Model-based diagnosis enables efficient and safe operation of engineered systems. In this paper, we describe two algorithms based on a qualitative event-based fault isolation framework augmented with model-based fault identification that are applied to spacecraft power distribution systems. Although based on a common framework, the fundamental difference between the two algorithms is that one u...

Multiple fault diagnosis is a difficult problem for dynamic systems. Due to fault masking, compensation, and relative time of fault occurrence, multiple faults can manifest in many different ways as observable fault signature sequences. This decreases diagnosability of multiple faults, and therefore leads to a loss in effectiveness of the fault isolation step. We develop a qualitative, event-ba...

Abstract: This paper describes a fault detection and isolation (FDI) scheme performed on the benchmark problem of a ship propulsion system. The model used for the ship propulsion system is nonlinear, for which two types of additive sensor faults, an additive incipient fault, and a multiplicative parametric fault are simulated. The estimation of the fault severity is accomplished by using an ada...

This work is concerned with multiple faults isolation for hybrid systems based on Global Analytical Redundancy Relationships (GARRs) approach. GARRs are derived from the Hybrid Bond Graph (HBG) model of a hybrid system with a specified causality assignment procedure. In this article, multiple faults are considered in a complex hybrid system and these faults can develop during a mode when the fa...

This paper extends the generalized parity vector approach for fault detection and isolation presented in Omana and Taylor [2], [3], [4], to achieve sensor accommodation. In this study, this fault detection, isolation and accommodation technique is applied to a two-phase separator followed by a three-phase gravity separator model used in oil production facilities. This model simulates a large sc...

We study the problem of sensor placement for maximum structural fault detection and isolation in systems with a graphical structure. In particular, we consider flow networks and sensor networks. We are interested in placing as few sensors as possible. We get efficient approximation algorithms and exact algorithms for computing a smallest sensor set for maximum structural fault detectability and...

The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as, model errors, uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models. The aim of this thesis is to propose a methodology for fault detection, isolation and identification based on interval models. Especially a modal interval based techni...

In this paper, an approach for suitable fault management in traffic information networks, focusing on the isolation of network faults in infrastructure networks, will be introduced. We will show, that modelbased diagnosis is an efficient method for finding explanations consisting of the underlying fault events of system failures. A fault management system based on these concepts will be discuss...

We present a novel approach for model-based FDI of abrupt faults in process components of continuous dynamic systems. Abrupt faults refer to parameter value changes that occur much faster than the nominal process dynamics, and component faults refer to faults that correspond to physical parameters in the bond graph model of a system. These faults cause transients in system behavior. We analyze ...