The Hypothetical Scenario Generator for Fault-tolerant Diagnostics (HSG) is an algorithm being developed in conjunction with other components of artificial- intelligence systems for automated diagnosis and prognosis of faults in spacecraft, aircraft, and other complex engineering systems. By incorporating prognostic capabilities along with advanced diagnostic capabilities, these developments hold promise to increase the safety and affordability of the affected engineering systems by making it possible to obtain timely and accurate information on the statuses of the systems and predicting impending failures well in advance.
Prognosis is tightly coupled with diagnosis. The simplest approach to prognosis by an artificial-intelligence system involves the use of a diagnostic engine in a controlled feedback loop to project from the current state of the affected engineering system to future states that are elements of scenarios that are discovered hypothetically. A hypothetical-scenario generator is a key element of this approach. A hypothetical- scenario generator accepts, as its input, information on the current state of the engineering system. Then, by means of model-based reasoning techniques, it returns a disjunctive list of fault scenarios that could be reached from the current state.
The HSG is a specific instance of a hypothetical-scenario generator that implements an innovative approach for performing diagnostic reasoning when data are missing. The special purpose served by the HSG is to (1) look for all possible ways in which the present state of the engineering system can be mapped with respect to a given model and (2) generate a prioritized set of future possible states and the scenarios of which they are parts. The HSG models a potential fault scenario as an ordered disjunctive tree of conjunctive consequences, wherein the ordering is based upon the likelihood that a particular conjunctive path will be taken for the given set of inputs. The computation of likelihood is based partly on a numerical ranking of the degree of completeness of data with respect to satisfaction of the antecedent conditions of prognostic rules. The results from the HSG are then used by a model-based artificial-intelligence subsystem to predict realistic scenarios and states.
To avoid the need to create special models to generate hypothetical scenarios, the HSG uses the same model that is used to perform fault-detection and other diagnostic functions but interprets the results generated by the model in a manner unique to the generation of hypothetical scenarios. An important additional advantage of this approach is that a future state can be diagnosed by the same model as that used to diagnose the current state.
This work was done by Mark James of Caltech for NASA's Jet Propulsion Laboratory. For more information, download the Technical Support Package (free white paper) at www.techbriefs.com/tsp under the Information Sciences category.
The software used in this innovation is available for commercial licensing. Please contact Karina Edmonds of the California Institute of Technology at (626) 395-2322. Refer to NPO-42516.
This Brief includes a Technical Support Package (TSP).
Hypothetical Scenario Generator for Fault-Tolerant Diagnosis
(reference NPO-42516) is currently available for download from the TSP library.
Don't have an account?
Overview
The document outlines the "Hypothetical Scenario Generator for Fault-Tolerant Diagnosis," identified by NTR Number 42516, developed by NASA's Jet Propulsion Laboratory (JPL). This innovation is part of NASA's efforts to advance aerospace technology and is documented in the NASA Tech Briefs under the designation NPO-42516.
The Hypothetical Scenario Generator is designed to enhance fault-tolerant diagnostic systems, which are crucial for ensuring the reliability and safety of aerospace missions. Fault tolerance is a critical aspect of engineering, particularly in space exploration, where systems must operate under extreme conditions and potential failures. The generator aims to create various hypothetical scenarios that can be used to test and improve diagnostic algorithms, ultimately leading to more robust systems capable of handling unexpected issues.
The document emphasizes the importance of making aerospace-related developments accessible for broader technological, scientific, and commercial applications. It is part of NASA's Commercial Technology Program, which seeks to promote innovation and collaboration between government and private sectors. By sharing this technology, NASA aims to foster advancements that can benefit various industries beyond aerospace.
For those interested in further information or assistance regarding this technology, the document provides contact details for the Innovative Technology Assets Management at JPL, including a mailing address, telephone number, and email. This allows interested parties to reach out for more detailed inquiries or potential collaborations.
Additionally, the document includes a notice regarding the proprietary nature of the information and the need to comply with U.S. export regulations. It clarifies that the United States Government does not assume liability for the use of the information contained within the document, nor does it endorse any specific trade names or manufacturers mentioned.
In summary, the "Hypothetical Scenario Generator for Fault-Tolerant Diagnosis" represents a significant step in improving diagnostic capabilities in aerospace systems, with potential applications across various fields. The initiative reflects NASA's commitment to innovation and collaboration, aiming to leverage advanced technologies for broader societal benefits.
