KEYWORDS: Structural health monitoring, Sensors, Acoustics, Digital signal processing, Ferroelectric materials, Prototyping, Signal processing, Signal generators, Discrete wavelet transforms, Aluminum
Structural damage for spacecraft is mainly due to impacts such as collision of meteorites or space debris. We present a
structural health monitoring (SHM) system for space applications, named Adverse Event Detection (AED), which
integrates an acoustic sensor, an impedance-based SHM system, and a Lamb wave SHM system. With these three
health-monitoring methods in place, we can determine the presence, location, and severity of damage. An acoustic
sensor continuously monitors acoustic events, while the impedance-based and Lamb wave SHM systems are in sleep
mode. If an acoustic sensor detects an impact, it activates the impedance-based SHM. The impedance-based system
determines if the impact incurred damage. When damage is detected, it activates the Lamb wave SHM system to
determine the severity and location of the damage. Further, since an acoustic sensor dissipates much less power than the
two SHM systems and the two systems are activated only when there is an acoustic event, our system reduces overall
power dissipation significantly. Our prototype system demonstrates the feasibility of the proposed concept.
KEYWORDS: Solar cells, Solar energy, Resistance, Energy harvesting, Prototyping, Structural health monitoring, Sensing systems, Domes, Detection and tracking algorithms, Field effect transistors
The SCANSn is a structural health monitoring (SHM) system is being developed by Acellent Technologies to monitor
steel bridges. The required voltage of the system is 14.4 V for active scanning, and the power consumption is
approximately 8 W. The investigated energy harvesting from both solar and thermal sources to recharge the lithium-ion
battery of the system. A solar panel and a Thermal Electric Generator (TEG) are used to harvest ambient energy. The
thermoelectric device is placed in a Fresnel dome to maximize the temperature gradient of the TEG. During shading of
the solar panel, the TEG continues to supply power to the battery charger. Since the output voltages and currents of the
solar and thermal energy harvesters vary significantly, the energy harvesting module is constructed by two buck-boost
converters operating in parallel. Maximal Power Point Tracking (MPPT) is employed for the buck-boost converter for
the solar panel, while a fixed duty cycle converter is used for the TEG due to substantially lower power compared with
the solar panel. The system design and measured results of a prototype system are presented. Our prototype system
successfully demonstrates that the SCANSn system can be powered by the energy harvested from solar and thermal.
We developed a self-powered wireless autonomous Structural Health Monitoring (SHM) sensor node using a Texas
Instruments MSP430 evaluation board. The sensor node employs a PZT (Lead Zirconate Titanate) based impedance
method, which saves power by eliminating a digital-to-analog-converter (DAC) for generation of an excitation signal
and an analog-to-digital converter (ADC) for sensing the response. The sensor node wakes up at a predetermined
interval, performs an SHM operation, and reports the result to the host computer wirelessly. The sensor node consumes only 0.3 J and is powered up by the energy harvested from vibrations, often available from infrastructures. The power management circuit integrated with a piezoelectric cantilever with the size of 50 mm x 31.8 mm generate up to 2.9 mW under 0.5g (rms) base acceleration, which is sufficient to run an SHM operation on every two minutes.
KEYWORDS: Digital signal processing, Signal processing, Prototyping, Structural health monitoring, Ferroelectric materials, Aluminum, Discrete wavelet transforms, Analog electronics, Computing systems, Wavelets
The analog-to-digital converter (ADC) of a Lamb wave system samples a response signal and converts it into a digital
signal for further processing in the digital domain. A typical ADC used for a Lamb wave system consumes a large
amount of power. It also increases the complexity of the signal processing for the processor, which, in turn, increases the power consumption of the processor. Elimination of the ADC can therefore significantly reduce the overall power dissipation of a Lamb wave system. In this paper, we propose a method to eliminate the ADC of a Lamb wave system, in which the ADC is replaced by two comparators. Our method quantizes the sampled signal into three levels rather than 2n levels as with an n-bit ADC. The experimental results performed with our prototype indicate that the proposed method is effective at detecting simulated damage on aluminum plates.
Shape memory alloy (SMA) washers expand axially when heated, and the expansion for the one-way type SMA is
permanent even if the heat is removed. We investigated a method to repair bolted joint loosening defects using SMA
washers. We incorporated such a feature into our impedance-based structural health monitoring (SHM) system. An SMA
washer wrapped with a heater is installed between a bolt and the nut. Upon detection of a loosening defect, the heater is
turned on to expand the SMA washer, which in turn repairs the defect. Our experimental results show that (i) our
enhanced SHM system can detect bolted-joint loosening defects, and (ii) it can repair such defects effectively. Our
system suggests that self-repairing of some structural defects is feasible without human interventions.
An impedance-based structural health monitoring (SHM) system employs a piezoelectric patch to excite the structure
under test and capture its response. Impedance-based SHM offers several advantages over other methods such as good
performance for local damage detection and simple hardware. A major problem for impedance-based SHM is
temperature dependency. Specifically, baseline impedance profiles of structures vary as the ambient temperature changes.
In this paper, we propose a new method to compensate the effect of temperature on baseline profiles. Our method is to
select a small subset of baseline profiles for some critical temperatures and estimates the baseline profile for a given
ambient temperature through interpolation. We incorporated our method into our SHM system and investigated the
effectiveness of our method. Our experimental results show that (i) our method reduces the number of baseline profiles
to be stored, and (ii) estimates the baseline profile of a give temperature accurately.
KEYWORDS: Ferroelectric materials, Structural health monitoring, Digital signal processing, Signal processing, Discrete wavelet transforms, Wave propagation, Sensing systems, Phase measurement, Signal generators, Sensors
We present an SHM system integrating both the impedance and the Lamb wave propagation method on a single board,
while sharing the same DSP (Digital Signal Processing) processor and the piezoelectric patches. Three functional blocks,
such as signal excitation/generation, signal sensing, and data processing, were implemented to incorporate the Lamb
wave method into our existing impedance-based SHM system. Both pitch-and-catch and pulse-and-echo schemes were
implemented for damage detection and location, respectively. Through synergetic integration of the two methods, our
SHM system can detect various types of simulated damages on aluminum plates.
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.
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