Before diving into the conversion process, it's essential to understand the nature of FRF data. The Frequency Response Function (FRF) is a measure of how a system responds to different frequencies of input signals. It's typically represented as a complex-valued function, which describes the magnitude and phase of the system's response at various frequencies. FRF data is commonly used in fields like mechanical engineering, aerospace, and civil engineering, where it helps in analyzing and characterizing the dynamic behavior of structures, mechanical systems, and other types of systems.
FRF data is usually obtained through experimental measurements, where a system is excited with a range of frequencies, and its response is recorded. The resulting data is a set of complex values representing the system's frequency response, which can be visualized as a frequency response curve. frf to bin
# Define bin boundaries bin_boundaries = np.linspace(0, 100, 10) Before diving into the conversion process, it's essential