Charles R. Farrar

Bio: Charles R. Farrar is an academic researcher from Los Alamos National Laboratory. The author has contributed to research in topics: Structural health monitoring & Sensor node. The author has an hindex of 70, co-authored 357 publications receiving 26338 citations. Previous affiliations of Charles R. Farrar include Analysis Group.

Structural health monitoring for ship structures

Abstract: Currently the Office of Naval Research is supporting the development of structural health monitoring (SHM) technology for U.S. Navy ship structures. This application is particularly challenging because of the physical size of these structures, the widely varying and often extreme operational and environmental conditions associated with these ships missions, lack of data from known damage conditions, limited sensing that was not designed specifically for SHM, and the management of the vast amounts of data that can be collected during a mission. This paper will first define a statistical pattern recognition paradigm for SHM by describing the four steps of (1) Operational Evaluation, (2) Data Acquisition, (3) Feature Extraction, and (4) Statistical Classification of Features as they apply to ship structures. Note that inherent in the last three steps of this process are additional tasks of data cleansing, compression, normalization and fusion. The presentation will discuss ship structure SHM challenges in the context of applying various SHM approaches to sea trials data measured on an aluminum multi-hull high-speed ship, the HSV-2 Swift. To conclude, the paper will discuss several outstanding issues that need to be addressed before SHM can make the transition from a research topic to actual field applications onmore » ship structures and suggest approaches for addressing these issues.« less

Workshop on transitioning structural health monitoring technology to military platforms

Abstract: Interest in structural health monitoring/management is attracting lots of attention across a spectrum that ranges from sensor developers to end users. The US military, in particular, is making a concerted effort to implement condition-based maintenance as a means of reducing the life cycle costs and improving availability of various weapon platforms. Despite this effort, the majority of installed health monitoring systems are limited to rotating machinery such as engines, transmissions, and other gear boxes. The goal of this workshop was to bring together representatives from military, industry, and academia covering the spectrum from hardware developers to end users and platform managers and have them discuss issues that must be addressed as structural health monitoring systems mature to the point that managers will implement them. This article describes those discussions and highlights important issues that need to be addressed as structural health monitoring systems make the transition from laboratory ...

Piezoelectric active sensing techniques for damage detection on wind turbine blades

Abstract: This paper presents the performance of a variety of structural health monitoring (SHM) techniques, based on the use of piezoelectric active sensors, to determine the structural integrity of a 9m CX-100 wind turbine blade (developed by Sandia National Laboratory). First, the dynamic characterization of a CX-100 blade is performed using piezoelectric transducers, where the results are compared to those by conventional accelerometers. Several SHM techniques, including Lamb wave propagations, frequency response functions, and time series based methods are then utilized to analyze the condition of the wind turbine blade. The main focus of this research is to assess and construct a performance matrix to compare the performance of each method in identifying incipient damage, with a special consideration given the issues related to field deployment. Experiments are conducted on a stationary, full length CX-100 wind turbine blade. This examination is a precursor for planned full-scale fatigue testing of the blade and subsequent tests to be performed on an operational CX-100 Rotor Blade to be flown in the field.

System and method for automated extraction of high resolution structural dynamics from video

Abstract: A method for extracting vibrational modes of a structure includes: receiving a plurality of video frames, each of the video frames including a plurality of pixels; decomposing each of the video frames on a plurality of spatial scales in accordance with complex steerable pyramid filters to obtain a filter response for each of the spatial scales; computing a plurality of local phases of the pixels of each frame; removing a temporal mean from each frame to obtain a plurality of factored vibration motion functions; performing principal component analysis on the factored vibration motion functions to obtain principal components; blind source separating the principal components to compute a plurality of modal coordinates; computing frequency and damping ratios in accordance with the modal coordinates; and outputting the computed frequency and damping ratios.

A comprehensive monitoring system for damage identification and location in large structural and mechanical systems

Abstract: This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project conducted at the Los Alamos National Laboratory (LANL). This project has focused on developing and experimentally verifying a suite of analytical tools for identifying the onset of damage in structural and mechanical systems from changes in their vibration characteristics. A MATLAB-based computer code referred to as Damage Identification And Modal aNalysis of Data @IAMOND) was developed. The code was then extensively exercised on data obtained from a variety of test structures. The most notable structure was an in situ bridge located ten mile north of Truth or Consequences, New Mexico. The suite of tools contained in DIAMOND is now being applied to the nuclear weapons enhanced surveillance program and an industrial partner has asked to enter into a partnership so that they can implement routines from DIAMOND into their commercial damage assessment hardware for large civil engineering structures. Because of the large volume of requests from around the world for DIAMOND, it can now be downloaded from the web site: http://esaea-www.esa.lanl.gov/damagejd. Background and Research Objectives The interest in the ability to monitor a structure and detect damage at the earliest possible stage is pervasive throughout the civil, mechanical, and aerospace engineering communities. Current damage detection methods are either visual or localized experimental methods such as acoustic or resonant ultrasonic (RUS) methods, magnetic field methods, "Principal Investigator, e-mail: farrar@lanl.gov

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Anomaly detection: A survey

Abstract: Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

Abstract: This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.