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Title: An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.

Abstract

One challenge faced by engineers today is replicating an operating environment such as transportation in a test lab. This paper focuses on the process of identifying sine-on-random content in an aircraft transportation environment, although the methodology can be applied to other events. The ultimate goal of this effort was to develop an automated way to identify significant peaks in the PSDs of the operating data, catalog the peaks, and determine whether each peak was sinusoidal or random in nature. This information helps design a test environment that accurately reflects the operating environment. A series of Matlab functions have been developed to achieve this goal with a relatively high degree of accuracy. The software is able to distinguish between sine-on-random and random-on-random peaks in most cases. This paper describes the approach taken for converting the time history segments to the frequency domain, identifying peaks from the resulting PSD, and filtering the time histories to determine the peak amplitude and characteristics. This approach is validated through some contrived data, and then applied to actual test data. Observations and conclusions, including limitations of this process, are also presented.

Authors:
 [1];
  1. ATA Engineering, Inc., San Diego, CA
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
970242
Report Number(s):
SAND2004-4872C
TRN: US201003%%449
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the 75th Shock and Vibration Symposium held October 17-22, 2004 in Virginia Beach, VA.
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; ACCURACY; AIRCRAFT; AMPLITUDES; DESIGN; ENGINEERS

Citation Formats

Hensley, Daniel P, and Cap, Jerome Scot. An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.. United States: N. p., 2004. Web.
Hensley, Daniel P, & Cap, Jerome Scot. An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.. United States.
Hensley, Daniel P, and Cap, Jerome Scot. Wed . "An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.". United States.
@article{osti_970242,
title = {An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.},
author = {Hensley, Daniel P and Cap, Jerome Scot},
abstractNote = {One challenge faced by engineers today is replicating an operating environment such as transportation in a test lab. This paper focuses on the process of identifying sine-on-random content in an aircraft transportation environment, although the methodology can be applied to other events. The ultimate goal of this effort was to develop an automated way to identify significant peaks in the PSDs of the operating data, catalog the peaks, and determine whether each peak was sinusoidal or random in nature. This information helps design a test environment that accurately reflects the operating environment. A series of Matlab functions have been developed to achieve this goal with a relatively high degree of accuracy. The software is able to distinguish between sine-on-random and random-on-random peaks in most cases. This paper describes the approach taken for converting the time history segments to the frequency domain, identifying peaks from the resulting PSD, and filtering the time histories to determine the peak amplitude and characteristics. This approach is validated through some contrived data, and then applied to actual test data. Observations and conclusions, including limitations of this process, are also presented.},
doi = {},
url = {https://www.osti.gov/biblio/970242}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2004},
month = {9}
}

Conference:
Other availability
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