuzhibiao16
- 信号特征提取16个时域、频域指标 均值、标准差、方差、 偏斜度指标、峭度指标、 峰-峰值、峰值、均方幅值、平均幅值、方根幅值、波形指标、峰值指标-Signal feature extraction 16 time domain, frequency domain mean, standard deviation, variance, skewness index, kurtosis index, peak- peak, mean s
dual-tree
- 首先将非平稳的故障振动信号进行双树复小波包分解，得 到不同频带的分量；然后对每个分量求其峭度值和相关系数并进行比较；最后选取峭度值和相关系数较大的分量 进行软阈值降噪和双树复小波包重构，即可有效地消除振动信号中噪声的干扰，同时保留信号中的有效信息即实 现了故障特征信息的提取。-In view of the above situation, a new fault diagnosis method is proposed
Time-domain-index-calculation
- 信号的一些时域指标计算，有效值，峰峰值，峭度，能量，倾斜度等-Calculation, effective value, some indexes of time domain signal peak, kurtosis, energy, gradient
TimeDomainFeature
- 比较全的信号统计特征的调用程序，包括均值MV, 均方根值RMS, 方根幅值RA, 绝对平均值AA, 偏斜度SKEW, 峭度KV, 方差VAR, 最大值maxW, 最小值minW, 峰-峰值PPV-Compare all the statistical characteristics of the signal caller, including mean MV, RMS value RMS, root amplitude RA, abs
baoluopu
- 对一段振动信号emd分解后，求每个分量的峭度值，选取峭度最大的分量，求其包络谱，能够明显看出特征频率。-After a period of vibration signal emd decomposition, seeking kurtosis value of each component, the largest component of kurtosis, seeking its envelope spectrum, can o
Fast--Kurtogram
- 将信号分为不同频带，计算峭度值，选择峭度值最大的频带解调分析-divide The signal into different frequency bands, calculate kurtosis value, the maximum kurtosis band demodulation
cepstrum_kurtosis
- 此程序先通过倒频谱解卷积，然后通过时域滤波，进而进行逆傅里叶变换，最后计算解卷积后的信号峭度值。-This program through cepstrum solution of convolution first, then by time domain filtering, then the inverse Fourier transform, the signal kurtosis value after calculation
MyIndex
- matlab求解峭度值，峰峰值，方差，均方差，协方差，裕度等统计学特征-Matlab solution of kurtosis, peak peak value, variance, variance, covariance, margin and other statistical characteristics
峭度指标VI
- 峭度指标是非平稳信号故障诊断的重要参数。峭度指标对信号中的冲击成分十分敏感，冲击成分能量越大，其峭度值就会越大，在故障诊断的时域分析中十分重要。本文件中将其独立做成了一个子vi，便于程序直接调用。(Kurtosis index is an important parameter of non-stationary signal fault diagnosis. The kurtosis index is very sensitive t
tezhengzhi
- 时域指标特征提取：包含均值、方差、最大最小值，峭度指标等16个指标(Time domain index feature extraction: including the mean, variance, maximum and minimum values, kurtosis indicators and other 16 indicators)
add_noise_pinyutu
- 进行纯净信号和加噪信号的时频域显示，及其包络图显示，并计算加噪信号的信噪比、互相关系数、峭度值，对信号进行离散余弦变换。(The time-frequency domain display of pure signal and noise-added signal and its envelope diagram display are carried out, and the signal-to-noise ratio, correl
优化K值
- 分解信号,能量差值优化K，峭度，样本熵，排列熵(Decomposition of signal, optimization of energy difference value K, kurtosis, sample entropy, permutation entropy)