Matlab Batch Process via Vibrationdata GUI

batch

I have added batch processing as an option for time histories as shown above.  I will add more options in upcoming revisions.  The Vibrationdata Matlab GUI package is given at: Vibrationdata Matlab Signal Analysis Package

Here are some sample input files for practicing batch processing: batch_sample.mat

Tom Irvine

SDOF Response to Sine or Sine Sweep Base Input, Rainflow

sdof_base_image

Rainflow fatigue cycles can be easily calculated for a single-degree-of-freedom subjected to a sine or sine sweep base input.  The reason is that each pair of consecutive positive and negative response peaks forms a half-cycle.

The relative fatigue damage can then be calculated from the rainflow cycles.

Here are Matlab scripts for performing the rainflow and damage calculations.  rainflow_sine.zip

rainflow_sine.m is for the case where the natural frequency is known.

rainflow_sine_fds.m gives the fatigue damage spectrum for a family of natural frequencies.

The remaining scripts are supporting functions.

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See also:

Rainflow Cycle Counting

ramp_invariant_base.pdf

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– Tom Irvine

Webinar 22 – Integration and Differentiation of Time Histories & Spectral Functions

PowerPoint File:

webinar_22_integration_part_2.ppt

Audio/Visual File:

NESC Academy Integration and Differentiation – Recommend viewing in Firefox with Sliverlight Plugin

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ASCII Text Data Files:

navmat_spec.psd

two_wheeled_trailer_vertical.txt

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Matlab script: Vibrationdata Signal Analysis Package

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Python version:
Unit_22_integration_part_2_python.ppt

Python Signal Analysis Package GUI

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See also:

Vibrationdata Webinars

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– Tom Irvine

Pierson-Moskowitz Spectrum

The Pierson–Moskowitz (PM) spectra is an empirical relationship that defines the distribution of energy with frequency within the ocean. The result is given as a wave height power spectra density.

Developed in 1964, the PM spectrum is one of the simplest descriptions for the energy distribution. It assumes that if the wind blows steadily for a long time over a large area, then the waves will eventually reach a point of equilibrium with the wind.

This is known as a fully developed sea. Pierson and Moskowitz developed their spectrum from measurements in the North Atlantic during 1964.

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Here is a paper: wave_height.pdf

Here is a Matlab script: ocean_wave_PSD.m

– Tom Irvine

Fatigue Damage for a Stress Response PSD

Here is a paper.

Estimating Fatigue Damage from Stress Power Spectral Density Functions: estimate_fatigue_psd.pdf

Note that the duration for the example in the paper was 600 sec.

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This following Matlab program calculates the cumulative rainflow fatigue damage for an input stress PSD using the following wideband methods:

1. Wirsching & Light
2. Ortiz & Chen
3. Lutes & Larsen, Single-Moment
4. Benasciutti & Tovo, alpha 0.75
5. Dirlik
6. Zhao & Baker

Reference:

Random Vibrations: Theory and Practice (Dover Books on Physics)

The stress PSD and the fatigue strength coefficient must have consistent stress units.

The input PSD must have two columns: freq(Hz) & stress(unit^2/Hz)

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Main scripts:

stress_psd_fatigue.zip

Vibrationdata Signal Analysis Package

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The following values are “For Reference Only.”

m = fatigue exponent
A = fatigue strength coefficient

Aluminum 6061-T6 with zero mean stress

m=9.25
A=9.7724e+17 (ksi^9.25)
A=5.5757e+25 (MPa^9.25)

Butt-welded Steel Joints

m=3.5
A=1.255e+11 (ksi^3.5)
A=1.080e+14 (MPa^3.5)

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See also:

Rainflow Fatigue

Mrsnik, Janko Slavic, Boltezar, Frequency-domain methods for a vibration-fatigue-life estimation – Application to real data:  mrsnik_article_vib_fatigue.pdf

Spectral Moments Notes

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– Tom Irvine

Webinar 21 – Integration & Differentiation of Time Histories

PowerPoint File:

Unit_21_integrate_differentiate.ppt

Audio/Visual File:

NESC Academy  Integration and Differentiation, Part 1 – Recommend viewing in Firefox with Sliverlight Plugin

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Pyrotechnic Shock File:

pyro_test.txt – time(sec) & accel(G)

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Matlab script: Vibrationdata Signal Analysis Package

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Python Version:

Unit_21_integrate_differentiate_python.ppt

Python script: Python Signal Analysis Package GUI

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See also:

Vibrationdata Webinars

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– Tom Irvine

Webinar 19 – Digital Filtering

PowerPoint File:

webinar_19_digital_filtering.ppt

Audio/Visual File:

NESC Academy Digital Filtering – Recommend viewing in Firefox with Sliverlight plugin

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Python version:

webinar_19_digital_filtering_python.ppt

Python script: Python Signal Analysis Package GUI

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Data:  sm.txt     –  unscaled relative displacement vs. time (sec)

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Reference Paper:

An Introduction to the Filtering of Digital Signals:  filter.pdf

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Matlab script: Vibrationdata Signal Analysis Package

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See also:

Vibrationdata Webinars

USGS, Solomon Island Earthquake, October 8, 2004

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If you would like to be included on the distribution list for the Webinar series, please send an Email to: tom@irvinemail.org

Thank you,
Tom Irvine

Webinar 18 – Force Vibration Response Spectrum

PowerPoint File:

webinar_18_force_VRS.pptx

Audio/Visual File:

NESC Academy Force_VRS

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Python version:

webinar_18_force_VRS_python.pptx – Recommend viewing in Firefox with Sliverlight plugin

Python script: Python Signal Analysis Package GUI

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Reference Papers:

The Steady-state Response of Single-degree-of-freedom System to a Harmonic Excitation Force: sforce.pdf

Derivation of Miles Equation for an Applied Force: Miles_force.pdf

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Matlab script: Vibrationdata Signal Analysis Package

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See also: Vibrationdata Webinars

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– Tom Irvine

Webinar 17 – SDOF Response to Applied Force

PowerPoint File:

webinar_17_SDOF_force.pptx

Audio/Visual File:

NESC Academy SDOF – Response to Applied Force – Recommend viewing in Firefox with Sliverlight plugin

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Reference Papers:

T. Irvine, Machine Mounting for Vibration Attenuation, Rev B, Vibrationdata, 2000 link

Bruel & Kjaer Booklets:
Mobility Measurement link
Modal Testing link

Additional reference papers are posted at:

Response of an SDOF System to an Applied Force PSD or Acoustic SPL

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Matlab script: Vibrationdata Signal Analysis Package

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Python version:

webinar_17_SDOF_force_python.pptx

Python script: Python Signal Analysis Package GUI

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See also: Vibrationdata Webinars

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– Tom Irvine

Webinar 16 – Vibration Response Spectrum

PowerPoint File:

Webinar_16_VRS.pptx

Audio/Visual File:

NESC Academy VRS  – Recommend viewing in Firefox with Sliverlight plugin

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Python Version

Webinar_16_VRS_python.pptx

Python script: Python Signal Analysis Package GUI

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PSD Data Files:

webinar_16_data_files.mat

webinar_16_data_files.zip

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Reference Paper:

An Introduction to the Vibration Response Spectrum link

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Matlab script:  Vibrationdata Signal Analysis Package

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See also: Vibrationdata Webinars

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– Tom Irvine