Using deep learning to detect defects in manufacturing: a comprehensive survey and current challenges
J Yang, S Li, Z Wang, H Dong, J Wang, S Tang - Materials, 2020 - mdpi.com
The detection of product defects is essential in quality control in manufacturing. This study
surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects …
surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects …
UAV fault detection methods, state-of-the-art
R Puchalski, W Giernacki - Drones, 2022 - mdpi.com
The continual expansion of the range of applications for unmanned aerial vehicles (UAVs) is
resulting in the development of more and more sophisticated systems. The greater the …
resulting in the development of more and more sophisticated systems. The greater the …
A sound based method for fault detection with statistical feature extraction in UAV motors
The motors of the Unmanned Aerial Vehicle are critical parts, especially when used in
applications such as military and defense systems. The fact that the brushless DC (BLDC) …
applications such as military and defense systems. The fact that the brushless DC (BLDC) …
Fault diagnosis of actuator damage in UAVs using embedded recorded data and stacked machine learning models
Unmanned aerial vehicles (UAVs) have gained significant importance due to their wide
applicability in modern life. Fault diagnosis plays a crucial role in ensuring their safe and …
applicability in modern life. Fault diagnosis plays a crucial role in ensuring their safe and …
An investigation of the reliability of different types of sensors in the real-time vibration-based anomaly inspection in drone
Early drone anomaly inspection is vital to ensure the drone's safety and effectiveness. This
process is often overlooked, especially by amateur drone pilots; however, some faulty …
process is often overlooked, especially by amateur drone pilots; however, some faulty …
Improved UAV blade unbalance prediction based on machine learning and ReliefF supreme feature ranking method
As unmanned aerial vehicles (UAVs) are witnessing a rapid increase in usage in regard to
many different applications, it has become paramount to classify blade faults and …
many different applications, it has become paramount to classify blade faults and …
Configurations, flight mechanisms, and applications of unmanned aerial systems: A review
Abstract Unmanned Aerial Systems (UASs) have a variety of applications in our daily life that
have attracted the attention of many researchers around the world. There are a variety of …
have attracted the attention of many researchers around the world. There are a variety of …
Failure detection in quadcopter UAVs using K-means clustering
J Cabahug, H Eslamiat - Sensors, 2022 - mdpi.com
We propose an unmanned aerial vehicle (UAV) failure detection system as the first step of a
three-step autonomous emergency landing safety framework for UAVs. We showed the …
three-step autonomous emergency landing safety framework for UAVs. We showed the …
Multiclass classification fault diagnosis of multirotor UAVs utilizing a deep neural network
A fault diagnosis algorithm using a deep neural network for an octocopter Unmanned Aerial
Vehicle (UAV) is proposed. All eight rotors are considered in the multiclass classification …
Vehicle (UAV) is proposed. All eight rotors are considered in the multiclass classification …
Fault tolerant control for modified quadrotor via adaptive type-2 fuzzy backstep** subject to actuator faults
In this paper, a robust attitude and position control of a novel modified quadrotor unmanned
aerial vehicles (UAV) which has higher drive capability as well as greater robustness …
aerial vehicles (UAV) which has higher drive capability as well as greater robustness …