A visual interpretation-based intelligent fault diagnosis framework for switch machines based on sound signal
A visual interpretation-based intelligent fault diagnosis framework is developed for switch-machine fault diagnosis using acoustic signals and achieves high diagnostic accuracy under different time–frequency representations, with several configurations reaching 100% accuracy under the current evaluation protocol.