Abstract
For embedded impedance spectroscopy, a suitable method for analyzing AC signals needs to be carefully chosen to overcome limited processing capability and memory availability. This paper compares various methods, including the fast Fourier transform (FFT), the FFT with barycenter correction, the FFT with windowing, the Goertzel filter, the discrete-time Fourier transform (DTFT), and sine fitting using linear or nonlinear least squares, and cross-correlation, for analyzing AC signals in terms of speed, memory requirements, amplitude measurement accuracy, and phase measurement accuracy. These methods are implemented in reference systems with and without hardware acceleration for validation. The investigation results show that the Goertzel algorithm has the best overall performance when hardware acceleration is excluded or in the case of memory constraints. In implementations with hardware acceleration, the FFT with barycentre correction stands out. The linear sine fitting method provides the most accurate amplitude and phase determinations at the expense of speed and memory requirements.
Highlights
Alternating Current (AC) Signal analysis plays a key role in signal processing, filtering, and system identification
We compare the computational complexity of all algorithms on a system without hardware acceleration
The AC signal analysis methods were first implemented in a Windows PC reference system using MATLAB and Visual C++
Summary
Alternating Current (AC) Signal analysis plays a key role in signal processing, filtering, and system identification It is very important for impedance spectroscopy, including human body tissue diagnosis [1], battery diagnosis [2], and cable diagnosis [3]. In this method, the impedance of a device-under-test (DUT) is measured at different frequencies. A sine frequency sweep and a magnitude-phase detector are used to calculate the impedance spectrum Alternative excitation signals such as a multisine signal, i.e., the sum of multiple sinewaves, are used instead It enables a shorter measurement time at the expense of more complex signal analysis [4]. Thereby, identifying the amplitude and phases of all the signals within the excitation and response signals can become challenging
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
