Showing papers by "Charles R. Farrar published in 2013"

A preliminary cyber-physical security assessment of the Robot Operating System (ROS)

Abstract: Over the course of the last few years, the Robot Operating System (ROS) has become a highly popular software framework for robotics research. ROS has a very active developer community and is widely used for robotics research in both academia and government labs. The prevalence and modularity of ROS cause many people to ask the question: “What prevents ROS from being used in commercial or government applications?” One of the main problems that is preventing this increased use of ROS in these applications is the question of characterizing its security (or lack thereof). In the summer of 2012, a crowd sourced cyber-physical security contest was launched at the cyber security conference DEF CON 20 to begin the process of characterizing the security of ROS. A small-scale, car-like robot was configured as a cyber-physical security “honeypot” running ROS. DEFFCON-20 attendees were invited to find exploits and vulnerabilities in the robot while network traffic was collected. The results of this experiment provided some interesting insights and opened up many security questions pertaining to deployed robotic systems. The Federal Aviation Administration is tasked with opening up the civil airspace to commercial drones by September 2015 and driverless cars are already legal for research purposes in a number of states. Given the integration of these robotic devices into our daily lives, the authors pose the following question: “What security exploits can a motivated person with little-to-no experience in cyber security execute, given the wide availability of free cyber security penetration testing tools such as Metasploit?” This research focuses on applying common, low-cost, low-overhead, cyber-attacks on a robot featuring ROS. This work documents the effectiveness of those attacks.

Compressed sensing techniques for detecting damage in structures

Abstract: One of the principal challenges facing the structural health monitoring community is taking large, heterogeneous sets of data collected from sensors, and extracting information that allows the estimation of the damage condition of a structure Another important challenge is to collect relevant data from a structure in a manner that is cost-effective, and respects the size, weight, cost, energy consumption and bandwidth limitations placed on the system In this work, we established the suitability of compressed sensing to address both challenges A digital version of a compressed sensor is implemented on-board a microcontroller similar to those used in embedded SHM sensor nodes The sensor node is tested in a surrogate SHM application using acceleration measurements Currently, the prototype compressed sensor is capable of collecting compressed coefficients from measurements and sending them to an off-board processor for signal reconstruction using l1 norm minimization A compressed version of the matched

Machine Learning Applications for a Wind Turbine Blade under Continuous Fatigue Loading

Abstract: Structural health monitoring (SHM) systems will be one of the leading factors in the successful establishment of wind turbines in the energy arena. Detection of damage at an early stage is a vital issue as blade failure would be a catastrophic result for the entire wind turbine. In this study the SHM analysis will be based on experimental measurements of vibration analysis, extracted of a 9m CX-100 blade under fatigue loading. For analysis, machine learning techniques utilised for failure detection of wind turbine blades will be applied, like non-linear Neural Networks, including Auto-Associative Neural Network (AANN) and Radial Basis Function (RBF) networks models.

Real-Time Condition Assessment of RAPTOR Telescope Systems

Abstract: The RAPid Telescopes for Optical Response (RAPTOR) observatory network consists of several ground-based, autonomous, robotic, astronomical observatories primarily designed to search for astrophysical transients called gamma-ray bursts. To make these observations, however, the RAPTOR telescopes must remain in peak operating condition at a high duty-cycle. Currently, the telescopes are maintained in an ad hoc manner, often in a run-to-failure mode. The required maintenance logistics are further complicated by the fact that many of the observatories are situated in remote locations. To ameliorate this situation, an effort has been initiated to develop a structural health monitoring (SHM) system capable of real-time, remote assessment of the RAPTOR telescopes. This paper summarizes the results from that effort. Common damage scenarios are identified to guide the instrumentation of the telescope system. A comprehensive analysis of the data acquired during experimental testing is then presented, highlig...

Development of a novel human-machine interface exploiting sensor substitution for structural health monitoring

Abstract: For the last 20 years the goal of the structural health monitoring community has been to endow man-made structures with a biologically-inspired nervous system in order to detect, localize, and quantify damage in structures. The effort has focused on collecting a wide array of measurements from sensor networks, extracting features from the data, comparing the data to models, and trying to use this information to determine the presence, extent and type of damage. Typically the Structural Health Monitoring community tries to make predictions of the remaining service life of the structure. It is generally assumed that there will be as little human intervention in this process as possible unless a high-consequence decision must be made. A number of advances have been made in structural health monitoring using this approach over the course of the last decade, but we are still struggling to build autonomous machines that can match the ability of a human to detect, localize and quantify damage in structures. This work aims to explore a new paradigm - cooperative human-machine structural health monitoring. The premise of this paradigm is the idea that a human cooperating with a machine will always significantly outperform a machine or human acting independently. There is no reason to not make full use of human resources that are available to us today. Furthermore, the regulatory and litigious environments that exist today for safety-critical structures are going to make it difficult to adopt health monitoring systems that effectively eliminate humans. Why not instead enhance the natural sensing and perception of human inspectors? During the course of this research effort a vibro-tactile haptic interface is under development that will in some sense allow a human to “feel” the pain of a structure when it is damaged. A number of different studies from the neuroscience community [1], [2], have indicated that it is possible to use “sensory substitution” to provide some restoration for lost senses such as sight. In this work we consider the possibility of extending the introception of a human to an external structure. This type of capability will help enable a wide variety of cyber-physical systems that must maintain reliability as well as interact with humans. For instance it may be possible to outfit a single human inspector with a haptic interface so they can single-handedly monitor a whole wind farm as if it were a natural extension of their own body. Alternatively, a single person with a haptic interface may be able to sense the state-of-health of a large ocean linear or an entire swarm of flying robots. These ideas will lead to creating a new class of high-performance, cyber-physical systems.

Damage Detection in RAPTOR Telescope Systems Using Time-Frequency Analysis Methods

Abstract: The RAPTOR telescope systems are astronomical observatories that operate in remote locations in New Mexico searching for astrophysical transients called gamma-ray bursts. Their operating condition should remain at good levels in order to have accurate observations. Currently, the first component of the RAPTOR telescopes to fail is a capstan driving mechanism that operates in a run-to failure mode. The capstans wear relatively frequently because of their manufacturing material and can cause damage to other more expensive components, such as the drive wheels and the telescope optics. Monitoring the condition of these systems seems a reasonable solution since the unpredictable rate at which the capstans experience wear, in combination with the remote locations and high duty cycles of these telescope systems, make it unprofitable to choose a strategy of replacing the capstans at chosen intervals. Experimental tests of the telescope systems reported here recorded vibration signals during clockwise and counterclockwise rotations, similar to a motion known as "homing-sequence". The Empirical Mode Decomposition (EMD) method in combination with the Hilbert Transform (HT) and a new alternative method for the estimation of the instantaneous features of a signal that applies an energy tracking operator, called Teager-Kaiser Energy operator, and an energy separation algorithm to the data being analysed, are the time-frequency analysis methods used for analysis here.

Structural Health Monitoring of Research-Scale Wind Turbine Blades

Abstract: This paper presents ongoing work by the authors to implement real-time structural health monitoring (SHM) systems for operational research-scale wind turbine blades. The authors have been investigating and assessing the performance of several techniques for SHM of wind turbine blades using piezoelectric active sensors. Following a series of laboratory vibration and fatigue tests, these techniques are being implemented using embedded systems developed by the authors. These embedded systems are being deployed on operating wind turbine platforms, including a 20-meter rotor diameter turbine, located in Bushland, TX, and a 4.5-meter rotor diameter turbine, located in Los Alamos, NM. The SHM approach includes measurements over multiple frequency ranges, in which diffuse ultrasonic waves are excited and recorded using an active sensing system, and the blades global ambient vibration response is recorded using a passive sensing system. These dual measurement types provide a means of correlating the effect of potential damage to changes in the global structural behavior of the blade. In order to provide a backdrop for the sensors and systems currently installed in the field, recent damage detection results for laboratory-based wind turbine blade experiments are reviewed. Our recent and ongoing experimental platforms for field tests are described, and experimental results from these field tests are presented. LA-UR-12-24691.

Experimental Characterization and Predictive Modeling of a Residential-Scale Wind Turbine

Abstract: As the demand for wind energy increases, industry and policymakers have been pushing to place larger wind turbines in denser wind farms. Furthermore, there are higher expectations for reliability of turbines, which require a better understanding of the complex interaction between wind turbines and the fluid flow that drives them. As a test platform, we used the Whisper 500 residential scale wind turbine to support structural and atmospheric modeling efforts undertaken to improve understanding of these interactions. The wind turbine’s flexible components (blades, tower, etc.) were modeled using finite elements, and modal tests of these components were conducted to provide data for experimental validation of the computational models. Finally, experimental data were collected from the wind turbine under real-world operating conditions. The FAST (Fatigue, Aerodynamics, Structures, and Turbulence) software developed at the National Renewable Energy Laboratory was used to predict total system performance in terms of wind input to power output along with other experimentally measurable parameters such as blade tip and tower top accelerations. This paper summarizes the laboratory and field test experiments and concludes with a discussion of the models’ predictive capability. LA-UR-12-24832.

Structural Identification for Selection, Application, and Calibration of Physics-Based Models

Abstract: Note: Chapter 5, Structural Identification of Constructed Systems Reference EPFL-CHAPTER-191194 Record created on 2013-12-10, modified on 2016-08-09

Data Processing and Direct Data Interpretation

Abstract: Note: Chapter Reference EPFL-CHAPTER-191195 Record created on 2013-12-10, modified on 2016-08-09