Health Management System for the Industrial Robot Control Cabinet

To address the demand for higher reliability brought about by the comprehensive, integrated development, and normalized operation of robot systems, particularly focusing on the associated controllers, this study investigates the fault diagnosis and health assessment methods for typical coupled software and hardware systems. In response to the current issues such as insufficient monitoring parameters, low diagnostic accuracy, and lack of quantitative evaluation methods, we first outline the typical fault mode trees of coupled software and hardware systems. Then, by integrating information on the operational status of software and hardware, we design a two-step fault diagnosis algorithm based on prior knowledge to effectively reduce false alarms. Additionally, we establish multi-level health assessment parameters and models. Finally, we implement a health management system based on the above methods and deploy it on an industrial robot control cabinets, verifying the effectiveness of our design approach.