… fault diagnosis (IFD) refers to applications of machine learning theories to machine fault
diagnosis… and automatically recognize the health states of machines, thus it has attracted much …

… Not only can a machine learning system bring higher efficiency, but it can also accumulate
the knowledge for further learning. Currently we are developing a machine learning system, …

… These new developments of machinery fault diagnosis have … of machinery fault diagnosis
based on machine learning … in shallow machine learning in machinery fault diagnosis, …

… in neural networks, support vector machine learning from large data sets, hybrid learning
system with neural networks and genetic algorithms, data mining from text documents, and …

… In line with engineering experience and information related to the system, we analyzed the
interval in which the fault diagnosis results were within [ Z − a, Z + a]. The a denotes the half-…

… and efficiency of fault identification. In order to solve these problems, a new fault diagnosis
(… (PCA) and the broad learning system (BLS) is proposed for rotor system in this paper. In the …

… system fault diagnosis, is not available in the literature. Given this need and growing trend
towards ML, the study … review of ML-based power system fault diagnosis. At first, efforts have …

… to develop an ensemble machine learning (EML) using for fault diagnosis by combining
DBNs… , a novel transformer fault diagnosis method using an IoT based monitoring system and an …

… to monitor all the components in the GTGS in one study, this research selected the fault
detection of a gearbox as a case study. The test rig can simulate many common faults in the …

… Architecture of the Multi-Agent Remote Diagnostic System A remote fault diagnostic system
with learning capability is discussed in this section. The framework of the system is shown in …