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A neural network based approach for machine fault diagnosis
Ari Vepsäläinen
VTT Technical Research Centre of Finland
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Dive into the research topics of 'A neural network based approach for machine fault diagnosis'. Together they form a unique fingerprint.
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Keyphrases
Amount of Training
25%
Back Propagation Network
50%
CA Model
25%
Class number
25%
Dynamic Neural Network
25%
Environmental Conditions
25%
Input Pattern
25%
Large Amount of Data
25%
Linear Classifier
25%
Machine Fault Diagnosis
100%
Machine Maintenance
25%
Markov Model
25%
Network Approach
100%
Neural Network
100%
Node number
25%
Nonlinear Classifier
25%
Operating Conditions
25%
Output Codes
25%
Physical Condition
25%
Recognizer
25%
Spatiotemporal Neural Network
100%
Spatiotemporal Pattern
25%
Spectral Signature
25%
Temporal Relations
25%
Third-order Nonlinear
25%
Training Information
25%
Vibration Measurement
25%
INIS
comparative evaluations
12%
data
12%
dynamics
12%
fault tree analysis
100%
information
25%
maintenance
12%
markov process
12%
neural networks
100%
nonlinear problems
12%
output
12%
symptoms
12%
Computer Science
Fault Diagnosis
100%
Linear Classifier
12%
Neural Network
100%
Operating Condition
12%
Physical Condition
12%
Presented Approach
12%
Recognizer
12%
Spectral Signature
12%