Application Development of Ground Special Vehicle Prognostic and Health Management

Ground special vehicle plays an important role in the process of special transportation and space launch preparation. Consideration of reliability and safety risk for ground launch vehicular system is very important prior to operation process. Based on the engineering requirement of safety maintenance and health evaluation analysis. A framework of prognostic and health management is developed based on diagnostics and prognostic information. The basic structure is a type of data driven problem solving according to case-based reasoning model. Optimization method of feature attribute weight allocation based on SA algorithm is presented. The proposed method combines case-based reasoning with machine learning and is a data-driven method. Main function modules of attribute management, project management, case maintenance, case reasoning and data monitoring is introduced, as well as method to manipulate database and case base. The developed framework has been applied to the engineering practices for over three years, which can provide better solutions and maintenance suggestions for the diagnosis and health management of the system.