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.

Full-Field Structural Dynamics by Video Motion Manipulations

Abstract: Structures with complex geometries, material properties, and boundary conditions, exhibit spatially local, temporally transient, dynamic behaviors. High spatial and temporal resolution vibration measurements and modeling are thus required for high-fidelity characterization, analysis, and prediction of the structure’s dynamic phenomena. For example, high spatial resolution mode shapes are needed for accurate vibration-based damage localization. Also, higher order vibration modes typically contain local structural features that are essential for high-fidelity dynamic modeling of the structure. In addition, while it is possible to build a highly-refined mathematical model (e.g., a finite element model) of the structure, it needs to be experimentally validated and updated with high-resolution vibration measurements. However, it is a significant challenge to obtain high-resolution vibration measurements using traditional techniques. For example, accelerometers and strain-gauge sensors provide low spatial resolution measurements. Laser vibrometers provide high-resolution measurements, but are expensive and make sequential measurements that are time-consuming. On the other hand, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation, optical flow), digital video camera based measurements have been successfully used for vibration measurements and subsequent modal analysis, based on techniques such as the digital image correlation (DIC) and the point-tracking. However, they typically require speckle pattern or high-contrast markers to be placed on the surface of structures, which poses challenges when the measurement area is large or inaccessible.

A compliant mechanism for inspecting extremely confined spaces

Abstract: We present a novel, compliant mechanism that provides the capability to navigate extremely confined spaces for the purpose of infrastructure inspection. Extremely confined spaces are commonly encountered during infrastructure inspection. Examples of such spaces can include pipes, conduits, and ventilation ducts. Often these infrastructure features go uninspected simply because there is no viable way to access their interior. In addition, it is not uncommon for extremely confined spaces to possess a maze-like architecture that must be selectively navigated in order to properly perform an inspection. Efforts by the imaging sensor community have resulted in the development of imaging sensors on the millimeter length scale. Due to their compact size, they are able to inspect many extremely confined spaces of interest, however, the means to deliver these sensors to the proper location to obtain the desired images are lacking. To address this problem, we draw inspiration from the field of endoscopic surgery. Specifically we consider the work that has already been done to create long flexible needles that are capable of being steered through the human body. These devices are typically referred to as 'steerable needles.' Steerable needle technology is not directly applicable to the problem of navigating maze-like arrangements of extremely confined spaces, but it does provide guidance on how this problem should be approached. Specifically, the super-elastic nitinol tubing material that allows steerable needles to operate is also appropriate for the problem of navigating maze-like arrangements of extremely confined spaces. Furthermore, the portion of the mechanism that enters the extremely confined space is completely mechanical in nature. The mechanical nature of the device is an advantage when the extremely confined space features environmental hazards such as radiation that could degrade an electromechanically operated mechanism. Here, we present a compliant mechanism developed to navigate maze-like arrangements of extremely confined spaces. The mechanism is shown to be able to selectively navigate past three 90° bends. The ability to selectively navigate extremely confined spaces opens up new possibilities to use emerging miniature imaging technology for infrastructure inspection.

Static load cycle testing of a very low-aspect-ratio six-inch wall TRG-type structure TRG-6-6 (0. 27, 0. 50)

Abstract: This test report is the third for a series of tests carried out by the Los Alamos National Laboratory under the sponsorship of the United States Nuclear Regulatory Commission's Division of Engineering. This research program has a Technical Review Group that recommended test geometries and sizes for the tests. The quasi-static load cycle testing of a totally shear-dominated structure (bending deformation negligible) made of 6-inch-thick reinforced concrete walls is reported herein. The background of the program and the results that led to this series of experiments is first reviewed for continuity. Next, the geometry of the test structure, the design parameters, and the construction of the structure, including the material property tests, are reported. Both modal analysis and modal testing were done to verify the undamaged dynamic properties of the structure. Finally, the results of the quasi-static cyclic testing are reported in detail. Results are compared with other investigations and with the American Concrete Institute (ACI) 349-85 code predictions. 25 refs., 32 figs., 6 tabs.

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.