Affiliations: Los Alamos National Laboratory, Engineering Sciences
& Applications, MS T-001, Los Alamos, NM 87545, USA | Motorola Labs, Los Alamos Research Park, 4200 West
Jemez Road, Suite 300, Los Alamos, NM 87544, USA
Note: [] Corresponding author: Charles R. Farrar, Ph.D., Engineering
Sciences & Applications Division, The Engineering Institute, Mail Stop
T001, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. Tel.: +1 505
663 5330; Fax: +1 505 663 5225; E-mail: farrar@lanl.gov
Abstract: The process of implementing a damage detection strategy for
aerospace, civil and mechanical engineering infrastructure is referred to as
structural health monitoring (SHM). The authors' approach is to address the SHM
problem in the context of a statistical pattern recognition paradigm. In this
paradigm, the process can be broken down into four parts: (1) Operational
Evaluation, (2) Data Acquisition and Cleansing, (3) Feature Extraction and Data
Compression, and (4) Statistical Model Development for Feature Discrimination.
These processes must be implemented through hardware or software and, in
general, some combination of these two approaches will be used. This paper will
discuss each portion of the SHM process with particular emphasis on the
coupling of a general purpose data interrogation software package for
structural health monitoring with a modular wireless sensing and processing
platform. More specifically, this paper will address the need to take an
integrated hardware/software approach to developing SHM solutions.
Keywords: Sensing, data Interrogation, software, system integration, structural health monitoring
