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An Aircraft Operation Counting System Using Type 2 Sound Level Meters and Automatic Data Processing Jaime Giandomenico Mariana Buzduga Richard J. Peppin.

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Presentation on theme: "An Aircraft Operation Counting System Using Type 2 Sound Level Meters and Automatic Data Processing Jaime Giandomenico Mariana Buzduga Richard J. Peppin."— Presentation transcript:

1 An Aircraft Operation Counting System Using Type 2 Sound Level Meters and Automatic Data Processing Jaime Giandomenico Mariana Buzduga Richard J. Peppin 2006 ADC40 TRB Noise & Vibration Summer Meeting July 10,2006

2 2 Overview Purpose / Requirements / Existing Purpose / Requirements / Existing Noise based methods: accuracy analysis Noise based methods: accuracy analysis Airport specifics Airport specifics System presentation and strong features System presentation and strong features Results Results

3 3 Purpose/Need Maryland Aviation Administration (MAA) Office of Regional Aviation (ORAA): Maryland Aviation Administration (MAA) Office of Regional Aviation (ORAA): –Statewide grant program that provides funding for capital projects at general-aviation airports –Accurate data on the level of operations at each airport is crucial for planning and prioritization purposes: how many aircraft use a given facility? Daily Daily Weekly Weekly Seasonally Seasonally Annually ? Annually ?

4 4 Methodology Data collection device placed on airport Data collection device placed on airport Sample translated into daily operational averages. Sample translated into daily operational averages. Algorithm determines seasonal/annual average. Algorithm determines seasonal/annual average. Nonstandard operations added to annual total. Nonstandard operations added to annual total.

5 5 Requirements Smallest size possible Smallest size possible Affordable Affordable Autonomous Autonomous Rugged Rugged Low power draw Low power draw Avoid features overkill Avoid features overkill Accuracy Accuracy User friendly data ops. User friendly data ops. Flexible Flexible Goal for annual estimate of operations: generate a 95% confidence interval.

6 6 Past Methods/Problems Methods: Methods: –Volunteer observer –Highway tubes –Fuel Sales (formula) –Analogue recorders (RENS) –First Generation Sound Level Meters Problems: Problems: –Small sample/impractical –Tampering/placement –Accuracy –User Interface $$$ –Memory/Data Handling

7 7 Putting Noise to Work Threshold-only noise monitoring: Threshold-only noise monitoring: –Low cost –Simplicity –Existing system gave acceptable results Noise sources: Noise sources: –Take-offs (which are of interest for this study) –Landings –Other planes and helicopters flying at low altitude. Characteristics of noises present: Characteristics of noises present: –Comparable levels –Same frequency domain

8 8 Helicopter Takeoff Landing Fig. 1

9 9 Listen Smart The system should be able to discriminate between these sources and to select only the take offs The system should be able to discriminate between these sources and to select only the take offs Need to determine: Need to determine: –the best parameter for the purpose: LE, Leq, Lmax LE, Leq, Lmax with A or C weighting with A or C weighting filtered parameter (in 1/1 octave band) filtered parameter (in 1/1 octave band) –the measurement resolution (records every/over 1 s, 10 s, 1 min) –the threshold for counting

10 10 Studies in the field: Test conditions: Test conditions: –Advanced instrument that not only recorded the levels but the sound itself. –Each event producing a level over 70 dBAmax, Fast was identified as either a take-off, a helicopter, or a landing. –Airport with one runway Data results: Data results: –The characteristic spectra of the sound produced by the three categories (figure 1 above) –Level time history for different parameters and resolutions Calculated diagrams of repartition (number of occurrences versus level): Calculated diagrams of repartition (number of occurrences versus level): –for each category of events (take-offs, planes, helicopters) –for the acoustical parameters to select from

11 Max level [dB] Helicopters [dB] Take-offs [dB] Landings [dB] 53.02000 56.14000 59.26000 62.38000 65.5010 68.62000 71.741014 74.8612115 77.982047 81.1932 84.22210 87.34071 90.46190 93.58170 96.70140 99.820280 102.940400 106.060130 109.18040 112.3040 Total4613639 LAmax

12 12

13 13 Conclusions to preliminary study Optimum parameter selection Optimum parameter selection –No parameter is obviously optimum Measurement resolution Measurement resolution –Take-off: duration 7-14 sec; separated by min. 30 sec –Best resolution to use: 10 sec Method estimated accuracy: <5% Method estimated accuracy: <5%

14 14 Airports specifics Multiple intersecting runways of different lengths introduce challenges. Multiple intersecting runways of different lengths introduce challenges. Airport geometry can introduce possibility of double counting of take-offs if counter thresholds are set too low. Airport geometry can introduce possibility of double counting of take-offs if counter thresholds are set too low. Runway lengths can vary dramatically underscoring the need for flexibility in establishing thresholds. Runway lengths can vary dramatically underscoring the need for flexibility in establishing thresholds.

15 15 Intersecting Runways KOXB

16 16 Very Short GA Runway 2W2

17 17 Aircraft Operation Counting System RION NL-21 SLM RION NL-21 SLM –Flash card memory –30+ day battery –Type 2 Rugged pelican case Rugged pelican case Custom designed software package: Custom designed software package: –Counts the events –Enters data in reports

18 18 Measurement settings Measured parameter: LAmax Measured parameter: LAmax Resolution: Resolution: –Instrument possibilities: 10 sec or 1 minute 10 sec or 1 minute Memory limitations Memory limitations –Selected: 1 minute New estimated accuracy: 7 % New estimated accuracy: 7 %

19 19 Data treatment software module

20 20 Reports AIRPORT: SEASON:1 FORM 2 : WEEK 1 DATA (A)(B)(E)(F) DAYDATE DAILY OPS COLUMN (B) - (D) COLUMN (E) SQUARED 1 #DIV/0!#DIV/0! 2 #DIV/0!#DIV/0! 3 #DIV/0!#DIV/0! 4 #DIV/0!#DIV/0! 5 #DIV/0!#DIV/0! 6 #DIV/0!#DIV/0! 7 #DIV/0!#DIV/0! SUM (C) 0 SUM (G) #DIV/0! AVG OPS (D) AVG OPS (D)#DIV/0! Transfer (G) to Form 3, Col (K)

21 21 Results Excel based spreadsheet automatically self populates and calculates algorithm for operational estimates. Excel based spreadsheet automatically self populates and calculates algorithm for operational estimates. 7 distinct steps to process data under old, first generation system, NL-21 and new software reduce this # to 2. 7 distinct steps to process data under old, first generation system, NL-21 and new software reduce this # to 2. Reduced manual operation also minimizes errors. Reduced manual operation also minimizes errors. Simpler meters cost less and offer greater reliability. Simpler meters cost less and offer greater reliability.

22 22 Validation of Accuracy Operational experience Operational experience Comparison with other sources (fuel consumption, other records, data history ) Comparison with other sources (fuel consumption, other records, data history ) Coordination is underway to place the units into airports with FAA control towers, the ultimate test of accuracy as all operations are logged at these facilities. Coordination is underway to place the units into airports with FAA control towers, the ultimate test of accuracy as all operations are logged at these facilities.

23 23 Hmmm ? Open to Suggestions

24 24 Contact Info: Jaime Giandomenico Jaime Giandomenico –Aviation Systems Planning Officer Maryland Aviation Administration (410) 859-7689 –JGiandomenico@bwiairport.com Mariana Buzduga, Scantek, Inc. Mariana Buzduga, Scantek, Inc. –BuzdugaM@scantekinc.com Richard J. Peppin, Scantek, Inc. Richard J. Peppin, Scantek, Inc. –PeppinR@scantekinc.com


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