Estimates the modal parametric model of a univariate or multivariate (vector) time series. The modal parameters include magnitude, phase, damping factor, and natural frequency. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.


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Inputs/Outputs

  • c1ddbl.png Xt —

    Xt specifies the univariate time series.

  • cu16.png method —

    method specifies the method to use in estimating the frequency component of the time series.

  • ci32.png model order —

    model order specifies the model order. The value of model order must be at least twice the number of frequency components you want to estimate. The default is 4.

  • cerrcodeclst.png error in (no error) —

    error in describes error conditions that occur before this node runs. This input provides standard error in functionality.

  • cdbl.png noise subspace (%) —

    noise subspace specifies the percentage of frequency components due to noise in the time series. The default is 50. This option is available only when method is Matrix Pencil.

  • i1dnclst.png frequency components —

    frequency components returns information about the estimated frequency components.

  • idbl.png frequency —

    frequency returns the estimated frequency of the frequency component.

  • idbl.png damping factor —

    damping factor returns the estimated damping factor of the frequency component.

  • idbl.png magnitude —

    magnitude returns the estimated magnitude of the frequency component.

  • idbl.png phase —

    phase returns the estimated phase of the frequency component.

  • ierrcodeclst.png error out —

    error out contains error information. This output provides standard error out functionality.

    • TSA Modal Parametric Modeling Details

    For a univariate impulse response time series, this VI estimates the modal parametric model according to the following equation:

    where ht is the univariate impulse response series, and n is the model order.

    ai denotes one of the complex amplitudes, which is defined as:

    ai = riejq

    where r is magnitude, and q is phase.

    Si is one of the modal poles, which is defined as:

    Si = a + j2pf

    where a is damping factor, and f is frequency.

    For a multivariate impulse response time series, this VI estimates the modal parametric model according to the following equation:

    where Ht is the multivariate impulse response series. Ht is a k×1 vector with k variables that come from k sources. Ai is a k×1 complex amplitude vector with k variables. AiT=(a1i,…,aki). Si is one of the modal poles. n is the model order.

    Refer to the univariate modal parametric model for the descriptions of aki in the vector Ai.

    Examples

    Refer to the following VIs for examples of using the TSA Modal Parametric Modeling VI:

    • Modal Analysis of a Plate VI: labview\examples\Time Series Analysis\TSAApplications
    • Frequency Components VI: labview\examples\Time Series Analysis\TSAGettingStarted