Deep learning has seen tremendous growth over the past decade. It set new performance limits for a wide range of applications, including computer vision, speech recognition, and machinery health monitoring. With abundance instrumentation data availability high computational power, deep continues to prove itself as an efficient tool extraction micropatterns from big repositories. This study presents comparative feature capabilities using stacked autoencoders considering use expert domain...

Real-time estimation of dynamic model parameters for an unmanned aircraft can provide valuable information about the dynamics vehicle. However, performance be severely degraded with active control system and highly collinear terms such as those found on a quadrotor aircraft. Model were estimated based flight data quadcopter System identification maneuvers generated using varying-amplitude orthogonal multisine input signals applied nominal hardware conditions damaged propeller. Recursive...

Data-driven fault diagnosis utilizing deep learning algorithms is currently a topic of great interest. Without proper training, data-driven models usually fail to generalize on operating conditions different from the ones used in training set. The majority domain adaptation research for machinery focuses transfer between limited working same machine. In real-life applications, machines operate under wide range and data are mostly available healthy with seldom failures. Hence, generated...

Intelligent fault diagnosis utilizing deep learning algorithms is currently a topic of great interest. When developing new Convolutional Neural Network (CNN) architecture to address machine problem, it common use model, with many layers, feature maps, and large kernels. These models are capable complex relationships can potentially achieve superior performance on test data. However, not only does network impose undue computational complexity for training eventual deployment, may also lead...

Aircraft prototyping and modeling is usually associated with resource expensive techniques significant post-flight analysis. The NASA Learn-To-Fly concept targets the replacement of conventional ground-based aircraft development approaches an efficient real-time paradigm. work presented herein describes a learning paradigm quadcopter unmanned that utilizes flight data. Closed-loop parameter estimation highly collinear model terms such as those found on quadrotor challenging. Using phase...

Advanced flight guidance and control laws have increased the level of automation aircrafts. To maintain a high automation, monitoring parameters is critical. In this paper, key such as angle attack (AoA), airspeed aircraft weight were analyzed for virtual sensing parameter estimation in real time. This paper presents an analytical redundancy approach during static (angle near zero) dynamic testing (moderate elevator deflection) using Extended Kalman Filter (EKF). Flight was conducted X-Plane...

Aircraft prototyping and modeling is usually associated with resource expensive techniques significant post flight analysis. The NASA Learn-To-Fly concept targets the replacement of conventional ground-based aircraft model development approaches an efficient real time paradigm. work presented herein describes intelligent excitation input design technique that determines frequencies based on predefined rotational motion dynamic model. then evaluated quadcopter unmanned utilizes new multisine...

Intelligent fault diagnosis utilizing deep learning algorithms has been widely investigated recently. Although previous results demonstrated excellent performance, features learned by Deep Neural Networks (DNN) are part of a large black box. Consequently, lack understanding underlying physical meanings embedded within the can lead to poor performance when applied different but related datasets i.e. transfer applications. This study will investigate Convolution Network (CNN) considering 4...

In recent years, Deep Learning (DL) and Internet of Things (IoT) technologies have been used deployed jointly to solve a wide range modern technical challenges in different areas. With the continuous advancement IoT connectivity solutions, applications that can benefit from such an increase is limitless. One area significantly combined strength DL Machine Health Monitoring (MHM) Systems. MHM utilizes analytical approaches tools determine state health components running machinery. The...