Honeywell International Inc.

Timothy J Felke

David Michael Kolbet

Randy R Magnuson

Jeff Van Der Zweep

John F Stone

George Daniel Hadden

Douglas L Bishop

John C Colclough

Michael W Stinson

Stephen P Eagleton

Pavel P H Hynek

Pavel Ph Hynek

A method, system, and computer program product for predicting the functional availability of a complex system is provided. Parameters of the complex system are converted from a plurality of binary values to at least one prognostic vector. At least a portion of a binary input expression is converted into an equivalent fuzzy output expression, the fuzzy output expression operable on the at least one prognostic vector.

Prediction of functional availability of complex system

An aircraft system includes an aircraft subsystem generating monitor trips related to the health of the aircraft subsystem; and an area health manager coupled to the aircraft subsystem. The area health manager includes a data receiver for receiving the monitor trips from the aircraft subsystem; a fault detector for processing inputs based on the monitor trips to identify faults; and an execution sequence queue coupled to the fault detector for storing a plurality of execution entities. Each of the plurality of execution entities is associated with a specific logic operation in the fault detector that is executed when the associated execution entity is in a first predetermined state.

Area health managers for aircraft systems

A recursive mapping structure for diagnostic models is provided. A parent diagnostic model includes a first input module, a first output module, a first monitor module coupled to the first input and first output modules, and a first propagation module coupled between the first input and first output modules. A child diagnostic model includes a second input module, a second output module, a second monitor module coupled to the second input and second output modules, and a second propagation module coupled between the second input and second output modules, wherein the second monitor module is coupled to the first monitor module.

Recursive structure for diagnostic model

A method of developing fault codes for complex systems based on historical data that in one aspect is a software program arranged to be installed and to operate on a processor to process the historical data in order to facilitate development of the fault codes, the software program resulting in the processor performing the method including: grouping the historical data into a plurality of observations and a plurality of repairs; analyzing the plurality of repairs to determine associated observation signatures, each of the observation signatures being one or more of the observations; and assigning a fault code to each observation signature.

Method and apparatus for developing fault codes for complex systems based on historical data

A relational database is for relating maintenance information that differs for each of a plurality of complex systems, such as a plurality of differing aircraft, using a common database structure so as to facilitate maintenance procedures for the plurality of complex systems. The database structure comprises: a plurality of primary entities for providing a fault model description of each of the plurality of complex systems, the fault model description including, for each of the plurality of complex systems, failure modes, symptoms and data required to effect a repair; and a categorical entity corresponding to a complex system, such as an aircraft, that enables selection of the fault model description corresponding to the complex system or aircraft. The relational database is particularly suited for use in or by an aircraft maintenance and diagnostic system that assists with fault correction for a fault condition within an aircraft based on a fault model for the aircraft.

Relational database for maintenance information for complex systems

A method for improving fault isolation for failure modes in complex systems, and a software program embodying the method or a corresponding method together with a computer based aircraft diagnostic system using such software is described. The method includes: capturing a set of symptoms that is consistent with a failure mode of the complex system; identifying a set of repairs for the complex system that are consistent with the set of symptoms; ranking, when the set of repairs includes more than one repair, the repairs in a sequence that will minimize an average cost to repair the complex system, the sequence including a historical component and reflecting the effectiveness of available test results to resolve each the repairs; determining possible tests that are consistent with the failure mode; and ranking the possible tests according to there respective net improvement in the average cost to repair the complex system.

Method and apparatus for improving fault isolation

A method of associating deferral procedures to a fault model for complex systems based on historical data, the method including the steps of: analyzing historical data for deferral information to identify deferral procedures; associating each of the deferral procedures with a corresponding one or more standard repairs; linking each of the standard repairs with a fault code; and associating each of the deferral procedures with one or more of the fault codes that were linked, respectively, with the one or more standard repairs to thereby provide a set of associations between deferral procedures and fault codes. The method may be implemented in a software program and the program may advantageously be employed in an aircraft maintenance and operations support system for automatically associating deferral procedures with an aircraft fault model based on historical data.

Method and apparatus using historical data to associate deferral procedures and fault models

A method for improving fault classifications for failure modes in complex systems, and a software program embodying the method or a corresponding method together with a computer based aircraft diagnostic system using such software is described. The method includes: capturing an observation that is consistent with a discrepancy of the complex system; identifying a set of failure modes of the complex system that are consistent with the observation; ranking, when the set includes more than one failure mode, the failure modes according to a degree of support the observation provides for each failure mode, the degree of support including a historical component; determining additional possible observations that are consistent with any failure mode included in the set; and ranking the possible observations according to how rapidly they reduce a number of failure modes included in the set; then preferably selecting a further observation and repeating the above steps until only one failure mode remains.

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Glendale, AZ, United States of America

Timothy J Felke