Svantek » Case Studies » Noise Source Identification

Case Study:
Noise Source Identification in Aircraft Noise Monitoring

Improved Accuracy of Aircraft Noise Measurement Using Noise Directivity in the SVANTEK SV 200A

Introduction

Ensuring Data Accuracy in Airport Noise Monitoring Environments

Accurately monitoring aircraft noise is critical for environmental compliance, especially in areas near airports. During routine monitoring, an unusual noise event was detected — a barking dog seemingly coming from above a 4-meter-high microphone. The incident highlighted the impact of site selection on measurement accuracy and underscored the role of ISO 1996-2:2017 guidance in eliminating residual and non-relevant sound sources.

Measurement Operator

SVANTEK Consultants

The project was conducted by SVANTEK Consultants, experts in environmental noise monitoring. Using the SV 200A Noise Monitoring Station, they set up two measurement points near an airport — one near buildings and one in an open field. Both locations were aligned with aircraft flight paths and configured in compliance with ISO standards, enabling a direct comparison of how site surroundings affect measurement accuracy and automated event classification.

Challenge

Identifying and Filtering Unwanted Sound Events in Real Environments

Aircraft noise monitoring in real environments often encounters interference from unrelated sound sources and reflections. The main challenge was to:

Identify and classify sound events automatically
Distinguish between true aircraft noise and unwanted sounds
Evaluate how site conditions affect the accuracy of data and the performance of automated event classification

Location of the monitoring points

Technology Used

Noise Monitoring Station from SVANTEK

SvanPC++ Software

SV 200A & SvanPC++

Expert Insight

Noise Directivity and GPS Enable Reliable Aircraft Noise Assessment

“The site where you place your microphone has a direct impact on how well you can automate aircraft noise classification. With SV 200A’s directional analysis, GPS, and audio playback, we not only improved measurement accuracy — we also proved that sometimes it’s not the source, but the reflection that misleads the data.”

Jacek Kuczyński, Environmental Noise Expert

SvanPC++ software in a Google Maps Satellite mode

Result

Measurement site selection significantly influenced event classification accuracy

Open-field location (Point B) enabled automated and accurate aircraft noise detection

Urban location (Point A) caused false positives due to sound reflections

Post-processing tools like audio, GPS, and noise directivity ensured reliable event verification

Selection of aircraft passages

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