Title page for ETD etd-09202004-124038

Type of Document Master's Thesis
Author Allen, David W
Author's Email Address dallen@lanl.gov
URN etd-09202004-124038
Title Software for Manipulating and Embedding Data Interrogation Algorithms Into Integrated Systems
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Inman, Daniel J. Committee Chair
Park, Gyuhae Committee Member
Robertshaw, Harry H. Committee Member
  • Extreme Value Statistics
  • Integrated Systems
  • Data Interrogation
  • Structural Health Monitoring
  • Embedded Systems
  • JAVA Software
  • Time Series Modeling
  • Process Development
  • Statistical Discrimination
Date of Defense 2004-08-31
Availability unrestricted
In this study a software package for easily creating and embedding structural health monitoring (SHM) data interrogation processes in remote hardware is presented. The software described herein is comprised of two pieces. The first is a client to allow graphical construction of data interrogation processes. The second is node software for remote execution of processes on remote sensing and monitoring hardware. The client software is created around a catalog of data interrogation algorithms compiled over several years of research at Los Alamos National Laboratory known as DIAMOND II. This study also includes encapsulating the DIAMOND II algorithms into independent interchangeable functions and expanding the catalog with work in feature extraction and statistical discrimination. The client software also includes methods for interfacing with the node software over an Internet connection. Once connected, the client software can upload a developed process to the integrated sensing and processing node. The node software has the ability to run the processes and return results. This software creates a distributed SHM network without individual nodes relying on each other or a centralized server to monitor a structure.

For the demonstration summarized in this study, the client software is used to create data collection, feature extraction, and statistical modeling processes. Data are collected from monitoring hardware connected to the client by a local area network. A structural health monitoring process is created on the client and uploaded to the node software residing on the monitoring hardware. The node software runs the process and monitors a test structure for induced damage, returning the current structural-state indicator in near real time to the client.

Current integrated health monitoring systems rely on processes statically loaded onto the monitoring node before the node is deployed in the field. The primary new contribution of this study is a software paradigm that allows processes to be created remotely and uploaded to the node in a dynamic fashion over the life of the monitoring node without taking the node out of service.

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