DXPCS: A software tool for consistency-based diagnosis of dynamic systems using Possible Conflicts
نویسندگان
چکیده
In this work we introduce DXPCS, a software tool capable of performing consistency-based diagnosis of continuous dynamic systems whose models can be represented as a set of Ordinary Differential Equations. The diagnosis approach relies upon the Possible Conflict, PC for short, concept. DXPCS is able to automatically build the simulation models for each PC. Single-fault and multiple-fault scenarios, for both parametric and additive faults, can be injected, and studied. DXPCS allows the integration of different algorithms for fault detection, residual generation and evaluation, together with an incremental version of the minimal-hitting set algorithm for fault localization. The software architecture, together with performance results for one simple case study, are provided in this paper.
منابع مشابه
Combination of Simulation and State Observers for Consistency-based Diagnosis
Consistency-based diagnosis of dynamic systems using possible conflicts rely upon a semi-closed loop simulation of numerical models. Simulation approaches need to know the initial state, which is a nontrivial requirement in real-world systems. Prognosis approaches also require techniques for predicting the future system states under nominal and faulty conditions. This work proposes to integrate...
متن کاملMachine Learning and Model Based Diagnosis using Possible Conflicts and System Decomposition.∗
This work presents an on-line diagnosis algorithm for dynamic systems that combines model based diagnosis and machine learning techniques. The Possible Conflicts method is used to perform consistency based diagnosis. Possible conflicts are in charge of fault detection and isolation. Machine learning methods are use to induce time series classifiers, that are applied on line for fault identifica...
متن کاملPossible conflicts, ARRs, and conflicts
Consistency-based diagnosis is the most widely used approach to model-based diagnosis within the Artificial Intelligence community. It is usually carried out through an iterative cycle of behavior prediction, conflict detection, and candidate generation and refinement. Many approaches to consistency-based diagnosis have relied on some kind of on-line dependency-recording mechanism for conflict ...
متن کاملImproving the Diagnostic Performance for Dynamic Systems through the use of Conflict-Driven Model Decomposition
This work studies potential ways of integration of two techniques for fault detection, isolation, and identification in dynamic systems: Lydia-NG suite of diagnosis algorithms and Consistency-based Diagnosis with Possible Conflicts. By integrating both techniques, LydiaNG will benefit from a more efficient fault detection and isolation task, and Possible Conflicts will benefit from the identifi...
متن کاملReal Time Dynamic Simulation of Power System Using Multiple Microcomputers
Recent developments in the design and manufacture of microcomputers together with improved simulation techniques make it possible to achieve the speed and accuracy required for the dynamic simulation of power systems in real time. This paper presents some experimental results and outlines new ideas on hardware architecture, mathematical algorithms and software development for this purpose. The ...
متن کامل