Research on Fault Feature Extraction Method Based on FDM-RobustICA and MOMEDA
نویسندگان
چکیده
منابع مشابه
A Fast Localization and Feature Extraction Method Based on Wavelet Transform in Iris Recognition
With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This rese...
متن کاملResearch on Feature Extraction of Mechanical Fault Based on Orthogonal Local Fisher Discriminant Analysis
The basic problem of fault diagnosis is to extract the characteristic parameters and design the decision function according to the running state signals collected by the sensors. In addition, it also can find out the fault states. Due to the complexity of the operation state of the mechanical equipment, the state signal has the characteristics of large amount of data and high degree of nonlinea...
متن کاملMultiple Fault Diagnosis Research on Motors in Aluminum Electrolytic Based on ICA Feature Extraction
Motors as the actuator in the aluminum electrolysis process, mainly used for control the lifting of the anode to control the cell voltage, make the electrolytic tank keep in the best condition, once the motors failed, slot voltage will be out of control. This paper study on the fault of the motors in the process of aluminum electrolysis. In this paper adopts the EMD algorithm for various stator...
متن کاملFeature Extraction Method of Rolling Bearing Fault Signal Based on EEMD and Cloud Model Characteristic Entropy
The randomness and fuzziness that exist in rolling bearings when faults occur result in uncertainty in acquisition signals and reduce the accuracy of signal feature extraction. To solve this problem, this study proposes a new method in which cloud model characteristic entropy (CMCE) is set as the signal characteristic eigenvalue. This approach can overcome the disadvantages of traditional entro...
متن کاملA Method of Bearing Fault Feature Extraction Based on Improved Wavelet Packet and Hilbert Analysis
In order to supply a gap of current resonance vibration and STFT demodulation method applied to rolling bearing fault feature extraction of city rail vehicle, a fault diagnosis method for rolling bearing is presented, which is based on the integration of improved wavelet packet, frequency energy analysis and Hilbert marginal spectrum. When faults occur in rolling bearing, the energy of the roll...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2020
ISSN: 1024-123X,1563-5147
DOI: 10.1155/2020/6753949