Rotating shafts experience a an elliptical motion called whirl. It is important to decompose this motion into a forward and backward whil orbits. The current function makes use of two sensors to generate a bi-directional spectrogram. The method can be extended to any time-frequency distribution
％
％ compute the forward/backward Campbell/specgtrogram
％
％ INPUT:
％ y (n x 2) each column is measured from a different sensor
％ ///////
％ __
％ |s1| y(:,1)
％ |__|
％ __
％ / \ ________|/
％ | | | s2 |/ y(:,2)
％ \____/ --------|/
％
％ Fs Sampling frequnecy
％
％ OUTPUT:
％ B spectrogram/Campbel diagram
％ x x-axis coordinate vector (time or Speed)
％ y y-axis coordinate vector (frequency [Hz])
For developers using FPGAs for the
implementation of floating-point DSP
functions, one key challenge is how to
decompose the computation algorithm
into sequences of parallel hardware
processes while efficiently managing data flow through the parallel pipelines of these processes.
In this paper we revisit hybrid analog-digital precoding systems with emphasis on their modelling
and radio-frequency (RF) losses, to realistically evaluate their benefits in 5G system implementations.
For this, we decompose the analog beamforming networks (ABFN) as a bank of commonly used RF
components and formulate realistic model constraints based on their S-parameters. Specifically, we
concentrate on fully-connected ABFN (FC-ABFN) and Butler networks for implementing the discrete
Fourier transform (DFT) in the RF domain. The results presented in this paper reveal that the performance
and energy efficiency of hybrid precoding systems are severely affected, once practical factors are
considered in the overall design. In this context, we also show that Butler RF networks are capable of
providing better performances than FC-ABFN for systems with a large number of RF chains.
