SITIS Archives - Topic Details
Program:  SBIR
Topic Num:  N07-084 (Navy)
Title:  Dynamically Reconfigurable Data Architectures for Aircraft Data Analysis and Anomaly Detection
Research & Technical Areas:  Air Platform, Information Systems

Acquisition Program:  PEO (T), Tactical: PMA-265, PMA-299, PMA-275, PMA-261, PMA 209
 RESTRICTION ON PERFORMANCE BY FOREIGN NATIONALS: This topic is “ITAR Restricted”. The information and materials provided pursuant to or resulting from this topic are restricted under the International Traffic in Arms Regulations (ITAR), 22 CFR Parts 120-130, which control the export of defense-related material and services, including the export of sensitive technical data. Foreign nationals may perform work under an award resulting from this topic only if they hold the “Permanent Resident Card”, or are designated as “Protected Individuals” as defined by 8 U.S.C. 1324b(a)(3). If a proposal for this topic contains participation by a foreign national who is not in one of the above two categories, the proposal may be rejected.
  Objective:  Develop an adaptive approach for advanced data analysis using automated reasoning and highly dynamic data architectures with integrated data fusion and adaptive analysis techniques for the detection of system anomalies and multi-variate trends only apparent through the integration and analysis of disparate data sources.
  Description:  Massive quantities of data are collected regularly from aircraft flight data recorders, maintenance, logistics, and readiness reporting systems. Typically, each of the data sources are designed to satisfy a unique requirement and are processed to provide only the requisite information to the intended audience. Through integration of these data sources, further insight into aircraft fleet usage, system performance, and readiness factors can be realized (for instance: rotor system vibration levels recorded by aircraft data systems may only make full sense when linked with operational usage data and component replacement information noted in the logistics system). However, due to the quantity and disparity of the data available across multiple DON data systems and aircraft, there is currently no way to automatically identify, access, retrieve, and integrate data sources to provide useable information from an amalgamation of these data sources. Advanced methods of processing the vast quantities of these disparate data is needed in order to accomplish this. Intelligent adaptive methods of accessing, integrating, mining, characterizing, and presenting the data must therefore be developed. These techniques must be able to account for a variety of data from multiple sources and extract useful information. Of particular interest are the detection of mechanical issues that are, as of yet, unknown or undocumented and the association of faults with their causal factors. Possible solutions include, but are not limited to artificial intelligence, intelligent software agents, advanced fusion algorithms, as well as meta-base or multi-base categorization and storage techniques. This topic is directly applicable to the mission requirements of Air ASW Assault & Special Missions Programs, and well as PEO (T), Tactical Air Programs. This topic will also support the following platforms: PMA-265 (F-18), PMA-299 (H-60), PMA-275 (V-22), PMA-261 (H-53), and PMA-209 (Common Avionics).

  PHASE I: Develop an approach for dynamically reconfigurable database architecture(s) and methods of data set integration with integrated data analysis and fusion algorithms. Apply to an illustrative example.
  PHASE II: Implement a test case of one aircraft type utilizing the architectures and methods developed.

  PHASE III: Implement the same for multiple aircraft type/model/series. PRIVATE SECTOR COMMERCIAL POTENTIAL/

  DUAL-USE APPLICATIONS: This technology is directly applicable to maintenance cost reduction in commercial aircraft fleets.

  References:  1. An Introduction to Predictive Maintenance, R. Keith Mobley, Elseveir, 2002 2. Condition Monitoring, E. D. Yardley, Wiley, 2002

Keywords:  aircraft;health-maintenance;condition-based;data;architectures;anomaly; prediction

Questions and Answers:
Q: This topic involves both a "dynamic database" component and an "analysis" component. Will a proposal be considered which addresses the "analysis" section without addressing database design?
A: . . . response pending . . .
Q: In this topic, “Of particular interest are the detection of mechanical issues that are, as of yet, unknown or undocumented …”, do we also need to consider electrical or electronic issues?
A: This is optional and will be left up to the bidder.
Q: One of the key aspects of this project is the integration of the data sources. Would there be sample sets of these data sources available to do development against?
A: We do not have sample data sets for Phase 1, we would rely on the contractor to generate simulated data sets to prove their concepts.
Q: This topic involves both a "dynamic database" component and an "analysis" component. Will a proposal be considered which addresses the "analysis" section without addressing database design?
A: . . . response pending . . .
Q: In this topic, “Of particular interest are the detection of mechanical issues that are, as of yet, unknown or undocumented …”, do we also need to consider electrical or electronic issues?
A: This is optional and will be left up to the bidder.
Q: One of the key aspects of this project is the integration of the data sources. Would there be sample sets of these data sources available to do development against?
A: We do not have sample data sets for Phase 1, we would rely on the contractor to generate simulated data sets to prove their concepts.

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