Data-Driven Engine Fault Classification and Severity Estimation Using Interpolated Fault Modes from Limited Training Data
Today modern vehicles are expected to be safe, environmentally friendly, durable and economical. Monitoring the health of the vehicle is therefore more important than ever. As the complexity of vehicular systems increases the need for efficient monitoring methods has increased as well. Traditional m...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Fordonssystem
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-173916 |