Integrated Aircraft Risk Analysis Framework for Health Monitoring Systems – A Case Study for Structural Health Monitoring

Steinweg, Dominik; Hornung, Mirko

doi:10.2514/6.2020-1453

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…The application of SHM techniques on these type of materials, even though it is very advanced, presents several drawbacks, mainly due to the inherent material anisotropic nature, especially when the geometry of the structure is complex, making the SHM real application in an aircraft a difficult challenge [18], in addition to other factors such as the weight of the instrumentation, the difficulties of wiring sensors and the cost-utility analysis of the technology [19].…”

Section: Introductionmentioning

confidence: 99%

Influence and Compensation of Temperature Effects for Damage Detection and Localization in Aerospace Composites

Azuara

Barrera

2020

Sensors

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Structural Health Monitoring (SHM) of Carbon Fiber Reinforced Polymers (CFRP) has become, recently, in a promising methodology for the field of Non-Destructive Inspection (NDI), specially based on Ultrasonic Guided Waves (UGW), particularly Lamb waves using Piezoelectric Transducers (PZT). However, the Environmental and Operational Conditions (EOC) perform an important role on the physical characteristics of the waves, mainly the temperature. Some of these effects are phase shifting, amplitude changes and time of flight (ToF) variations. In this paper, a compensation method for evaluating and compensating the effects of the temperature is carried out, performing a data-driven methodology to calculate the features from a dataset of typical temperature values obtained from a thermoset matrix pristine plate, with a transducer network attached. In addition, the methodology is tested on the same sample after an impact damage is carried out on it, using RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) and its geometrical variant (RAPID-G) to calculate the location of the damage.

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Section: Introductionmentioning

confidence: 99%