(Thisinformationisthefunctionasfollows:theuseofmathematicalstatisticalmethodsandtimeseriesanalysisoftheoriginalvibrationsignalanalysis,toobtainthecorrespondingtime-domain,frequencydomain,frequencydomainandtime-seriesmodelparametersandasacharacteristicparameter,andthendistinguishbetweentheuseofdistancetechnologyassess,selectthecharacteristicsofsensitiveparametersastheART-similarityclassifierinputandfortraining,thefinalperformanceofthedevicecanidentifythestate.YU-basednormofthebearingpreloadstatusindifferentanalysissystemsforfeedingthedatacollectedsamplesknowbeforehandthatthecorrespondingstate,canmakeuseofnorm-basedYUsupervisionofART-SimilarityClassifierdiagnosisofthem.Yu-basednormfortheART-Similarityofthealgorithm,IuploadedthefileshallbethealgorithmMATLABcode,matlab,theyhavereplacedthefileonthe"ryu0jin32feat.txt""ryu1jin32feat.txt""ryu2jin32feat.t) - IMDN开发者社群-imdn.cn">
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jingeiARTYU

于 2010-01-22 发布 文件大小:296KB
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  本资料的功能为：运用数学统计方法和时间序列分析方法对原始振动信号进行分析，获取相应的时域，频域，频域及时间序列模型参数并以此作为特征参数，然后运用距离区分技术进行评估，选取敏感的特征参数作为ART-similarity分类器的输入并进行训练，最后便可识别出设备的性能状态。 基于YU范数对承不同预紧状态的分析，针对进给系统所采集的数据样本事先不知其对应的状态时，则可利用基于YU范数的ART-Similarity监督分类器对其进行诊断分析。针对基于Yu范数ART-Similarity的算法，我上传的文件即为该算法的MATLAB代码，在matlab中，把文件中的关于"ryu0jin32feat.txt" "ryu1jin32feat.txt" "ryu2jin32feat.txt" "ryu3jin32feat.txt" "ryu4jin32feat.txt" "ryu5jin32feat.txt"文件的路径修改正确，即可正常运行，这些文件的主函数为"jingeiART.m"(This information is the function as follows: the use of mathematical statistical methods and time series analysis of the original vibration signal analysis, to obtain the corresponding time-domain, frequency domain, frequency domain and time-series model parameters and as a characteristic parameter, and then distinguish between the use of distance technology assess, select the characteristics of sensitive parameters as the ART-similarity classifier input and for training, the final performance of the device can identify the state. YU-based norm of the bearing preload status in different analysis systems for feeding the data collected samples know beforehand that the corresponding state, can make use of norm-based YU supervision of ART-Similarity Classifier diagnosis of them. Yu-based norm for the ART-Similarity of the algorithm, I uploaded the file shall be the algorithm MATLAB code, matlab, they have replaced the file on the "ryu0jin32feat.txt" "ryu1jin32feat.txt" "ryu2jin32feat.t)

文件列表：

ARTExample.m
ARTYUexample.m
ARTYUnorm_Activate_class.m
ARTYUnorm_Add_New_class.m
ARTYUnorm_Calculate_Match.m
ARTYUnorm_classify.m
ARTYUnorm_Complement_Code.m
ARTYUnorm_Create_Network.m
ARTYUnorm_Learn.m
ARTYUnorm_Update_Weights.m
ARTYUtezhen.asv
ARTYUtezhen.m
ART_Activate_Categories.m
ART_Add_New_Category.m
ART_Calculate_Match.m
ART_Categorize.m
ART_Complement_Code.m
ART_Create_Network.m
ART_Learn.m
ART_Update_Weights.m
ART_YUnorm.m
feat32discriARTYUjingei.asv
feat32discriARTYUjingei.m
fig.m
gyihua.m
hs_err_pid2896.log
jingeiART.asv
jingeiART.m
jingeiARTYUnorm.asv
jingeiARTYUnorm.m
jingeiPCAyunorm.asv
jingeiPCAyunorm.m
pca.m
ryu0jin32feat.txt
ryu1jin32feat.txt
ryu2jin32feat.txt
ryu3jin32feat.txt
ryu4jin32feat.txt
ryu5jin32feat.txt
yu0jin32feat.txt
yu1jin32feat.txt
yu2jin32feat.txt
yu3jin32feat.txt
yu4jin32feat.txt
yu5jin32feat.txt

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