No abstract

Piezoelectric shunt damping is a well-known technique to damp mechanical vibrations of a structure, using a piezoelectric transducer to convert mechanical vibration energy into electrical energy, which is dissipated in an electrical resistance. Resonant shunts consisting of a resistance and an inductance connected to a piezoelectric transducer are used to damp structural vibrations in narrow frequency bands, but their performance is very sensitive to variations in structural modal frequencies and transducer capacitance. In order to overcome this drawback, a piezoelectric shunt damping technique with improved performance and robustness is presented in this paper. The design of the adaptive circuit considers the variation of the host structure's natural frequency as a project parameter. This paper describes an adaptive resonant piezoelectric vibration absorber enhanced by a synthetic negative capacitance applied to a shell structure. The resonant shunt circuit autonomously adapts its inductance value by comparing the phase difference of the vibration velocity and the current flowing through the shunt circuit. Moreover, a synthetic negative capacitance is added to the shunt circuit to enhance the vibration attenuation provided by the piezoelectric absorber. The circuitry is implemented using analog components. Validation of the proposed method is done by bonding the piezoelectric absorber on a freeformed metallic shell.

No abstract

Aircraft visual inspections, or General Visual Inspections (GVIs), aim at finding damages or anomalies on the exterior and interior surfaces of the aircraft, which might compromise its operation, structure, or safety when flying. Visual inspection is part of the activities of aircraft Maintenance, Repair and Overhaul (MRO). Specialists perform quality inspections to identify problems and determine the type and importance that they will report. This process is time-consuming, subjective, and varies according to each individual. The time that an aircraft stays grounded without flight clearance means financial losses. The main goal of this work is to advance the state-of-the-art of defect detection on aircraft exterior with deep learning and computer vision. We investigate improvements to the accuracy of dent detection. Besides, we investigate new classes of identified defects, such as scratches. We also plan to demonstrate that it is possible to develop a complete system to automate the visual inspection of aircraft exterior using images of the aircraft acquired by drones. We will use deep neural networks for the detection and segmentation of defective regions. This system will aid in the elimination of subjectivity caused by human errors and shorten the time required to inspect an aircraft, bringing benefits to its safety, maintenance, and operation.