• No results found

[PDF] Top 20 Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes

Has 10000 "Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes" found on our website. Below are the top 20 most common "Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes".

Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes

Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes

... applying wavelet transform to a signal, if the Shannon entropy measure of a particular scale is minimum then we can say that a major defect frequency component exists in the scale but, in the present study out of ... See full document

12

Fault diagnosis of gearboxes using LSSVM and WPT

Fault diagnosis of gearboxes using LSSVM and WPT

... system using a least square support vector machine ...Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and ... See full document

10

Thermal Image Based Fault Diagnosis of Gears using Support Vector Machines

Thermal Image Based Fault Diagnosis of Gears using Support Vector Machines

... [5], wavelet transform [6] and Hilbert transform [7] have also been formulated for diagnosing the inchoate defects in rotating ...acquired using vibration sensors are usually influenced by the choice of ... See full document

6

Research on Diagnosis of AC Engine Wear Fault Based on Support Vector Machine and Information Fusion

Research on Diagnosis of AC Engine Wear Fault Based on Support Vector Machine and Information Fusion

... As various oil sample analysis methods produce varied diagnosis data and dimensions, subsequent fusion Ⅶ will encounter some inconveniences. Therefore, pretreatment on original symptom data will be made to convert ... See full document

6

Support Vector Machine Based Fault  Diagnosis of Power Transformer Using k Nearest Neighbor Imputed DGA Dataset

Support Vector Machine Based Fault Diagnosis of Power Transformer Using k Nearest Neighbor Imputed DGA Dataset

... dataset using the k-nearest neighbor imputation method with two different distance metrics: Euclidean and ...Thereafter, using these imputed datasets as inputs, this study applies Support ... See full document

10

OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS 
FOR ONE MAGNETRON

OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON

... Support vector machine (SVM) is a relatively new machine learning approach based on the statistical learning theory (SLT) and the empirical risk minimization ...other machine learning ... See full document

11

Support Vector Machine based Decision for Induction Motor Fault Diagnosis using Air Gap Torque Frequency Response

Support Vector Machine based Decision for Induction Motor Fault Diagnosis using Air Gap Torque Frequency Response

... early fault detection and diagnosis permit condition-based maintenance to be efficient for the electrical machines during scheduled ...the fault detection problem, it is interesting to know if a ... See full document

7

To Prepare a Forecasting Proxy Server to Improve
          Hits Using SVM.

To Prepare a Forecasting Proxy Server to Improve Hits Using SVM.

... the support vector machine to build up the optimal classification brings difficulties, in [16] Jing Tang ...of fault characteristics and then use kernel density estimation method, proposed a ... See full document

6

Gear Fault Detection Using Recurrence Quantification Analysis and Support Vector Machine

Gear Fault Detection Using Recurrence Quantification Analysis and Support Vector Machine

... The current work involved investigating a mock-up of a helicopter gear box system. All of the test data was acquired by collaboration with the United Technologies Research Center (UTRC). The gear-train experimental setup ... See full document

23

Fault Detection and Diagnosis Using Support Vector Machines - A SVC and SVR Comparison

Fault Detection and Diagnosis Using Support Vector Machines - A SVC and SVR Comparison

... The support vectors utilize a hyperplane with maximum margin to separate different classes of data producing a satisfactory overall ...[9], fault detection [10-11] and modeling of nonlinear dynamical ... See full document

12

Detection and Classification of Tumor in Mammograms using Discrete Wavelet Transform and Support Vector Machine

Detection and Classification of Tumor in Mammograms using Discrete Wavelet Transform and Support Vector Machine

... Feature extraction techniques are used to extract the most discriminating features which represent various classes of images. The image properties of the extracted features are provided and compare with the unknown ... See full document

7

Application of Support Vector Machines to Fault Diagnosis and Automated Repair

Application of Support Vector Machines to Fault Diagnosis and Automated Repair

... ern machine learning techniques to the problem of Fault Diagnosis and Automated ...of using pattern recogni- tion techniques to determine correct repairs for faults from past production ... See full document

5

Optimum Parameters for Fault Detection in Bioreactor Using Support Vector Machine and Neural Network

Optimum Parameters for Fault Detection in Bioreactor Using Support Vector Machine and Neural Network

... robust fault detection and diagnosis (FDD) strategy will help in maintaining the quality of the product by early detection of ...of support vector machines (SVM) and artificial neural networks ... See full document

13

Artificial Intelligence Tools Aided decision for Power Transformer Fault Diagnosis

Artificial Intelligence Tools Aided decision for Power Transformer Fault Diagnosis

... intelligent fault classification approach for power transformer dissolved gas analysis ...(DGA). Fault diagnosis methods by the DGA and artificial intelligence (AI) techniques are implemented to ... See full document

8

Transformer Fault Diagnosis Based on Support Vector Machine and Cat Swarm Optimization

Transformer Fault Diagnosis Based on Support Vector Machine and Cat Swarm Optimization

... transformer using Dissolved Gas Analysis (DGA) method is very ...their diagnosis accuracies need ...a Support Vector Machine (SVM) based faults diagnosing method in the ...transformer ... See full document

5

Research of Sensor Fault Detection and Diagnosis for EMB System Based on CSA-SVM Model

Research of Sensor Fault Detection and Diagnosis for EMB System Based on CSA-SVM Model

... robust fault detection filter which is effective for the sensor fault diagnose is proposed in ...sensor fault, however, this method is put forward for the linear system, it cannot adapt to the ... See full document

8

IWSNs with On-sensor Data Processing for Machine Fault Diagnosis

IWSNs with On-sensor Data Processing for Machine Fault Diagnosis

... Abstract: Machine fault diagnosis systems need to collect and transmit dynamic monitoring signals, like vibration and current signals, at ...implementing machine fault diagnosis ... See full document

14

Bearing Fault Diagnosis using Multiclass Support Vector Machine with efficient Feature Selection Methods

Bearing Fault Diagnosis using Multiclass Support Vector Machine with efficient Feature Selection Methods

... the wavelet family called discrete wavelet decomposition is used for ex- tracting wavelet coefficients and statistical features are ex- tracted for different levels of decomposition and fed into MSVM ... See full document

12

Compression of Images using Hierarchical Correlation of Wavelet Coefficients in Support Vector Machine Regression

Compression of Images using Hierarchical Correlation of Wavelet Coefficients in Support Vector Machine Regression

... Image compression techniques are used to reduce the size of images without much degrading their quality for efficient storage and transmission. Transform based image compression techniques have been widely used in ... See full document

5

Using Semi supervised Discriminant Analysis to Predict Subcellular Localization of Gram negative Bacterial Proteins

Using Semi supervised Discriminant Analysis to Predict Subcellular Localization of Gram negative Bacterial Proteins

... without using dimensionality re- duction is ...improved using dimensionality reduction ...enhanced using our method, which indicates that the proposed method is well for recog- nition the bacterial ... See full document

5

Show all 10000 documents...