Application of model-based fault detection and diagnosis to the quality assurance of an automotive actuator

Abstract The increased degree of automation of technical processes requires an increased number of mechanical-electronic components. In order to maintain the dependability and availability despite of the increased complexity, new methods for the quality assurance of mechanical-electronic systems are necessary. This paper describes an automatic diagnostic system for an automotive actuator. Analytic models of the process under investigation are used in order to extract detailed information about the process, using only the usually measured signals and evaluating the signals e.g. by parameter estimation and state estimation. However, some relations, especially the cause — effect relations between the underlying faults and the observable symptoms, are quite difficult to represent by analytic models. A rule-based approach is more suitable to acquire, represent and process the diagnostic knowledge base. In order to cope with uncertainty, a fuzzy structure is applied to the classification of faults.