Design of Gearbox Fault Diagnosis System Using Empirical Mode Decomposition Algorithm and LabVIEW Software

2011 ◽  
pp. 107-112
Author(s):  
Ling Zhang
Keyword(s):  
Fault Diagnosis ◽  
Empirical Mode Decomposition ◽  
Decomposition Algorithm ◽  
Diagnosis System ◽  
Labview Software ◽  
Mode Decomposition ◽  
Fault Diagnosis System

Monitoring Point Configuration of Gearbox Based on EEMD and VPRS

2013 ◽  
Vol 347-350 ◽  
pp. 237-240
Author(s):  
Hui Ling Liu ◽  
Hong Xia Pan ◽  
Ai Yu Wang
Keyword(s):  
Fault Diagnosis ◽  
Empirical Mode Decomposition ◽  
Rough Set ◽  
Ensemble Empirical Mode Decomposition ◽  
Decision Table ◽  
Monitoring Point ◽  
Mode Decomposition ◽  
Fault Diagnosis System ◽  
Variable Precision Rough Set ◽  
Approximate Dependence

To gain the sensitive fault information, proper sampling point configuration is essential and important. A method based on ensemble empirical mode decomposition and variable precision rough set is proposed to optimize the monitoring points in the gearbox fault diagnosis system. First, the vibration signal was processed by ensemble empirical mode decomposition, the energetic characteristic vector can be got by the intrinsic mode functions. Samples in different conditions constructed the decision table, each monitoring point corresponded to a decision table. Second, the approximate dependence values of condition attributes to decision attributes of every monitoring point were got by variable precision rough set. Finally, the importance of the sampling points was achieved by the approximate dependence value. The experimental results show the method is effective and feasible for the monitoring points configuration, and it can minimize the impact of noise as well as improve the efficiency and accuracy of the fault diagnosis system.

scholarly journals Research on Fault Diagnosis System of a Diesel Engine Based on Wavelet Analysis and LabVIEW Software

2014 ◽  
Vol 7 (18) ◽  
pp. 3821-3836
Author(s):  
Eidam Ahmed Hebiel ◽  
Zhu Zhou ◽  
Dong Sheng Wang ◽  
Liu Jie ◽  
Mohamed Ahmed Elbashier ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Diesel Engine ◽  
Wavelet Analysis ◽  
Diagnosis System ◽  
Labview Software ◽  
Fault Diagnosis System

Remote Fault Diagnosis System Based on EMD and SVM for Heavy Rolling-Mills

2014 ◽  
Vol 889-890 ◽  
pp. 681-686 ◽  
Author(s):  
Jin Fei Liu ◽  
Ming Chen ◽  
Jia Yun Gu ◽  
Lu Cheng
Keyword(s):  
Fault Diagnosis ◽  
Fault Location ◽  
Prototype System ◽  
Diagnosis System ◽  
Health Trends ◽  
Hilbert Huang Transform ◽  
Mode Decomposition ◽  
Healthy State ◽  
Fault Diagnosis System ◽  
Remote Fault Diagnosis

Aiming at the requirements of fault diagnosis for heavy mills, the architecture of remote fault diagnosis system based on EMD and SVM for heavy mills is built. Then the function of 3 main subsystems in the prototype system is introduced: Pattern recognition subsystem is used to evaluate healthy state of equipment with SVM classification algorithm; Fault location subsystem is used to fix fault position in the equipment with the method of Empirical Mode Decomposition and Hilbert-Huang Transform; Remaining life prediction subsystem is used to make a prediction of equipments health trends with SVM regression algorithm. At last, a remote fault diagnosis system based on website is established.

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