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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:
;
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
952823
Report Number(s):
SAND2004-2865C
TRN: US200914%%36
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.
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; AIRCRAFT; OPERATION; DATA ANALYSIS; AUTOMATION; COMPUTERIZED SIMULATION

Citation Formats

Cap, Jerome Scot, and Hensley, Daniel P. An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.. United States: N. p., 2004. Web.
Cap, Jerome Scot, & Hensley, Daniel P. An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.. United States.
Cap, Jerome Scot, and Hensley, Daniel P. Tue . "An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.". United States.
@article{osti_952823,
title = {An automated approach to identifying sine-on-random content from short duration aircraft flight operating data.},
author = {Cap, Jerome Scot and Hensley, Daniel P},
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/952823}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2004},
month = {6}
}

Conference:
Other availability
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