<![CDATA[Acoustic resonance experiments using closed organ pipes are widely used to study the relationship between sound frequency, wavelength, and air-column length. However, low-cost sensor-based systems often produce unstable acoustic signals contaminated by environmental noise, amplitude fluctuations, and sensor-response variability, making resonance identification difficult. This study aims to develop and evaluate an amplitude-based statistical filtering method to improve signal stability and determine the fundamental resonance position more accurately. The proposed method was evaluated using a closed organ pipe experiment integrated with an acoustic sensor and microcontroller-based data acquisition system. Acoustic signals were processed using amplitude-based statistical filtering to extract dominant resonance responses and improve resonance localization. Statistical evaluation was conducted to analyze signal stability and measurement accuracy. The results showed that the filtering process reduced the standard deviation from 9.24 cm in the raw dataset to 6.72 cm in the final resonance candidates, indicating improved resonance localization stability. The experimental resonance length obtained after filtering was 16.12 cm, while the theoretical resonance length was 16.75 cm, resulting in a relative error of 3.76%. These findings demonstrate that the proposed filtering method can improve resonance detection accuracy using a simple, practical, and computationally efficient approach suitable for low-cost educational laboratory systems.]]>
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