Active Noise Control of a Forest Machine Cabin
Today, a high noise level is considered a problem in many working environments. The main reason is that it contributes to stress and fatigue. Traditional methods using passive noise control is only practicable for high frequencies. As a complement to passive noise control, active noise control (ANC) can be used to reduce low frequency noise. The main idea of ANC is to use destructive interference of waves to cancel disturbing noises. The purpose of this thesis is to design and implement an ANC system in the driver's cabin of a Valmet 890 forest machine. The engine boom is one of the most disturbing noises and therefore the main subjective for the ANC system to suppress. The ANC system is implemented on a Texas Instrument DSP development starter kit. Different FxLMS algorithms are evaluated with feedback and feedforward configurations. The results indicate that an ANC system significantly reduces the sound pressure level (SPL) in the cabin. Best performance of the evaluated systems is achieved for the feedforward FxLMS system. For a commonly used engine speed of 1500 rpm, the SPL is reduced with 17 dB. The results show fast enough convergence and global suppression of low frequency noise.
Summary
This master thesis presents the design, implementation, and evaluation of an active noise control (ANC) system for the driver's cabin of a Valmet 890 forest machine. The authors describe FxLMS-based adaptive filtering, secondary-path modeling and a real-time implementation on a Texas Instruments DSP, demonstrating suppression of low-frequency engine boom.
Key Takeaways
- Design an ANC layout for a vehicle cabin including sensor/actuator placement and control objectives.
- Implement and tune FxLMS adaptive algorithms for real-time noise cancellation on fixed-point TI DSP hardware.
- Model and estimate the secondary path to ensure algorithm stability and effective convergence.
- Evaluate ANC performance for low-frequency engine noise and interpret subjective and objective results.
Who Should Read This
Intermediate DSP engineers or graduate students working on adaptive filtering, embedded real-time implementations, or vehicle/industrial cabin noise reduction who want practical guidance from a complete prototype and evaluation.
Still RelevantIntermediate
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