AIMC Topic: Aircraft

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Deep Neural Network Recognition of Rivet Joint Defects in Aircraft Products.

Sensors (Basel, Switzerland) Apr 29, 2022
The mathematical statement of the problem of recognizing rivet joint defects in aircraft products is given. A computational method for the recognition of rivet joint defects in aircraft equipment based on video images of aircraft joints has been prop...
Neural Networks, Computer Machine Learning Aircraft
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Mobile Robots for In-Process Monitoring of Aircraft Systems Assemblies.

Sensors (Basel, Switzerland) Apr 27, 2022
Currently, systems installed on large-scale aerospace structures are manually equipped by trained operators. To improve current methods, an automated system that ensures quality control and process adherence could be used. This work presents a mobile...
Humans Algorithms Feedback Robotics Aircraft
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Aircraft Image Recognition Network Based on Hybrid Attention Mechanism.

Computational intelligence and neuroscience Apr 18, 2022
With the deepening of deep learning research, progress has been made in artificial intelligence. In the process of aircraft classification, the precision rate of aircraft picture recognition based on traditional methods is low due to various types of...
Neural Networks, Computer Artificial Intelligence Algorithms Aircraft
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Facilitating the Work of Unmanned Aerial Vehicle Operators Using Artificial Intelligence: An Intelligent Filter for Command-and-Control Maps to Reduce Cognitive Workload.

Human factors Apr 7, 2022
OBJECTIVE: Evaluating the ability of a Gibsonian-inspired artificial intelligence (AI) algorithm to reduce the cognitive workloads of military Unmanned Aerial Vehicle (UAV) operators.
Humans Artificial Intelligence Aircraft Workload Awareness Unmanned Aerial Devices
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Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods.

Sensors (Basel, Switzerland) Mar 29, 2022
Linear dependence of variables is a commonly used assumption in most diagnostic systems for which many robust methodologies have been developed over the years. In case the system nonlinearities are relevant, fault diagnosis methods, relying on the as...
Machine Learning Algorithms Support Vector Machine Aircraft
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Modified Artificial Potential Field for the Path Planning of Aircraft Swarms in Three-Dimensional Environments.

Sensors (Basel, Switzerland) Feb 17, 2022
Path planning techniques are of major importance for the motion of autonomous systems. In addition, the chosen path, safety, and computational burden are essential for ensuring the successful application of such strategies in the presence of obstacle...
Algorithms Robotics Aircraft Motion
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Aircraft Landing Gear Retraction/Extension System Fault Diagnosis with 1-D Dilated Convolutional Neural Network.

Sensors (Basel, Switzerland) Feb 10, 2022
The faults of the landing gear retraction/extension(R/E) system can result in the deterioration of an aircraft's maneuvering conditions; how to identify the faults of the landing gear R/E system has become a key issue for ensuring aircraft take-off a...
Neural Networks, Computer Algorithms Aircraft Data Collection
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Fuzzy Logic in Aircraft Onboard Systems Reliability Evaluation-A New Approach.

Sensors (Basel, Switzerland) Nov 27, 2021
This paper is a continuation of research into the possibility of using fuzzy logic to assess the reliability of a selected airborne system. The research objectives include an analysis of statistical data, a reliability analysis in the classical appro...
Reproducibility of Results Fuzzy Logic Aircraft
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Remaining Useful Life Estimation of Aircraft Engines Using a Joint Deep Learning Model Based on TCNN and Transformer.

Computational intelligence and neuroscience Nov 24, 2021
The remaining useful life estimation is a key technology in prognostics and health management (PHM) systems for a new generation of aircraft engines. With the increase in massive monitoring data, it brings new opportunities to improve the prediction ...
Neural Networks, Computer Computer Simulation Deep Learning Aircraft
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Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks.

Sensors (Basel, Switzerland) Aug 24, 2021
In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor animals because of their customizability, ease of operating, ability to access difficult to navigate places, and potential to minimize disturbance to animals. Au...
Neural Networks, Computer Algorithms Animals Deep Learning Cattle Aircraft Horses Deer
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