A modular adaptive residual generator for a diagnostic system that detects sensor faults on engine test beds

Abstract

Abstract. It is a great challenge to apply a diagnostic system for sensor fault detection to engine test beds. The main problem is that such test beds involve frequent configuration changes or a change in the entire test engine. Therefore, the diagnostic system must be highly adaptable to different types of test engines. This paper presents a diagnostic method consisting of the following steps: residual generation, fault detection and fault isolation. As adaptability can be achieved with residual generation, the focus is on this step. The modular toolbox-based approach combines physics-based and data-driven modeling concepts and, thus, enables highly flexible application to various types of engine test beds. Adaptability and fault detection quality are validated using measurement data from a single-cylinder research engine and a multicylinder diesel engine.