Multi-label relevant vector machine based simultaneous fault diagnosis

摘要

To address the simultaneous fault diagnosis problem, a Multi-Label approach that makes use of Relevance vector machines (RVM), as the learning algorithm, is proposed to decrease the number of fault identification models and deal simultaneous fault diagnosis problems. The system is proved to be efficient by the simulation test on the Tennessee Eastman Process (TEP).