EngineFaultDB: A Novel Dataset for Automotive Engine Fault Classification and Baseline Results

EngineFaultDB: A Novel Dataset for Automotive Engine Fault Classification and Baseline Results

This paper introduces EngineFaultDB, a novel dataset capturing the intricacies of automotive engine diagnostics. Centered around the widely represented C14NE spark ignition engine, data was collected under controlled laboratory conditions, simulating various operational states, including normal and...

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Bibliographic Details
Main Authors: Mary Vergara, Leo Ramos, Nestor Diego Rivera-Campoverde, Francklin Rivas-Echeverria
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Engine fault
automotive engine
spark ignition engine
fault classification
machine learning
deep learning
Online Access:https://ieeexplore.ieee.org/document/10311597/

Internet

https://ieeexplore.ieee.org/document/10311597/

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