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

• Main Authors: Pirker, G. (Author), Wimmer, A. (Author), Wohlthan, M. (Author)
• Format: Article
• Language: English
• Published: Copernicus GmbH 2022
• Subjects: Adaptive residual generators; Diagnostic methods; Diagnostic systems; Engine test bed; Engines; Equipment testing; Fault detection; Fault detection isolations; Modulars; Residual generation; Sensor fault detection; Sensors faults
• Online Access: View Fulltext in Publisher

 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. © 2022 Michael Wohlthan et al.