Current satellite transportation sensors can provide a binary indication of the
acceleration or shock that a satellite has experienced during the shipping process
but do little to identify if significant structural change has occurred in the satellite
and where it may be located. When a sensor indicates that the satellite has
experienced shock during transit, an extensive testing process begins to evaluate the
satellite functionality. If errors occur during the functional checkout, extensive
physical inspection of the structure follows. In this work an alternate method for
inspecting satellites for structural defects after shipping is presented. Electro-
Mechanical Impedance measurements are used as an indication of the structural
state. In partnership with the Air Force Research Laboratory University
Nanosatellite Program, Cornell's CUSat mass model was instrumented with
piezoelectric transducers and tested under several structural damage scenarios. A
method for detecting and locating changes in the structure using EMI data is
presented.
Bi-stable composite tape springs present several volume efficient solutions for deployable structures in small
satellites. Viscoelastic changes within the composite matrix of these materials caused by their long term storage and
exposure to varying temperatures can negatively impact the ability to deploy the structure. This study investigates a
method for developing an in situ sensor for structural health monitoring in space structures employing tape springs. A
method is developed by employing a custom load cell to detect stress relaxation in a bent tape spring over a period of
time and two tests of this method were conducted. Results from the first test reveal the correct trend for stress relaxation
but with significant noise. The second test showed the cause of the noise to be material behavior changes due to
temperature fluctuations. The results show the expected decreasing exponential trend in the strain data as stress
relaxation occurs, proving the feasibility of the approach.
KEYWORDS: Sensors, Wave propagation, Structural health monitoring, Satellites, Signal attenuation, Actuators, Finite element methods, Data modeling, Analytical research, Nondestructive evaluation
This work focuses on an analysis of wave propagation in isogrid structures as it
relates to Structural Health Monitoring (SHM) methods. Assembly, integration,
and testing (AI&T) of satellite structures in preparation for launch includes
significant time for testing and reworking any issues that may arise. SHM methods
are being investigated as a means to validate the structure during assembly and
truncate the number of tests needed to qualify the structure for the launch
environment. The most promising of these SHM methods uses an active wave-based
method in which an actuator propagates a Lamb wave through the structure; the
Lamb wave is then received by a sensor and evaluated over time to detect structural
changes. To date this method has proven effective in locating structural defects in a
complex satellite panel; however, the attributes associated with the first wave
arrival change significantly as the wave travels through ribs and joining features.
Previous studies have been conducted in simplified ribbed structures, giving initial
insight into the complex wave propagation phenomena. In this work, the study has
been extended numerically to the isogrid plate case. Wave propagation was
modeled using commercial finite element analysis software. The results of the
analyses offer further insight into the complexities of wave propagation in isogrid
structures.
This work focuses on the detection, localization, and quantification of damage in the form
of loose bolts on an isogrid satellite structure. In the process of rapid satellite development
and deployment, it is necessary to quickly complete several levels of validation tests.
Structural Health Monitoring methods are being investigated as a means for reducing the
number of validation tests required. This method for detecting loose bolts enables quick
confirmation of proper assembly, and verification that structural fasteners are still intact
after validation testing. Within this testing framework, feature selection is presented as well
as a localization methodology. Quantification of fastener torque is also developed. Locating
damage in an isogrid structure is complicated by the directionally dependent dispersion
characteristics caused by a propagating wave passing through ribs and holes. For this
reason, an actuation frequency with the best first wave arrival clarity is selected. A
methodology is presented in which a time map is constructed for each actuator-sensor pair which establishes times of flight for each location on the sample. Differences in time between healthy and damaged sensor signals are then extracted and used to create a map of possible damage locations. These resulting solution maps are merged yielding a final damage position. Fastener torque is correlated to a damage parameter, and the loose bolt position is calculated within 3 cm.
Integrity of bolted joints is critical for successful deployment and operation of space structures. Conventional
structural qualification tests span weeks if not months and inhibit rapid launch of space systems. Recent developments
in the embedded ultrasonic acousto-elastic method offer fast diagnosis of bolted joints and opportunities for locating
the fault. However, in current acousto-elastic measurement procedures, a baseline representing the healthy condition
of the joint is necessary. To mitigate a requirement of the baseline, a new methodology based on relative amplitude
and phase measurements is developed. The approach has been validated on laboratory specimens, and modifications
were suggested for applications in realistic structures. The paper discusses principles of the baseline-free acoustoelastic
method, its practical realization, and respective advantages and disadvantages. Comparison of baseline and
baseline-free approaches is presented showing the utility of the recently proposed methodology. Fundamentals of the
acousto-elastic response were studied in experiments involving guided wave propagation in a thin plate under tension.
The results indicate a difference between acousto-elastic responses collected using sensors oriented parallel and perpendicular to the applied stress. It is suggested that this effect may be used to infer stress orientation in the sample. Practical issues related to acousto-elastic measurements in realistic complex structures are discussed, damage diagnosis algorithms are presented, and potential extensions of the acousto-elastic technique are proposed.
The ability to detect anomalies in signals from sensors is imperative for structural health monitoring (SHM) applications.
Many of the candidate algorithms for these applications either require a lot of training examples or are very
computationally inefficient for large sample sizes. The damage detection framework presented in this paper uses a
combination of Linear Discriminant Analysis (LDA) along with Support Vector Machines (SVM) to obtain a
computationally efficient classification scheme for rapid damage state determination. LDA was used for feature
extraction of damage signals from piezoelectric sensors on a composite plate and these features were used to train the
SVM algorithm in parts, reducing the computational intensity associated with the quadratic optimization problem that
needs to be solved during training. SVM classifiers were organized into a binary tree structure to speed up classification,
which also reduces the total training time required. This framework was validated on composite plates that were
impacted at various locations. The results show that the algorithm was able to correctly predict the different impact
damage cases in composite laminates using less than 21 percent of the total available training data after data reduction.
Carbon-fiber composites will increasingly be used in next generation air transportation vehicles. Therefore, it is critical
to develop state awareness models that can accurately capture the damage states and predict remaining useful life based
on current and future loading conditions. In the current research, a structural health monitoring (SHM) and prognosis
framework is being developed for heterogeneous material systems. The objective of this paper is to present some of the
experimental components of this work. In the experiments preformed, the use of a pitch catch method using
piezoelectric transducers for both the actuator and sensor were employed for collecting information on the damage
status. The focus of this work is to quantify damage within the sample by relating parameters in the sensor signal to
damage intensity. Good correlation has been observed in several tests between damage level and wave attenuation.
These results are confirmed using off-the-shelf NDE techniques.
We describe a statistical method for the classification of damage in complex structures. Our approach is based
on a Bayesian framework using hidden Markov models (HMMs) to model time-frequency features extracted from
structural data. We also propose two different methods for sensor fusion to combine information from multiple
distributed sensors such that the overall classification performance is increased. The proposed approaches are
applied to the classification and localization of delamination in a laminated composite plate. Results using
both discrete and continuous observation density HMMs, together with the sensor fusion, are presented and
discussed.
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