Despite advances in computational cognition, there are many cyber-physical systems where human supervision and control is desirable. One pertinent example is the control of a robot arm, which can be found in both humanoid and commercial ground robots. Current control mechanisms require the user to look at several screens of varying perspective on the robot, then give commands through a joystick-like mechanism. This control paradigm fails to provide the human operator with an intuitive state feedback, resulting in awkward and slow behavior and underutilization of the robot's physical capabilities. To overcome this bottleneck, we introduce a new human-machine interface that extends the operator's proprioception by exploiting sensory substitution. Humans have a proprioceptive sense that provides us information on how our bodies are configured in space without having to directly observe our appendages. We constructed a wearable device with vibrating actuators on the forearm, where frequency of vibration corresponds to the spatial configuration of a robotic arm. The goal of this interface is to provide a means to communicate proprioceptive information to the teleoperator. Ultimately we will measure the change in performance (time taken to complete the task) achieved by the use of this interface.
Tamper-evident seals are commonly used for non-proliferation applications. A properly engineered tamper-evident seal enables the detection of unauthorized access to a protected item or a secured zone. Tamper-evident seals must be susceptible to malicious attacks. These attacks should cause irreversible and detectable damage to the seals. At the same time, tamper-evident seals must demonstrate robustness to environmental changes in order to minimize false-positive and false-negative rates under real operating conditions. The architecture of the tamper-evident seal presented in this paper features a compressive sampling (CS) acquisition scheme, which provides the seal with a means for self- authentication and self-state of health awareness. The CS acquisition scheme is implemented using a micro-controller unit (MCU) and an array of resistors engraved on a graphite oxide (GO) film. CS enables compression and encryption of messages sent from the seal to the remote reader in a non-bit sensitive fashion. As already demonstrated in our previous work through the development of a simulation framework, the CS non-bit sensitive property ensures satisfactory reconstruction of the encrypted messages sent back to the reader when the resistance values of the resistor array are simultaneously affected by modest changes. This work investigates the resistive behavior of the reduced GO film to changes in temperature and humidity when tested in an environmental chamber. The goal is to characterize the humidity and temperature range for reliable operation of a GO-based seal.
The blossoming of sensing solutions based on the use of carbon materials and the pervasive exploration of compressed sensing (CS) for developing structural health monitoring applications suggest the possibility of combining these two research areas in a novel family of smart structures. Specifically, the authors propose an architecture for security-related applications that leverages the tunable electrical properties of a graphite oxide (GO) paper-based tamper-evident seal with a compressed-sensing (CS) encryption/authentication protocol. The electrical properties of GO are sensitive to the traditional methods that are commonly used to remove and replace paper-based tamper-evident seals (mechanical lifting, solvents, heat/cold temperature changes, steam). The sensitivity of the electro-chemical properties of GO to such malicious insults is exploited in this architecture. This is accomplished by using GO paper to physically realize the measurement matrix required to implement a compressive sampling procedure. The proposed architecture allows the seal to characterize its integrity, while simultaneously providing an encrypted/authentication feature making the seal difficult to counterfeit, spoof, or remove/replace. Traditional digital encryption/authentication techniques are often bit sensitive making them difficult to implement as part of a measurement process. CS is not bit sensitive and can tolerate deviation caused by noise and allows the seal to be robust with respect to environmental changes that can affect the electrical properties of the GO paper during normal operation. Further, the reduced amount of samples that need to be stored and transmitted makes the proposed solution highly attractive for power constrained applications where the seal is interrogated by a remote reader.
There is currently an interest in developing mobile sensing platforms that fly indoors. The primary goal for these
platforms is to be able to successfully navigate a building under various lighting and environmental conditions. There
are numerous research challenges associated with this goal, one of which is the platform’s ability to detect and identify
the presence of transparent barriers. Transparent barriers could include windows, glass partitions, or skylights. For
example, in order to successfully navigate inside of a structure, these platforms will need to sense if a space contains a
transparent barrier and whether or not this space can be traversed. This project’s focus has been developing a multimodal
sensing system that can successfully identify such transparent barriers under various lighting conditions while
aboard a mobile platform. Along with detecting transparent barriers, this sensing platform is capable of distinguishing
between reflective, opaque, and transparent barriers. It will be critical for this system to be able to identify transparent
barriers in real-time in order for the navigation system to maneuver accordingly. The properties associated with the
interaction between various frequencies of light and transparent materials were one of the techniques leveraged to solve
this problem.
Haptics is the field at the interface of human touch (tactile sensation) and classification, whereby tactile feedback is used to train and inform a decision-making process. In structural health monitoring (SHM) applications, haptic devices have been introduced and applied in a simplified laboratory scale scenario, in which nonlinearity, representing the presence of damage, was encoded into a vibratory manual interface. In this paper, the “spirit” of haptics is adopted, but here ultrasonic guided wave scattering information is transformed into audio (rather than tactile) range signals. After sufficient training, the structural damage condition, including occurrence and location, can be identified through the encoded audio waveforms. Different algorithms are employed in this paper to generate the transformed audio signals and the performance of each encoding algorithms is compared, and also compared with standard machine learning classifiers. In the long run, the haptic decision-making is aiming to detect and classify structural damages in a more rigorous environment, and approaching a baseline-free fashion with embedded temperature compensation.
In crack detection applications large sensor arrays are needed to be able to detect and locate cracks in structures. This paper analyzes different sensor shapes and layouts to determine the layout which provides the optimal performance. A “snaked hexagon” layout is proposed as the optimal sensor layout when both crack detection and crack location parameters are considered. In previous work we have developed a crack detection circuit which reduces the number of channels of the system by placing several sensors onto a common bus line. This helps reduce data and power consumption requirements but reduces the robustness of the system by creating the possibility of losing sensing in several sensors by a single broken wire. In this paper, sensor bus configurations are analyzed to increase the robustness of the bused sensor system. Results show that spacing sensors in the same bus out as much as possible increases the robustness of the system and that at least 3 buses are needed to prevent large segments of a structure from losing sensing in the event of a bus failure.
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.
Mobile sensor nodes are an ideal solution for efficiently collecting measurements for a variety of applications.
Mobile sensor nodes offer a particular advantage when measurements must be made in hazardous and/or adversarial
environments. When mobile sensor nodes must operate in hostile environments, it would be advantageous for them to
be able to avoid undesired interactions with hostile elements. It is also of interest for the mobile sensor node to maintain
low-observability in order to avoid detection by hostile elements. Conventional path-planning strategies typically
attempt to plan a path by optimizing some performance metric. The problem with this approach in an adversarial
environment is that it may be relatively simple for a hostile element to anticipate the mobile sensor node's actions (i.e.
optimal paths are also often predictable paths). Such information could then be leveraged to exploit the mobile sensor
node. Furthermore, dynamic adversarial environments are typically characterized by high-uncertainty and highcomplexity
that can make synthesizing paths featuring adequate performance very difficult. The goal of this work is to
develop a path-planner anchored in info-gap decision theory, capable of generating non-deterministic paths that satisfy
predetermined performance requirements in the face of uncertainty surrounding the actions of the hostile element(s)
and/or the environment. This type of path-planner will inherently make use of the time-tested security technique of
varying paths and changing routines while taking into account the current state estimate of the environment and the
uncertainties associated with it.
The acoustic emission (AE) phenomena generated by a rapid release in the internal stress of a material represent a
promising technique for structural health monitoring (SHM) applications. AE events typically result in a discrete number
of short-time, transient signals. The challenge associated with capturing these events using classical techniques is that
very high sampling rates must be used over extended periods of time. The result is that a very large amount of data is
collected to capture a phenomenon that rarely occurs. Furthermore, the high energy consumption associated with the
required high sampling rates makes the implementation of high-endurance, low-power, embedded AE sensor nodes
difficult to achieve. The relatively rare occurrence of AE events over long time scales implies that these measurements
are inherently sparse in the spike domain. The sparse nature of AE measurements makes them an attractive candidate for
the application of compressed sampling techniques. Collecting compressed measurements of sparse AE signals will relax
the requirements on the sampling rate and memory demands. The focus of this work is to investigate the suitability of
compressed sensing techniques for AE-based SHM. The work explores estimating AE signal statistics in the compressed
domain for low-power classification applications. In the event compressed classification finds an event of interest, ι1
norm minimization will be used to reconstruct the measurement for further analysis. The impact of structured noise on
compressive measurements is specifically addressed. The suitability of a particular algorithm, called Justice Pursuit, to
increase robustness to a small amount of arbitrary measurement corruption is investigated.
Mobile sensor nodes hold great potential for collecting field data using fewer resources than human operators
would require and potentially requiring fewer sensors than a fixed-position sensor array. It would be very beneficial to
allow these mobile sensor nodes to operate unattended with a minimum of human intervention. In order to allow mobile
sensor nodes to operate unattended in a field environment, it is imperative that they be capable of identifying and
responding to external agents that may attempt to tamper with, damage or steal the mobile sensor nodes, while still
performing their data collection mission. Potentially hostile external agents could include animals, other mobile sensor
nodes, or humans. This work will focus on developing control policies to help enable a mobile sensor node to identify
and avoid capture by a hostile un-mounted human. The work is developed in a simulation environment, and
demonstrated using a non-holonomic, ground-based mobile sensor node. This work will be a preliminary step toward
ensuring the cyber-physical security of ground-based mobile sensor nodes that operate unattended in potentially
unfriendly environments.
In order to realize the wide-scale deployment of high-endurance, unattended mobile sensing technologies, it is
vital to ensure the self-preservation of the sensing assets. Deployed mobile sensor nodes face a variety of physical
security threats including theft, vandalism and physical damage. Unattended mobile sensor nodes must be able to
respond to these threats with control policies that facilitate escape and evasion to a low-risk state. In this work the
Precision Immobilization Technique (PIT) problem has been considered. The PIT maneuver is a technique that a
pursuing, car-like vehicle can use to force a fleeing vehicle to abruptly turn ninety degrees to the direction of travel. The
abrupt change in direction generally causes the fleeing driver to lose control and stop. The PIT maneuver was originally
developed by law enforcement to end vehicular pursuits in a manner that minimizes damage to the persons and property
involved. It is easy to imagine that unattended autonomous convoys could be targets of this type of action by adversarial
agents. This effort focused on developing control policies unattended mobile sensor nodes could employ to escape,
evade and recover from PIT-maneuver-like attacks. The development of these control policies involved both simulation
as well as small-scale experimental testing. The goal of this work is to be a step toward ensuring the physical security of
unattended sensor node assets.
The rapid deployment of satellites is hindered by the need to flight-qualify their components and the resulting
mechanical assembly. Conventional methods for qualification testing of satellite components are costly and time
consuming. Furthermore, full-scale vehicles must be subjected to launch loads during testing. The focus of this research
effort was to assess the performance of Structural Health Monitoring (SHM) techniques to replace the high-cost
qualification procedure and to localize faults introduced by improper assembly. SHM techniques were applied on a
small-scale structure representative of a responsive satellite. The test structure consisted of an extruded aluminum spaceframe
covered with aluminum shear plates, which was assembled using bolted joints. Multiple piezoelectric patches
were bonded to the test structure and acted as combined actuators and sensors. Piezoelectric Active-sensing based wave
propagation and frequency response function techniques were used in conjunction with finite element modeling to
capture the dynamic properties of the test structure. Areas improperly assembled were identified and localized. This
effort primarily focused on determining whether or not bolted joints on the structure were properly tightened.
Structural health monitoring consists of an integrated paradigm of sensing, data interrogation, and statistical modeling
that results in a strategy to assess the performance of a structure. Sensor networks play a central role in this paradigm, as
such networks typically perform much of the actuation, data acquisition, information management, and even local
computing necessary to enable the overall implementation of the strategy, increasingly in a wireless mode. In many
applications power provision can become a limiting factor, as the conventional strategy for wireless networks is a
battery. However, batteries require replacement, as their useful shelf lives often do not exceed the intended service of
their host structures.
Energy harvesting has emerged as a class of potential network powering solutions whereby one form of energy available
on the structure is harvested and converted to useful electrical energy. The objective of this work is to investigate the
harvesting of energy from galvanic corrosion that typically occurs naturally in many structures. Specifically, this study
considers corrosion between magnesium and graphite rods embedded in a concrete structure immersed in seawater. The
energy was evaluated by connecting a .1F capacitor and measuring the voltage charge over finite time intervals during
the corrosion process. A carbon fiber admixture was introduced to the concrete host to improve electrical conductivity,
and the power increase was calculated from voltage measurements. The investigation concludes that the voltage levels
achieved may be naturally integrated with a booster circuit to provide CMOS voltage levels suitable for sensor network
powering in some applications.
In this paper, we present experimental investigations using energy harvesting and wireless energy transmission to
operate embedded structural health monitoring sensor nodes. The goal of this study is to develop sensing systems
that can be permanently embedded within a host structure without the need for an on-board power source. With this
approach the required energy will be harvested from the ambient environment, or periodically delivered by a RF
energy source to supplement conventional harvesting approaches. This approach combines several transducer types
to harvest energy from multiple sources, providing a more robust solution that does not rely on a single energy
source. Both piezoelectric and thermoelectric transducers are considered as energy harvesters to extract the ambient
energy commonly available on civil structures such as bridges. Methods of increasing the efficiency, energy storage
medium, target applications and the integrated use of energy harvesting sources with wireless energy transmission
will be discussed.
Proc. SPIE. 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009
KEYWORDS: Sensors, Data storage, Data transmission, Sensor networks, Data acquisition, Structural health monitoring, Microcontrollers, Bridges, Connectors, Multiplexers
This paper presents recent developments in an extremely compact, wireless impedance sensor node for combined use
with both impedance method and low-frequency vibrational data acquisition. The sensor node, referred to as the WID3
(Wireless Impedance Device) integrates several components, including an impedance chip, a microcontroller for local
computing, telemetry for wireless data transmission, multiplexers for managing up to seven piezoelectric transducers per
node, energy storage mediums, and several triggering options into one package to truly realize a self-contained wireless
active-sensor node for SHM applications. Furthermore, we recently extended the capability of this device by
implementing low-frequency A/D and D/A converters so that the same device can measure low-frequency vibration
data. The WID3 requires less than 60 mW of power to operate and is designed for the mobile-agent based wireless
sensing network. The performance of this miniaturized device is compared to our previous results and its capabilities are
demonstrated.
Proc. SPIE. 6932, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008
KEYWORDS: Sensors, Linear filtering, Signal processing, Microcontrollers, Bridges, Microsoft Foundation Class Library, Picosecond phenomena, Algorithm development, Smart sensors, Performance modeling
In this study, a smart sensor node is developed for hybrid health monitoring of PSC girder bridges. Hybrid health
monitoring of those structures is to alarm damage occurrence, to classify damage-types, and to identify damage locations
and severities by measuring accelerations and impedance signals. In order to achieve the objective, the following
approaches are implemented. Firstly, a smart sensor node with wireless sensing capacity and embedded monitoring
algorithms is developed for measuring acceleration. Secondly, we design a hybrid damage monitoring scheme that
combines acceleration-based and impedance-based methods for PSC girder bridges. Finally, the performance of the
smart sensor node is evaluated using a laboratory-scale PSC girder bridge model for which acceleration and impedance
signals were measured for prestress-loss and stiffness-loss cases.
A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is
developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host
wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The
roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to
sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing
center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for
measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the
bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly
from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless
sensor networks.
This paper presents the development and applications of a miniaturized impedance sensor node for structural health monitoring. The principle behind the impedance-based structural health monitoring technique is to apply high frequency structural excitations (typically higher than 30 kHz) through the surface-bonded piezoelectric transducers, and measure the impedance of structures by monitoring the current and voltage applied to the piezoelectric transducers. Changes in impedance indicate changes in the structure, which in turn can indicate that damage has occurred. Although many proof-of-concept experiments have been performed using the impedance methods, the impedance-measuring device is bulky and impractical for field-use. Therefore, a recently developed, miniaturized, low-cost impedance measurement chip was used to measure and record the electric impedance of a piezoelectric transducer. The performance of this miniaturized and portable device has been compared to our previous results and its effectiveness has been demonstrated in detecting bolt preload changes in a bolted frame structure. Furthermore, the possibility of wireless communication and local signal processing at the sensor node has been investigated by integrating the device with a microprocessor and telemetry.
It is estimated that 70% of all mechanical failures are related to fastener failure. One important mode of fastener failure is self-loosening of bolted joints. Self-loosening is especially problematic when the bolted joint is in an inaccessible location, a hostile environment, or a part of a machine whose shutdown would be costly. In this study, a piezoelectric (PZT) active-sensing device was used to detect the self-loosening mode in bolted joint connections. PZT enhanced washers were used to continuously monitor the condition of the joint by monitoring its dynamic characteristics. The mechanical impedance matching between the PZT enhanced devices and the joint connections was used as a key feature to monitor the preload changes and prevent further failure. The dynamic response was readily measured using electromechanical coupling property of the PZT patch, in which its electrical impedance is coupled with the mechanical impedance of the structure. This paper summarizes experimental results, the considerations needed in experimental procedures and design and several issues that can be used as a guideline for future investigation.
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