Fault Diagnosis of Induction Motors Using Data Fusion of Vibration and Current Signals
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김광진
(부경대학교 대학원 기계공학부)
한천 (부경대학교 대학원 기계공학부) |
1 |
Integration of ART-Kohonen Neural Network and Case-Based Reasoning for Intelligent Fault Diagnosis
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DOI ScienceOn |
2 |
A k-nearest Neighbor Classification Rule Based on Dempster-Shafer Theory
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DOI ScienceOn |
3 |
Induction Machine Drive Condition Monitoring and Diagnostic Research- A Survey
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DOI ScienceOn |
4 |
A Review of Induction Motors Signature Analysis as a Medium for Faults Detection
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DOI ScienceOn |
5 |
유도전동기의 고장원인분석 및 진단기술
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6 |
Case-Based Reasoning System with Petri Nets for Induction Motor Fault Diagnosis
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DOI ScienceOn |
7 |
교류전동기의 포괄적인 On-line 감시도구
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8 |
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9 |
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10 |
An Introduction to Multisensor Data Fusion
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DOI ScienceOn |
11 |
A Neural Network Classifier Based on Dempster-Shafer Theory
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12 |
Root Cause AC Motor Failure Analysis with a Focus on Shaft Failures
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DOI ScienceOn |
13 |
Belief Function Combination and Conflict Management
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DOI ScienceOn |
14 |
Upper and Lower Probabilities Induced by Multivalued Mappings
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DOI ScienceOn |
15 |
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16 |
The Transfer-able Belief Model
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DOI ScienceOn |
17 |
Condition Classification of Reciprocating Compressors using Radial Basis Function Neural Network
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