Online Model-based Diagnosis for Multiple, Intermittent and Interaction Faults
نویسندگان
چکیده
This paper extends model-based diagnosis (MBD) (Reiter, 1987; de Kleer and Williams, 1987) to systems which convert, move and process materials or objects. Examples of such systems are printers, refineries, manufacturing lines and food processing plants. Such plants present two challenges to model-based diagnosis: (1) the plant may process with very high speed while handling multiple objects in parallel such that retaining full details of behavior of all past objects is impractical, and (2) complex multi-way interactions can occur among components operating on the same object. We address the first challenge by synopsizing past behavior and the current knowledge in a data structure of linear size in the number of components in the system. The second challenge is addressed by introducing the notion of interaction fault. An interaction fault is present if a set of components operating on the same object, damage the object even though each component alone produces non noticeable damage. Introducing interaction faults is much simpler than introducing fine-grained models of component-object interactions. We demonstrate the approach on a highly redundant printer.
منابع مشابه
Online Fault Detection and Isolation Method Based on Belief Rule Base for Industrial Gas Turbines
Real time and accurate fault detection has attracted an increasing attention with a growing demand for higher operational efficiency and safety of industrial gas turbines as complex engineering systems. Current methods based on condition monitoring data have drawbacks in using both expert knowledge and quantitative information for detecting faults. On account of this reason, this paper proposes...
متن کاملOn the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model
This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...
متن کاملOn the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model
This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...
متن کاملDiagnosing Multiple Persistent and Intermittent Faults
Almost all approaches to model-based diagnosis presume that the system being diagnosed behaves non-intermittently and analyze behavior over a small number (often only one) of time instants. In this paper we show how existing approaches to model-based diagnosis can be extended to diagnose intermittent failures as they manifest themselves over time. In addition, we show where to insert probe poin...
متن کاملFault diagnosis in a distillation column using a support vector machine based classifier
Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...
متن کامل