...Ufuk Himmet; Emre Kiyak Purpose This study proposes a SCADA-integrated predictive maintenance framework for aircraft engine health monitoring by leveraging machine learning and deep learning models. The objective is to enhance early fault detection capability, reduce unexpected failures...

... rights only Machine learning Trimmable horizontal stabilizer (THS) angle Roll angle Random forest Decision tree During flight, an aircraft must be capable of detecting unforeseen situations and completing its mission safely. Aircraft manufacturers traditionally integrate backup hardware...

... implications Provides an objective, data-driven tool for assessing cadets’ SA in flight simulations, supporting targeted training strategies and improving aviation safety. Originality/value Among the first to integrate facial AUs, gaze analysis and SDP technology with advanced machine learning for SA...

...Raja Selvam; Pradeep George Purpose Optimizing coating deposition processes is essential for aerospace applications, particularly for thermal barrier coatings, environmental barrier coatings and protective films on turbine engine components. This study aims to develop a machine learning based...

... presents a comprehensive comparative study of six machine learning models XGBoost, random forest ( RF ), logistic regression ( LR ), k-nearest neighbours ( KNN ), support vector machine ( SVM ) and multi-layer perceptron ( MLP ). The models used to identify and classify the jet engine faults based...

... flight. The acoustic characteristics of the propeller vary with different propeller damages. Design/methodology/approach For the research, feature extraction methods and machine learning techniques were used during damage detection from propeller acoustic data. First of all, sound recordings were...

... intelligence, machine learning, neural network and big data in civil aircraft maintenance and continuing airworthiness processes. This method is used to organize, analyze and structure the body of literature to identify research gaps in the selected scope of the study. Findings The high position of digital...

... on individual operations. This machine learning methodology also learns from the data on which the model is based. Design/methodology/approach The methodology comprises three steps. Firstly, a statistical analysis of individual operations is carried out using elementary or initial variables...

...João Antônio Dantas de Jesus Ferreira; Ney Rafael Secco Purpose This paper aims to investigate the possibility of lowering the time taken during the aircraft design for unmanned aerial vehicles by using machine learning (ML) for the configuration selection phase. In this work, a database...

... and altitude. Fault detection and reconstruction were carried out by using adaptive neural fuzzy inference system and artificial neural networks, which are machine learning methods. MATLAB software was used for all the calculations. Findings No false alarm was detected when the fault test following...

..., respectively. Originality/value This study has been added to the literature T56-A-15 turboprop engine for the current machine learning methods to multilayer feed forward neural network methods, exhaust emission and combustion efficiency index value calculation. Nowadays, there are some studies conducted...