| Title | A Distributed Autonomic Logistics System with Parallel-Computing Diagnostic Algorithm for Aircrafts |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Han, Danyang, Yu, Jinsong, Song, Yue, Tang, Diyin, Dai, Jing |
| Conference Name | 2019 IEEE AUTOTESTCON |
| Keywords | aircraft conditions, aircraft maintenance, autonomic logistic, autonomic logistic system, client-server systems, complex operating conditions, compositionality, computing time complexity, conceptional system, condition monitoring, dependency matrix expansion, diagnostic health assessment platform, distributed ALS, distributed autonomic logistics system, distributed system, expandability, fault diagnosis, fault location, fault points, health management system, improved diagnostic algorithm, large-scale aircraft control center, Logistics, machine groups, maintenance decisions-making, maintenance engineering, parallel computing, presents repairment instructions, primary control system, production engineering computing, prognostics and health management, promoted diagnostic algorithm, pubcrawl, real-time failure monitoring, real-time flight conditions, remaining life assessment, resilience, Resiliency, scale aircraft control centers, single machines, telemetry, telemetry parameters, typical diagnostic algorithms |
| Abstract | The autonomic logistic system (ALS), first used by the U.S. military JSF, is a new conceptional system which supports prognostic and health management system of aircrafts, including such as real-time failure monitoring, remaining useful life prediction and maintenance decisions-making. However, the development of ALS faces some challenges. Firstly, current ALS is mainly based on client/server architecture, which is very complex in a large-scale aircraft control center and software is required to be reconfigured for every accessed node, which will increase the cost and decrease the expandability of deployment for large scale aircraft control centers. Secondly, interpretation of telemetry parameters from the aircraft is a tough task considering various real-time flight conditions, including instructions from controllers, work statements of single machines or machine groups, and intrinsic physical meaning of telemetry parameters. It is troublesome to meet the expectation of full representing the relationship between faults and tests without a standard model. Finally, typical diagnostic algorithms based on dependency matrix are inefficient, especially the temporal waste when dealing with thousands of test points and fault modes, for the reason that the time complexity will increase exponentially as dependency matrix expansion. Under this situation, this paper proposed a distributed ALS under complex operating conditions, which has the following contributions 1) introducing a distributed system based on browser/server architecture, which is divided overall system into primary control system and diagnostic and health assessment platform; 2) designing a novel interface for modelling the interpretation rules of telemetry parameters and the relationship between faults and tests in consideration of multiple elements of aircraft conditions; 3) proposing a promoted diagnostic algorithm under parallel computing in order to decrease the computing time complexity. what's more, this paper develops a construction with 3D viewer of aircraft for user to locate fault points and presents repairment instructions for maintenance personnels based on Interactive Electronic Technical Manual, which supports both online and offline. A practice in a certain aircraft demonstrated the efficiency of improved diagnostic algorithm and proposed ALS. |
| DOI | 10.1109/AUTEST.2019.8878478 |
| Citation Key | han_distributed_2019 |
A Distributed Autonomic Logistics System with Parallel-Computing Diagnostic Algorithm for Aircrafts