sdynpy.signal_processing.sdynpy_srs.srs

srs(signal, dt, frequencies=None, damping=0.05, spectrum_type=9, b_filter_weights=None, a_filter_weights=None)[source]

Computes shock response spectrum of a signal

Computes the shock response spectrum using a ramp invariant digital filter simulation of the single degree-of-freedom system.

Parameters

  • signal (np.ndarray) – A shape (…, num_samples) ndarray containing the sampled signals to compute SRSs from.

  • dt (float) – The time between samples (1/sample rate)

  • frequencies (np.ndarray) – An iterable of frequency lines at which the shock response spectrum will be calculated. If not specified, it will be computed from the sample rate/10000 to the sample rate/4 over 50 lines.

  • damping (float) – Fraction of critical damping to use in the SRS calculation (e.g. you should specify 0.03 to represent 3%, not 3). The default is 0.03.

  • spectrum_type (int) –

    The type of spectrum desired: If spectrum_type > 0 (pos) then the SRS will be a base acceleration-absolute acceleration model If spectrum_type < 0 (neg) then the SRS will be a base acceleration-relative displacement model (expressed in equivalent static acceleration units). If abs(spectrum_type) is:

    1–positive primary, 2–negative primary, 3–absolute maximum primary 4–positive residual, 5–negative residual, 6–absolute maximum residual 7–largest of 1&4, maximum positive, 8–largest of 2&5, maximum negative 9 – maximax, the largest absolute value of 1-8

    10 – returns a matrix s(9,length(fn)) with all the types 1-9.

  • b_filter_weights (np.ndarray, optional) – Optional filter weights with shape (frequencies.size,3). The default is to automatically compute filter weights using sdof_ramp_invariant_filter_weights.

  • a_filter_weights (np.ndarray, optional) – Optional filter weights with shape (frequencies.size,3). The default is to automatically compute filter weights using sdof_ramp_invariant_filter_weights.

Returns

  • srs (np.ndarray) – The shock response spectrum at the frequencies specified. If spectrum_type == 10 or -10, then this will have shape (… x 9 x len(frequencies)) where each row is a different type of SRS

  • frequencies (np.ndarray) – The frequencies at which the SRSs were computed.