Bearing Performance Degradation Assessment Using Lifting Wavelet Packet Symbolic Entropy and SVDD
نویسندگان
چکیده
منابع مشابه
Application of Wavelet Packet Entropy Flow Manifold Learning in Bearing Factory Inspection Using the Ultrasonic Technique
For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing factory quality. The data were analyz...
متن کاملECG Classification Using Wavelet Packet Entropy and Random Forests
The electrocardiogram (ECG) is one of the most important techniques for heart disease diagnosis. Many traditional methodologies of feature extraction and classification have been widely applied to ECG analysis. However, the effectiveness and efficiency of such methodologies remain to be improved, and much existing research did not consider the separation of training and testing samples from the...
متن کاملRoller Bearing Fault Diagnosis Based on Nonlinear Redundant Lifting Wavelet Packet Analysis
A nonlinear redundant lifting wavelet packet algorithm was put forward in this study. For the node signals to be decomposed in different layers, predicting operators and updating operators with different orders of vanishing moments were chosen to take norm l(p) of the scale coefficient and wavelet coefficient acquired from decomposition, the predicting operator and updating operator correspondi...
متن کاملRolling Bearing Fault Diagnosis Based on Wavelet Packet Decomposition and Multi-Scale Permutation Entropy
This paper presents a rolling bearing fault diagnosis approach by integrating wavelet packet decomposition (WPD) with multi-scale permutation entropy (MPE). The approach uses MPE values of the sub-frequency band signals to identify faults appearing in rolling bearings. Specifically, vibration signals measured from a rolling bearing test system with different defect conditions are decomposed int...
متن کاملIdentification of Surface EMG Signals Using Wavelet Packet Entropy
This paper introduces a novel and simple algorithm to extract the feature from Surface EMG signals recorded from the skin surface over forearm muscles. Surface EMG signal is decomposed into 16 frequency bands (FB) by wavelet packet transform (WPT), and then wavelet packet entropy (WPE) of every surface EMG signal is calculated by its relative wavelet energy in every FB. WPE is regarded as the f...
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: Shock and Vibration
سال: 2016
ISSN: 1070-9622,1875-9203
DOI: 10.1155/2016/3086454