Implementation of a Piezo-diagnostics Approach for Damage Detection Based on PCA in a Linux-Based Embedded Platform
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Fecha
2018-11
Autores
Camacho, Jhonatan
Quintero, Andrés
Ruiz, Magda
Villamizar, Rodolfo
Mujica, Luis
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MDPI
Resumen
The implementation of damage-detection methods for continuously assessing structural
integrity entails systems with attractive features such as storage capabilities, memory capacity,
computational complexity and time-consuming processing. In this sense, embedded hardware
platforms are a promising technology for developing integrated solutions in Structural Health
Monitoring. In this paper, design, test, and specifications for a standalone inspection prototype are
presented, which take advantage of piezo-diagnostics principle, statistical processing via Principal
Component Analysis (PCA) and embedded systems. The equipment corresponds to a piezoelectric
active system with the capability to detect defects in structures, by using a PCA-based algorithm
embedded in the Odroid-U3 ARM Linux platform. The operation of the equipment consists of
applying, at one side of the structure, wide guided waves by means of piezoelectric devices operated
in actuation mode and to record the wave response in another side of the structure by using the
same kind of piezoelectric devices operated in sensor mode. Based on the nominal response of
the guide wave (no damages), represented by means of a PCA statistical model, the system can
detect damages between the actuated/sensed points through squared prediction error (Q-statistical
index). The system performance was evaluated in a pipe test bench where two kinds of damages
were studied: first, a mass is added to the pipe surface, and then leaks are provoked to the pipe
structure by means of a drill tool. The experiments were conducted on two lab structures: (i) a meter
carbon-steel pipe section and (ii) a pipe loop structure. The wave response was recorded between the
instrumented points for two conditions: (i) The pipe in nominal conditions, where several repetitions
will be applied to build the nominal statistical model and (ii) when damage is caused to the pipe
(mass adding or leak). Damage conditions were graphically recognized through the Q-statistic chart.
Thus, the feasibility to implement an automated real-time diagnostic system is demonstrated with
minimum processing resources and hardware flexibility.
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Palabras clave
Principal component analysis, Embedded system, Online monitoring, Structural health monitoring, Guided waves, Pipeline damage detection