A model of fault diagnosis performance of expert marine engineers

Abstract

Models of fault diagnosis by expert human operators are classified into two types: macro and micro. Macro models describe general problem-solving rules or strategies that are abstracted from observations of expert fault diagnostic behaviour. Micro models are concerned with the detailed knowledge and the mechanisms underlying the diagnostic actions. This paper proposes a micro model developed from observations of fault diagnosis performance on a marine powerplant simulator. Based on experimental data, including protocols and operator action sequences, two types of knowledge are identified: rule-based symptom knowledge and hierarchical system knowledge. The diagnostic process seems to proceed with frequent reference to these two types of knowledge. Characteristics of the diagnostic process are discussed. A conceptual entity called a hypothesis frame is employed to account for observed characteristics. The diagnostic process involves choosing an appropriate frame that matches the known symptoms and evaluating the frame against the system state. This model of fault diagnosis performance is employed to explain protocol data and operator actions.