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Aircraft Cabin Noise Analysis
Aircraft cabin noise analysis is critical for passenger comfort and communication system design. Our Frequency Domain Identification Toolbox provides powerful tools for characterizing acoustic transfer functions in complex environments like airplane cabins.
The Challenge
In this case study, we needed to investigate noise propagation properties in an aircraft cabin by measuring the transfer function between a loudspeaker and a microphone. This included:
- Capturing the full system dynamics including DAC conversion effects
- Working with a physical delay (approximately 5 sampling periods at 1300 Hz)
- Identifying an appropriate model from frequency domain measurements
- Creating a model suitable for real-time digital control implementation
Measurement Setup
The measurement captured the input-output relationship of digital sine waves from 75 Hz to 400 Hz. The physical distance between the loudspeaker and microphone was approximately 1.3 meters. Extensive averaging was performed for each sine wave to minimize measurement noise (estimated output variance of 1e-5).
Solution Approach
Using our Frequency Domain Identification Toolbox, we explored various model structures to find the most suitable representation:
1) IIR Model Identification: We initially tested rational transfer function models of various orders, finding that models of order 40/40 or higher provided good fits to the measured data.
2) FIR Model Alternative: For implementation simplicity, we also identified FIR models, accounting for their intrinsic delay by specifying a negative delay parameter of -30 samples. An AR model has the advantage that it is straightforward to invert. However, the sharp valleys call for a rather high order.
Results
The toolbox successfully identified multiple model options with different tradeoffs:
- IIR models provided the highest accuracy but required careful stability analysis
- FIR models offered simpler implementation with acceptable accuracy
- High-order AR models enabled straightforward system inversion for control applications
Conclusion
This case study demonstrates how our Frequency Domain Identification Toolbox enables engineers to identify complex acoustic systems from frequency domain measurements. The flexibility to explore different model structures (IIR, FIR, AR) with appropriate delay compensation makes it ideal for practical engineering applications where implementation constraints must be balanced with model accuracy.