scholarly journals Structural Health Monitoring System Using Piezoelectric Networks with Tuned Lamb Waves

2010 ◽  
Vol 17 (4-5) ◽  
pp. 677-695 ◽  
Author(s):  
Bruno Rocha ◽  
Carlos Silva ◽  
Afzal Suleman

The paper presents a structural health monitoring system based on propagation of tuned Lamb waves and their interference with discontinuities. The dispersion curves are studied to determine the appropriate type and dimension of transducers and to select the optimum scanning frequencies and relevant propagation modes. A piezoelectric sensor network was implemented in an aluminum plate in order to generate and to sense the wave propagation and associated reflections. The algorithm developed for damage detection relies on the comparison of undamaged and damaged responses of the structure. Combinations of filters and statistical methods were applied to detect differences in the sensor signals acquired for the two different states (damaged and undamaged), corresponding to damage reflections. In order to eliminate the false positives due to noise, a probability analysis is performed to obtain the final damage position. The software designed for the current application allows the automatic calculation of dispersion curves, it executes the scans, performs data processing, executes the detection algorithm and presents the probable damages and their positions in a graphical form. Experiments were performed with the introduction of cumulative damages in the plate such as surface and through-the-thickness holes and cuts, ranging from 7 mm to 1 mm in diameter. Additionally, a stringer was attached to the plate by a single rivet line to simulate an aircraft skin structure. Cuts originating from rivet holes and connecting adjacent rivets, as well as loosened rivets were detected by the system. The introduction of the stringer resulted in a loss of precision in the determination of the radial position of the damages near it. Also, the network revealed significant difficulties in the detection of damages beyond the stringer.

Author(s):  
Prabhav Borate ◽  
Azam Thatte

Abstract This paper focuses on the development of a structural health monitoring system based on guided Lamb waves propagating over the structure and a network of surface acoustic sensors in communication at high frequencies. A time-of-flight (ToF), algorithm and a probabilistic diagnostic imaging and calibration method is developed to detect miniscule material losses or material adhesion as well as the defects like small scale holes and cracks in turbomachinery components like blades, rotors, plates and pipes. Using an advanced ToF algorithm, precise differences in timescales for arrival of symmetric / antisymmetric lamb wave packets are found for all possible combinations of actuator-sensor pairs. This leads to a deterministic mathematical construct for damage localization for various actuator-sensor pairs at focal points. In the probabilistic diagnostic imaging (PDI) method, field value is assigned based on fusion of wave signals rendered by various actuator-sensor paths to indicate the probability of the presence of a damage at a particular location on the structure. Correlation coefficients between healthy and damaged data for each of the actuator-sensor path is used to calculate the field value for each pixel on the structure. Damage calibration curve is developed by progressively increasing the damage and obtaining a magnitude of the probability density function of the severity of the damage. Proposed approach has been validated using experimental data for multiple damage cases on plates, internal surfaces of pipes and impeller blade to successfully detect submillimeter scale holes and cracks, material adhesion as well as rate of pipeline erosion and corrosion.


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