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Creating Virtual Sensors ForOperational UseReal World Perspective

August 2017

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Virtual Sensing thru Big Data• Some thoughts on Big Data

• Challenges with the Big Data collective

• Virtualization utilizing Big Data

• Examples and applications

• Looking forward and discussion

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Jacobs Interest in Big Data• Develop tools and capabilities to integrate

data sets Past, Present and Future

• Have a globally adaptive usable and dynamicsystem to create virtual sensing capabilities

Data and Data Types• Big Data is a term for data sets

that are so large or complex thattraditional data processing application software is inadequate to deal with them

• Big Data is a part of everydaylife, it is a part of everything wedo, record, type and capture via any media.

• Let’s not limit it to mereexamples – Anything you can record and store can become BigData…..

• History lends itself to hidden gems of potentiall data and BigData

Data Environment – (MV hPOV)• There exists many challenges in accessing the

data sets that are present in today’s world• Categorized:✓ Political - Friendly or not whoever has the data

and whoever needs the data usually have to build a bridge in order to share

✓ Economic - Capitalism at its worst or best, ROI is always at the top

✓ IP - Whoever controls the data usually considers that they are the owner and have all rights

Creating Virtual Sensors• Additional sensors are desired

• Cost is prohibitive to modify current and legacy aircraft

• Data sources abound and need to be used

• Politics, economics and IP of data collection and sharing is a challenge

• Manipulating data into sensors – Big data is a bucket in which to draw from and create virtual sensing capabilities

Advantage and Implementation

Past

Present

Future

Global Scale

Vehicle Level Can You Hear Me Now?

Big Data or Not?

ACOUSTICCORRELATION

Global Scale –Wind ModelsRecorded winds aloft and on thesurface have large number of applications• Where the data is

– Airports, ground stations, weather balloons, aircraft, ocean vessels

• Better and more complete data set for multiple applications– Turbulence, atmospheric

dispersion, NOAA models– Engine performance– Vehicle performance

Data were there – Big Data was not• 15 December 1993 an Israeli Westwind corporate jet

crashed 2.1 miles from landing following B757

• Lead aircraft on 5.6 degree glide path, Westwind attempted to increase their glide path to avoid waketurbulence

• The gaps – No sensors in area of vortices

• End result – Westwind accomplished a 360 degree roll and 45 degree tangential impact resulting in total loss

W 75In

Data were there – Big Data was not• The previous 12 months had 5 similar events involving

B757 wake vortices– Two recovered– Three had less fortunate outcomes

• Prior to this event B757 was not considered a “Heavy” aircraft by FAA standards– Heavy aircraft or afforded longer clearance times

• The data here was pilot verbal input

• There were 47 other events used in analysis

https://www.faa.gov/regulations_policies/orders_notices/index.cfm/go/document.current/documentnumber/7110.65

Should’ve, Could’ve, Would’ve

http://libraryonline.erau.edu/online-full-text/ntsb/special-investigation-reports/SIR94-01.pdf

Vehicle Level – Oil Health & Condition• Oil has contributed to costly maintenance and

undesirable events in all aspects of bearing use

• In aviation it easily can cost you the entire engine and beyond

• Much effort has been put into accelerometers, stress wave and ferrous measuring sensors to display thehealth and condition of oil in a bearing system

• There may be a virtual way of understanding oil better

Virtual Indicators and Validation• The obvious – Bad vs good

• The desirable and not desirable

• The how and where?

• Validation– Sampling– Analysis

Can You Hear Me Now?• So many correlations can be made from sound• A simple microphone strategically placed does

enhance acoustic correlations– Type of aircraft– Aircraft configurations– Anomalies with aircraft systems– Traffic volume

• Its just a matter of algorithm development

Can You Hear Me Now?• In 2005 NASA Dryden/Ames

conducted Noise Mitigating SmartTerminal Approach Trajectoryresearch

• The objective was to compare and assess standard and spiral approaches into a commercial airport

• The goal was validating that a spiral approach left a smallerfootprint than current techniques

• Additionally we were able to detect flap and landing gearposition during the flyovers

Can You Hear Me Further?• NASA Vehicle Integrated

Propulsion Research (VIPR)– Three stages to research new

sensing technologies, gas path modeling growth and volcanicash effects on large turbineengines

• During phase III ash was injected into the engine and seeded faults were used to validate anomalydetection– Top graph was a primary goal of

detecting a hard seeded fault– Bottom graph was the additional

finding– Both are virtual detectors

Where to Next?• Take a look at an

airport microphone for SNA in Orange countyCA.

• Would it be possible to detect traffic volumearound the 3 majorfreeways near theairport??

Questions?

Discussion