Fourier Transform essentially incorporates a time series of pressure intensity in the determination of the perfect pitched frequencies summation. It also incorporates the level of the amplitude to recreate the original sound. Series of data aids in telling the amplitude of the sound as a function of time to a corresponding series data that determines the amplitude of the frequencies for recreation of the sound.
Based on the graphs collected the ambiguity within the time durations and frequencies measured for diverse sound waves emanated from the errors in the measurement Logger Pro. The percentage error amidst the tuning fork frequency and corresponding measured frequencies was less that 1%, which is relatively safe. The percentage error amidst the printed frequency and the measured frequency was 0.58% as depicted by the sine curve. Undertaking the curve fit is relatively more precise measurement method regarding finding the frequency since it is not subjective to many of individual’s errors.
The concept of Fourier Transforms is fundamental in the examination of the sound waves. Moreover, it integrates a time series of pressure intensity in the resolving the perfect pitched frequencies summation. Series of data display amplitude of the sound as a function of time to a corresponding series data that determines the amplitude of the frequencies for recreation of the sound. There was certain error in the lab experiment that mainly occurs due to the individual’s point of view of the underlying maximum intensity, within is not fundamental to other