Smart Sensing Systems in Aerospace
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Aerospace Science and Engineering".
Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 276
Special Issue Editors
Interests: structural health monitoring; guided waves; smart sensors; elastic wave metamaterials
Interests: physics-informed machine learning for structural health monitoring (SHM); smart structures; cyber-physical systems/digital twin; robotic tactile sensing and mechanics of aerospace composite structures
Interests: smart structures; smart aircraft technologies; morphing structures; structural dynamics; vibration control; dynamic aeroelasticity; non-linear dynamics; mechanics and experimental dynamics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Health monitoring of aircraft structures is crucial in order to ensure their safety during service. The key to achieving this is developing online advanced sensing systems, including hardware and software. The former contains smart sensors, sensor arrays, and corresponding integrated measurement equipment to capture the responses of aircraft structures, i.e., vibration, strain, elastic/guided wave, electromechanical impedance, eddy current, and so on. The latter extracts the intrinsic features of the captured signals with advanced signal processing methods and synthesizes signal features for damage identification algorithms to evaluate the health status of structures. Moreover, the evaluation of the system’s uncertainty in terms of its stability and reliability in different environments is also highly required in this discipline. This Special Issue is, therefore, dedicated to recent advances in novel smart sensing systems for structural health monitoring in aerospace applications.
Dr. Shengbo Shan
Dr. Cheng Liu
Dr. Rosario Pecora
Guest Editors
Manuscript Submission Information
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Keywords
- novel smart sensors
- sensor array design
- integrated measurement equipment
- advanced signal processing methods
- damage diagnosis algorithms
- uncertainty evaluation
