A Distance e-Learning Platform for FFT-Based Signal Analysis and Measurement

Abstract

The fast fourier transform (FFT) and the power spectrum are still powerful tools for analyzing and measuring both stationary and transient signals with power system harmonics in power systems. However, the misapplications of FFT can lead to incorrect results caused by some problems such as aliasing effect, spectral leakage and picket-fence effect. Measurement errors can be efficiently reduced by understanding fundamentals of FFT as well as using windows, etc. This paper develops an e- learning and distance learning environment using a graphical programming tool to help electrical students and engineers to enhance their measurement skills in signal analysis via the Internet explorer (IE). Critical issues pertaining to engineering education, such as design of course, expected learning outcomes, assessment of student performance, and course evaluation are discussed in detail.