KEYWORDS: Finite element methods, Data modeling, Performance modeling, Computing systems, Detection and tracking algorithms, Structural health monitoring, Modal analysis
Naval structures are subjected to damage that occurs on short-term (i.e. impact) and long-term (i.e. fatigue) time scales. Digital twins of ship structures can provide real-time condition assessments and be leveraged by a decision-making framework to enable informed response management that will increase ship survivability during engagements. A key challenge in the development of digital twins is the development of methodologies that can distinguish the various fault cases. Moreover, these methodologies must be able to operate on the resource-constrained computing environments of naval structures while meeting real-time latency constraints. This work reports on recent progress in the development of a multi-event model updating framework specially designed to meet stringent latency constraints while operating on a system with constrained computing resources. The proposed methodology tracks structural damage for both impact and fatigue damage through a swarm of particles that represent numerical models with varying input parameters with set latency and computational restraints. In this work, numerical validation is performed on a structural testbed subjected to representative wave loadings. Results demonstrate that continuous fatigue crack growth and plastic deformation caused by impact can be reliably distinguished. The effects of latency and resource constraints on the accuracy of the proposed system are quantified and discussed in this work.
Energy harvesting of environmental vibrations has been an intensive research field for several years, but there are lingering challenges regarding low frequency applications. Building off our recent invention of a multi-stable, broadband electromagnetic harvester relying on a dual resonant, rectilinear-to-rotary motion converter, research detailed in this paper outlines the creation of theoretical models for the dual resonator and systematically examines these models through experiments to further understand the interrelation of key design parameters and to optimize the harvester’s performance. More specifically, the dual resonant system converts broadband rectilinear vibrations to rotational motions via magnetic coupling, while frequency up-conversion via magnetic plucking converts low frequency vibrations into high frequency rotations. By combining the advantages of multi-stable nonlinearity, the invented dual resonant energy harvester possesses high power density at low operating frequencies. In this paper, a nonlinear electromechanical model of the dual resonant harvester is established, and the parametric study is conducted for various repulsive magnets configurations. Subsequent experiments validate the theoretical analysis. Systematic analysis of both theoretical and experimental results shows that the initial rotation angle and the configurations among the coupling magnets are critical to determining the operating patterns of the rotor and fully exploiting the potential of magnetic plucking to increase voltage output. The optimized dual resonator is advantageous over the linear harvesters by providing wider low frequency bandwidth via the inherent nonlinear dynamics.
During the interpretation of the Lamb wave data, the main concern is often the arrival times of wave groups. Group
arrival times determine the distance of the source or the reflector. The inspection of sensory signal envelopes is
satisfactory to identify and localize defects. The S-transformation is proposed for isolating wave forms at their
excitation frequency and obtaining their envelopes. To further minimize the storage and computational costs, reduction
of the data size by down sampling (skipping 5 data points for each saved one) and compression via calculating the
wavelet transformation three times are proposed. The data was reduced to 1/30th of its original size, while the
reconstructed wavelet transformation had a less than 1% average error with respect to the down sized envelope signal.
In this study, the feasibility of monitoring the structural integrity of welded thick aluminum plates was experimentally
tested using two widely used SHM methods: impedance and Lamb wave analyses. The test structure was fabricated
from two 1/4 inch thick aluminum plates welded together, and various structural defects, such as holes and cuts, were
applied. At each of these damage steps, data were collected for both the impedance and Lamb wave techniques. Results
consistently revealed the impedance method to be sensitive to damage in and through the weld. The envelopes of the
Lamb wave signals were calculated using the S-transformation of the time histories. There was significant change to the
curves when different defects were added to the plate. Both of the SHM methods studied detected each of the cuts and
holes acting to reduce the overall strength of the structure. Each technique also detected the hole damage on the opposite
side of the weld as the sensor(s) used for damage detection. The study further verified that surface waves move across
welds allowing SHM methods to detect the defects even if the sensors are located on neighboring plates or geometries.
Wind power is a fast-growing source of non-polluting, renewable energy with vast potential. However, current wind
turbine technology must be improved before the potential of wind power can be fully realized. Wind turbine blades are
one of the key components in improving this technology. Blade failure is very costly because it can damage other
blades, the wind turbine itself, and possibly other wind turbines. A successful damage detection system incorporated
into wind turbines could extend blade life and allow for less conservative designs. A damage detection method which
has shown promise on a wide variety of structures is impedance-based structural health monitoring. The technique
utilizes small piezoceramic (PZT) patches attached to a structure as self-sensing actuators to both excite the structure
with high-frequency excitations, and monitor any changes in structural mechanical impedance. By monitoring the
electrical impedance of the PZT, assessments can be made about the integrity of the mechanical structure. Recently,
advances in hardware systems with onboard computing, including actuation and sensing, computational algorithms, and
wireless telemetry, have improved the accessibility of the impedance method for in-field measurements. This paper
investigates the feasibility of implementing such an onboard system inside of turbine blades as an in-field method of
damage detection. Viability of onboard detection is accomplished by running a series of tests to verify the capability of
the method on an actual wind turbine blade section from an experimental carbon/glass/balsa composite blade developed
at Sandia National Laboratories.
KEYWORDS: Digital signal processing, Clocks, Structural health monitoring, Prototyping, Signal processing, Damage detection, Light emitting diodes, Signal generators, Ferroelectric materials, Sensors
Currently, much of the focus in the structural health monitoring community is shifting towards incorporating health
monitoring technology into real world structures. Deployment of structural health monitoring systems for permanent
damage detection is usually limited by the availability of sensor technology. Previously, we developed the first fully
self-contained system that performs impedance-based structural health monitoring. This digital signal processor based
system effectively replaces a traditional impedance analyzer and all of the manual analysis usually required for damage
determination. The work described here will focus on improving this hardware. Efforts are made to reduce the overall
power consumption of the prototype while at the same time improving the overall performance and efficiency. By
introducing a new excitation method and implementing a new damage detection scheme, reliance on both analog-to-digital
and digital-to-analog conversion are circumvented. These new actuation and sensing techniques, along with the
underlying hardware, are described in detail. The reduction of power dissipation and improved performance are
documented and compared with both traditional impedance techniques and the previous prototype.
KEYWORDS: Composites, Microsoft Foundation Class Library, Vibrometry, Sensors, Satellites, Laser applications, Ferroelectric materials, Signal attenuation, Vibration control, Positive feedback
Composite booms are an emerging low weight structural alternative for on-orbit satellites. With any satellite, vibrational control of the structure is a concern. Using traditional measurement techniques, possible inaccuracies may result due to the lightweight natures of the composite boom. Laser vibrometry techniques are investigated in this paper as an alternative to standard accelerometer measurements. The advantages of non contact measurement are presented in two different experimental setups. Using the dynamic measurements obtained from these experiments, a positive feedback controller is developed to attenuate the vibration of the strut.
For some time, the smart materials and structures community has focused on transducer effects, and the closest advance into actually having the "structure" show signs of intelligence is implementing adaptive control into a smart structure. Here we examine taking this a step further by attempting to combine embedded computing into a smart structure system. The system of focus is based on integrated structural health monitoring of a panel which consists of a completely wireless, active sensing systems with embedded electronics. We propose and discuss an integrated autonomous sensor "patch" that contains the following key elements: power harvesting from ambient vibration and temperature gradients, a battery charging circuit, local computing and memory, active sensors, and wireless transmission. These elements should be autonomous, self contained, and unobtrusive compared to the system being monitored. Each of these elements is discussed as a part of an integrated system to be used in structural health monitoring applications.
Components used for thermal protection have not previously been interrogated with the impedance method. In this study, structures are fabricated to represent typical thermal protections systems. The replicas are designed to simulate actual protection systems in use. Observations are made into the verification of the impedance method in effectively monitoring complex thermal protection systems from non-optimal sensor placement locations. The thermal protections systems are damaged in a way to represent typical damage mechanisms. The sensitivity of the impedance method to various types of damage in representative structures will also be discussed. Different operational conditions, including high temperatures, are also included in the experimentation.
Rail lines are subject to many types of damage that, in the worst cases, can cause train derailments. The damage can arise from either manufacturing defects or external factors, possibly even terrorist acts to disrupt the civil infrastructure. Current rail inspection techniques require train traffic to be interrupted while workers and equipment move along the track. Moreover, a technician with rail testing experience is required to analyze the results. This paper focuses on simple proof of concept experiments to determine if impedance based structural health monitoring may be used to detect anomalies in rail tracks, and in particular broken rails. The technique applies a very low voltage (one volt) high frequency wave to a structure, measures its response and determines the location and extent of a rail break. The monitoring device is envisioned to run off of ambient vibration and thermal gradients provided by passing trains and daily thermal cycles, store the energy and utilize the stored energy periodically to inspect the track (according to the track usage schedule). If damage occurs or starts to occur, a warning signal would be transmitted to substation then broadcast to the appropriate operator listing the location and extent of the damage.
The influences of temperature variations on the use of wave propagation for damage detection are investigated for use with impedance-based structural health monitoring. The equations used to determine the damage based upon a longitudinal wave are presented as derived by Kabeya, et al. Equations are defined in order to determine the damage location in a simulation. Temperature variations are induced, and the resulting errors are presented. A possible application using a realistic temperature differential is proposed. A curve-fit of the modulus of elasticity is implemented to correct damage location error.
KEYWORDS: Sensors, Microsoft Foundation Class Library, Ferroelectric materials, Structural health monitoring, Space operations, Solids, Rockets, Actuators, Composites, Intelligence systems
Many of the structures responsible for the launch, ground turnaround and support operations of the space shuttle are still being used well past their design life. This has led to an increased interest in monitoring these structures in order to decrease the risk of breakdowns or structural failure. One monitoring method which has shown promising results for such applications is the impedance-based structural health monitoring technique. This paper presents results from proof-of-concept tests on the launch pad's orbiter access arm bolted connection, solid rocket booster support post, mobile launch platform heat shield and crawler transporter bearing. These tests showed that the impedance method can provide a permanent structural health monitoring solution to NASA's ground structures. In addition several positive and negative aspects of the impedance method were discovered or highlighted. Modifications for future tests are suggested.
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