搜索资源列表
Statistic
- 数据驱动的统计学习方法，包括PLS、PCA、ICA等，可方便进行故障诊断研究-Data-driven statistical learning methods, including PLS, PCA, ICA, can do researching on fault diagnosis
immune
- 一种高效的免疫算法，可以被用来进行故障诊断。经过检测，效果较好。-A highly effient immune algorithm and can be used in the fault diagnosis field
FCM
- 可以实现聚类，结合神经网络、支持向量机等用于故障诊断。-Clustering can be achieved, combined with neural networks, support vector machines for fault diagnosis.
work
- 将神经网络应用于故障诊断，由此可提高故障诊断速度，可提高效率-The neural network fault diagnosis, this can increase the speed of fault diagnosis can improve the efficiency
dianjiguzhangzhenduan
- 用matlab编写的电机故障诊断的M文件，可以判断故障电机故障类型-Prepared using matlab M-file motor fault diagnosis, fault type motor failure can be judged
代码
- 隐Markov模型(简称为HMM)是在Markov模型的基础上发展而来的。由于实际问题比Markov模型所描述的问题更为复杂，观测到事件并不是与状态一一对应，而是通过一组观测概率分布相联系，这样的模型称为HMM。它是一个双重随机过程，其中之一是Markov链，这是一个基本的随机过程，描述状态之间的转移。另一个随机过程描述状态和观测变量之间的统计对应关系，这样，站在观察者的角度，只能看到观察值，不象Markov模型中的观测值和状态一一对应。(The implicit Markov model (H
自适应观测器故障诊断
- 利用自适应观测器进行故障诊断，matlab仿真，修改参数即可(Using adaptive observer for fault diagnosis, matlab simulation, modify the parameters can be)
GLP.rar
- 简单的神经网络故障诊断，代码自己可以看看(This is a neural network analysis of the bearing data of the West University of storage, the main data can be under the official website.)
emd+信息熵
- 可以实现机械EMD经验模态分解，提取特征量并利用神经网络进行模式识别故障类型(The empirical mode decomposition of mechanical EMD can be realized, feature quantity is extracted and neural network is used to identify the type of fault.)
模式识别应用于故障诊断
- 将模式识别和机械中的故障诊断结合。结合实例和程序，验证出方法的有效性，内附文档和代码，运行无错误。(Combining pattern recognition with fault diagnosis in machinery.The effectiveness of the method is verified by examples and programs.The artical is attached code and can be run without error.)
immunityFaultDiagnosis
- 人工免疫算法应用到故障诊断领域的实例代码，可以在Matlab中直接运行，可以进行适当的修改，对算法进行改进(The artificial immune algorithm is applied to the case code of the fault diagnosis field. It can be run directly in the Matlab, and can be modified properly to improve the algorithm.)
Genetic Algorithm with PHM
- 遗传算法与和机械故障诊断向结合的matlab程序，包括例子，少许修改即可自用。(Genetic algorithm and MATLAB combined with mechanical fault diagnosis, including examples, can be used by a small number of modifications.)
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.)
mckd
- 最大相关峭度反褶积，给定滤波器长度和周期T、位移数后可将与周期成分不相符成分默认为噪声成分，具有极强的降噪能力。(Maximum correlation kurtosis deconvolution, given the filter length and period T, displacement number, can default to the non-conforming component of the periodic component as the noise compone
rbf
- RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。 简单说明一下为什么RBF网络学习收敛得比较快。当网络的一个或多个可调参数（权值或阈值）对任何一个输出都有影响时，这样的网络称为全局逼近网络。由于对于每次输入，网络上的每一个权值都要调整，从而导致全局逼近网络的学习速度很慢。BP网络就是一个典型的例子。(RBF network
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.)
多尺度排列熵
- 多尺度样本熵程序，实例中用于一段轴承故障数据，简单易懂。MultiscalePermutationEntropy函数中的PermutationEntropy也可以单独拎出来计算单个样本熵。(The multi-scale sample entropy program, which is used for a section of bearing fault data in an example, is simple and easy to understand. The permutatione
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.)
包络谱诊断轴承故障
- 实现包络谱轴承故障诊断检测，通过matlab实现，可以直接演示(The envelope spectrum bearing fault diagnosis and detection is realized by MATLAB, which can be demonstrated directly)