- A. Al-Haddad, An Intelligent Fault Diagnosis Approach for Multirotor UAVs Based on Deep Neural Network of Multi-Resolution Transform Features, Drones, 7 (2023) 82 .https://doi.org/10.3390/drones7020082
- A. Al-Haddad, A. A. Jaber, P. Neranon, S. A. Al-Haddad, Investigation of Frequency-Domain-Based Vibration Signal Analysis for UAV Unbalance Fault Classification, Eng. Technol. J., 41 (2023) 915-923. https://doi.org/10.30684/etj.2023.137412.1348
- Cui, G. lai, WANG, Q. LIANG, Y. and CAO, Y., Wind Tunnel Investigation of Different Engine Layouts of a Blended-Wing-Body Transport, Chinese J. Aeronaut., 36 (2023) 123-132. https://doi.org/10.1016/j.cja.2023.04.027
- F. Westin, J. M. Balthazar, R. G. A. da Silva, Ribeiro, M. A. Tusset, Characterization of Aeroelastic Behavior in a High Aspect Ratio Wing Using Computational and Wind Tunnel Experiments, Axioms, 12 (2023). https://doi.org/10.3390/axioms12090826
- Smolka, K. Kempná,P. Kučera, K. Kempný, E. Asimakopoulou, P. Danihelka, Setup of a 3D Printed Wind Tunnel: Application for Calibrating Bi-Directional Velocity Probes Used in Fire Engineering Applications, HardwareX, 15 (2023) e00440. https://doi.org/10.1016/j.ohx.2023.e00440
- Zhiming, F. XUE, H. YU, Y. WANG, Z. JIANG, W. LU, L. DONG, Derivation and Validation of a Similarity Law for Free-Flight Wind Tunnel Tests of Parallel Stage Separation, Chinese J. Aeronaut., 36 (2023) 91–100. https://doi.org/10.1016/j.cja.2023.02.010
- Li, W. Zou, J. Fu, F. Gao, M. Yu, Development of an Anti-Vibration Aircraft Model Support System with Magnetorheological Annular Squeeze Dampers for Wind Tunnel, Mech. Syst. Signal Process., 202 (2023) 110663. https://doi.org/10.1016/j.ymssp.2023.110663
- A. Al-Haddad, A. A. Jaber, Influence of Operationally Consumed Propellers on Multirotor UAVs Airworthiness: Finite Element and Experimental Approach, IEEE Sensors J., 23 (2023) 11738-11745. https://doi.org/10.1109/JSEN.2023.3267043
- S. Shijer, Simulation of Piezoelectric in Engine Knock Sensor with Different Frequency Modes, ECS Transactions, 107 (2022) 17271. https://doi.org/10.1149/10701.17271ecst
- A. Dubaish, A. A. Jaber, Fabrication of a Test Rig for Gearbox Fault Simulation and Diagnosis, Diagnostyka, 24 ( 2023) 2023204. https://doi.org/10.29354/diag/162541
- Yassa, M. Rachek, Modeling and Detecting the Stator Winding Inter Turn Fault of Permanent Magnet Synchronous Motors Using Stator Current Signature Analysis, Math Comput Simul, 167 (2020) 325–39. https://doi.org/10.1016/j.matcom.2018.04.012
- A. Al-Haddad, A. A. Jaber, S. A. Al-Haddad, Y. M. Al-Muslim, Fault Diagnosis of Actuator Damage in UAVs Using Embedded Recorded Data and Stacked Machine Learning Models, J. Supercomput., (2023). https://doi.org/10.1007/s11227-023-05584-7
- Casabianca, Y. Zhang, Acoustic-Based UAV Detection Using Late Fusion of Deep Neural Networks, Drones, 5 (2021). https://doi.org/10.3390/drones5030054
- Xiaoqian, A Sensor Fault Diagnosis Algorithm for UAV Based on Neural Network, 2021 Int. Conf. Intell. Transp., Big Data & Smart City, Xi'an, China, (2021) 260–65. https://doi.org/10.1109/ICITBS53129.2021.00072
- Moussafir, H. Chaibi, R. Saadane, A. Chehri, A. El Rharras, G. Jeon, Design of Efficient Techniques for Tomato Leaf Disease Detection Using Genetic Algorithm-Based and Deep Neural Networks, Plant Soil, 479 (2022) 251–266. https://doi.org/10.1007/s11104-022-05513-2
- A. F. Ogaili, M. N. Hamzah, A. A. Jaber, Integration of Machine Learning (ML) and Finite Element Analysis (FEA) for Predicting the Failure Modes of a Small Horizontal Composite Blade, Int. J. Renew. Energy Res., 12 (2022) 2168–2179.
- H. Flaieh, F. O. Hamdoon, A. A. Jaber, Estimation the Natural Frequencies of a Cracked Shaft Based on Finite Element Modeling and Artificial Neural Network, Int. J. Adv. Sci. Eng. Inf. Technol., 10 (2020) 1410–16.
- Kuang-Hua, E-Design: Computer-Aided Engineering Design, Academic Press, 2016.
- Yuan, D. Lian, X. Kang, Y. Chen, and K. Zhai, Rolling Bearing Fault Diagnosis Based on Convolutional Neural Network and Support Vector Machine, IEEE Access, 8 (2020) 137395–137406. https://doi.org/10.1109/ACCESS.2020.3012053
- Al-Mukhtar, M., Modeling the Monthly Pan Evaporation Rates Using Artificial Intelligence Methods: A Case Study in Iraq, Environ. Earth Sci., 80 (2021). https://doi.org/10.1007/s12665-020-09337-0
- Al-Mukhtar, Random Forest, Support Vector Machine, and Neural Networks to Modelling Suspended Sediment in Tigris River-Baghdad, Environ. Monit. Assess., 191 (2019). https://doi.org/10.1007/s10661-019-7821-5
- A. Jamil, M. A. A. Khan , S. Khanam, Feature-Based Performance of SVM and KNN Classifiers for Diagnosis of Rolling Element Bearing Faults, Vibroengineering Procedia, 39 (2021) 36–42. https://doi.org/10.21595/vp.2021.22307
- A. Al-Haddad, A. A. Jaber, Improved UAV Blade Unbalance Prediction Based on Machine Learning and ReliefF Supreme Feature Ranking Method, J. Braz. Soc. Mech. Sci. Eng., 45 (2023b) 463. https://doi.org/10.1007/s40430-023-04386-5
|