What is the name of the process used when we convert a time waveform into a vibration spectrum?

The process used to convert a time waveform into a vibration spectrum is known as the Fast Fourier Transform (FFT). The FFT is an efficient algorithm that computes the Discrete Fourier Transform (DFT) and its inverse, allowing for the analysis of frequency components within a time-domain signal. By applying the FFT to a time waveform, you can represent the signal in the frequency domain, which highlights the different frequency components and their amplitudes. This conversion is crucial in vibration analysis as it enables the identification of specific frequencies associated with mechanical faults and helps in diagnosing issues in machinery.

Other methods mentioned, such as waveform analysis and signal decomposition, may pertain to various aspects of signal processing, but they do not specifically refer to the mathematical transformation that converts time-domain data into frequency-domain information. Time-frequency analysis involves examining how the frequency components of a signal change over time but doesn't directly describe the conversion process into a vibration spectrum. Thus, FFT stands out as the standard and most efficient method in vibration analysis for this purpose.