Analog circuit fault diagnosis using lifting wavelet transform and SVM

2010 ◽  
Vol 24 (1) ◽  
pp. 17-22 ◽  
Author(s):  
Guoming Song ◽  
Houjun Wang ◽  
Hong Liu ◽  
Shuyan Jiang
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Analog Circuit ◽  
Lifting Wavelet Transform ◽  
Lifting Wavelet ◽  
Circuit Fault Diagnosis

The Application of Improved SVM in Mixed Circuit

2012 ◽  
Vol 224 ◽  
pp. 493-496 ◽  
Author(s):  
Huai Long Wang ◽  
Qiang Pan ◽  
Hong Liu
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Small Samples ◽  
Lifting Wavelet Transform ◽  
Fault Features ◽  
Diagnosis Method ◽  
Lifting Wavelet ◽  
Current Characteristics ◽  
Mixed Circuit ◽  
Better Than

In order to improve the speed and the rate of fault diagnosis in mixed circuit, this paper introduces a new fault diagnosis method. Through extracting fault features of current characteristics effectively and applying to Improved SVM, the ability of pattern recognition will be better than the traditional BP Neural Network and Single SVM, especially in small samples or non-linear cases. Meanwhile, this paper presents the lifting wavelet transform in order to obtain the feature information accurately. The accuracy of fault diagnosis can greatly enhance by discussing the Improved SVM combined with lifting wavelet transform in a specific monostable trigger. That points out a new direction for the fault diagnosis of mixed circuit.

Research of Fault Diagnosis of Coalmine Motor Bearings Based on Scale Adaptive Lifting Wavelet Transform

2013 ◽  
Vol 433-435 ◽  
pp. 494-498
Author(s):  
Jian Wu ◽  
Nan Wu ◽  
Feng Lv
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Vibration Signal ◽  
Electrical Equipment ◽  
Variable Load ◽  
Mining Equipment ◽  
Lifting Wavelet Transform ◽  
Signal Characteristics ◽  
Fault Diagnosis System ◽  
Lifting Wavelet

For Rolling of the mine key equipment is damaged easily the problem which is machinery fault diagnosis,through the failure mechanism of the reload / variable load conditions and the weak fault signal characteristics of coal mine electrical equipment bearing are analyzed, a more refined analysis of the vibration signal and achieve coal mining equipment online monitoring and Intelligent Fault Diagnosis system is constructed directly by scale adaptive lifting wavelet transform

DWT and Lifting Wavelet Transform Based Robust Watermarking for Color Image

2015 ◽  
Vol 10 (11) ◽  
pp. 1127
Author(s):  
Nidaa Hasan Abbas ◽  
Sharifah Mumtazah Syed Ahmad ◽  
Wan Azizun Wan Adnan ◽  
Abed Rahman Bin Ramli ◽  
Sajida Parveen
Keyword(s):  
Wavelet Transform ◽  
Color Image ◽  
Robust Watermarking ◽  
Lifting Wavelet Transform ◽  
Lifting Wavelet
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