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Flight Data Monitoring. CGAR Conference June 13, 2012. The Team UND Jim Higgins Dana Siewert Gary Ullrich Lewis Liang Brett Venhuizen Karin Hennseleck , GRA Yong Lai, GRA Computer Science Sophine Clarchar , GRA Computer Science. What is Flight Data Monitoring (FDM)?
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Flight Data Monitoring CGAR Conference June 13, 2012
The Team • UND • Jim Higgins • Dana Siewert • Gary Ullrich • Lewis Liang • Brett Venhuizen • Karin Hennseleck, GRA • Yong Lai, GRA Computer Science • SophineClarchar, GRA Computer Science
What is Flight Data Monitoring (FDM)? • The systematic collection of data from onboard flight recording devices • The aggregation of all data into a central data repository • The rigorous analysis of the data to proactively identify hazards currently undetected • The adaption of policies and/or procedures to mitigate or eliminate the risks of all identified hazards
FDM has been implemented at many airlines throughout the world • Usually known as Flight Operations Quality Assurance (FOQA) • Widely accepted as an effective method of proactive hazard identification
If You Can Measure Behavior, You Can Manage It HOMP Begins in September 2007
So what is CGAR trying to accomplish with its FDM research? • Bring FDM to General Aviation
Current status of FDM at UND • 62 Cessna 172s Garmin G1000 SD Card • 3 have Appareo Vision 1000 systems • 1 Bell 206 Appareo Vision 1000 system • RFP Discussion
How is the current CGAR FDM grant is overcoming the barriers for widespread deployment of FDM GA?
The systematic collection of data from onboard flight recording devices • Barriers for GA • Recording Technology/Cost • Overcome by G1000 SD card • Flight recorder vendors • Potential mobile devices/handheld units
The aggregation of all data into a central data repository • Barriers for GA • No database/software • Overcome by the development of the NGAFID
Current Status of the NGAFID • Originally had over 80,000 files and 100,000 hours in database • After the correction, we now have 50,468 files in database • Estimated 76.3% are flights (≈38,000 flights) • Defined as indicated airspeed > 30 • Estimated 1.35 mean flight time • Estimated: 51,984 flight hours
The rigorous analysis of the data to proactively identify hazards currently undetected • Two options • Hire a vendor (cost-restrictive for weekend pilots) • Use FDM software (cost-restrictive for weekend pilots) • Overcome by NGAFID toolset (under development)
The adaption of policies and/or procedures to mitigate or eliminate the risks of all identified hazards • Barriers for GA • Not a widespread adoption of SMS (yet) • Hopefully will be overcome by the efforts of other CGAR projects and industry (GA JSC)
A Case Study in how FDM could work in GA • UND Ramp • The UND SMS risk analysis people determined that we were at a heightened risk for an accident or major incident on our ramp • Reasons for this risk: • Congestion • Taxi speeds • Complacency
A Case Study (Continued) • Can this be tracked? • Tracking variables (frequency) • Taxi speed FDM • Complacency LOSA/Observations • Congestion LOSA/Observations • Tracking variables (severity) • Reporting ASAP • Accident reports
A Case Study (Continued) • Time-of-day example
Other exceedances that have been analyzed • Maximum Altitude • Maximum Bank Angle • Maximum Pitch Angle • VNE
Specific Problems • Aircraft WoW • Aircraft flap setting • Terrain elevation • ARINC 429 data/onboard data • Automated retrieval
Phase III Directions • Formally invite other collegiate fleets to share data • Develop educational tools regarding to use the NGAFID • Develop national FDM database usage and access standards • Open the NGAFID to the flying public • Secure long-term support for the continued operation of the NGAFID
Thank You! Jim Higgins jhiggins@aero.und.edu