In this paper, we propose an approach for modeling fault coverage in nonlinear dynamical systems. Fault coverage gives a measure of the likelihood that a system will be able to recover after a fault occurrence. In our setup, the system dynamics are described by a standard state-space model. The system input (disturbance) is considered to be unknown but bounded at all times. Before any fault occ...

Stratified fault sampling is used in RTL fault simulation to estimate the gate-level fault coverage of given test patterns. RTL fault modeling and fault injection algorithm are developed such that the RTL fault list of a module can be treated as a representative fault sample of the collapsed stuck-at fault set of the module. The RTL coverage for the module is experimentally found to track the g...

A physically based fault conceptual model is presented for modeling multiphase flow and transport processes in fractured rock of fault zones. In particular, we discuss a general mathematical framework model for dealing with fracture-matrix interactions, which is applicable to both continuum and discrete fracture conceptualization in fault zones. In this conceptual model, faults or fault zones o...

Fault isolability plays a significant role and could be critical with respect to many aspects such as safety and maintenance for a process to be diagnosed. In the development of processes including diagnosis, design decisions are taken, e.g. sensor configuration selection, which affects the fault isolability possibilities. In this paper an algorithm for predicting fault isolability possibilitie...

This paper presents results for an automatic navigation system for agricultural vehicles. The system uses stereo-vision, inertial sensors and GPS. Special emphasis has been placed on modeling the natural environment in conjunction with a fault-tolerant navigation system. The results are exemplified by an agricultural vehicle following cut grass (swath). It is demonstrated how faults in the syst...

Data Models are high order [O(3)] multi-variable characterizations derived from simple third order polynomial building blocks. Such functions can be used to build real-time operational condition diagnostic and prognostic, i.e. fault classification and time to failure estimates. Data Modeling can achieve anomalous detection while only requiring nominal (no-fault) conditions for training. This ma...

The main objective of this tutorial is to present the 2005 situation of the state-of-the-art concerning the application of soft computing methods to fault diagnosis and supervision systems. Another objective is to show the unsolved and open problems of modern fault diagnosis and supervision that can be solved either with soft computing methods or hybrid systems based on analytical and soft comp...

In the areas of both safety and reliability analysis the precise modeling of complex technical systems during development and for evaluation purposes is of great importance. Traditionally, fault tree models have been used to accomplish this, and, more recently, stochastic Petri-net models have begun to be employed. To provide engineers with an intuitive high-level modeling interface to Petri-ne...

This paper develops a fault diagnosis methodology for civil engineering structures based on the bond graph approach. The bond graph theory provides a modeling framework that includes parametric models of the physical system and the sensors. Structural faults are modeled as abrupt or gradual damage in structural components. Sensor faults are modeled as biases or drifts from true measurements. Fa...

A new approach to parallel fault simulation for sequential circuits based on Binary Decision Diagrams (BDD) is proposed. The efficiency of BDDs for simulation is well known. However, traditional BDDs are not well-suited for fault simulation. Furthermore, up to now, they have not been used for parallel simulation. In the paper, a new class of BDDs is presented, called Structurally Synthesized BD...