Abstract:This chapter presents signal processing in the frequency domain, which has the ability to divulge information based on frequency characteristics that are not easy to observe in the time domain. It des...This chapter presents signal processing in the frequency domain, which has the ability to divulge information based on frequency characteristics that are not easy to observe in the time domain. It describes Fourier analysis, including Fourier series, discrete Fourier transform, and fast Fourier transform (FFT), which are the most commonly used signal transformation techniques and allow one to transform time domain signals to the frequency domain. With the invention of FFT and digital computers, the efficient computation of the signal's power spectrum became feasible. The spectrum of the frequency components generated from the time domain waveforms makes it easier to see each source of vibration. The chapter provides an explanation of different techniques that can be used to extract various frequency spectrum features that can more efficiently represent a machine's health. These include: envelope analysis, also called high-frequency resonance analysis or resonance demodulation; and frequency domain features.Read More
Publication Year: 2019
Publication Date: 2019-12-06
Language: en
Type: other
Indexed In: ['crossref']
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Cited By Count: 1
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