BEYOND SPEED THRESHOLDS: ENERGY MANAGEMENT DEGRADATION LEADING TO FAST ON APPROACH
Abstract. Unstable approaches remain one of the most persistent safety risks in commercial aviation and are strongly associated with long landing and runway excursion events. While conventional safety monitoring practices primarily rely on threshold-based exceedance detection within stabilized approach criteria, considerably less attention has been given to the underlying energy management processes that precede such […]
EVALUATION OF THE EFFECTIVENESS OF TECHNOLOGICAL OPERATIONS FOR APPLYING PAINT COATINGS TO AIRCRAFT SAMPLES USING A FLEXIBLE ROBOT
Abstract. The article discusses the issues of increasing the efficiency of paint and varnish coating operations on aircraft samples using a flexible industrial robot. The subject of the research is the technological processes of automated application of paint and varnish materials on the surface of aircraft structures of complex geometric shape, as well as methods […]
INTELLIGENT ANALYSIS OF UNSTRUCTURED AVIATION MAINTENANCE DATA BASED ON DENSITY-BASED CLUSTERING AND LARGE LANGUAGE MODELS
Аbstract. Ensuring flight safety and improving the economic efficiency of aircraft maintenance require intelligent analysis of unstructured textual reports. Traditional topic modelling methods are limited by the loss of semantic context in short messages and the high labour intensity of manual text preprocessing. The subject of this study is methods for the automated extraction of […]
IDENTIFICATION OF LATENT FAILURE TYPES IN AN AIRCRAFT EXTERIOR LIGHTING SYSTEM BASED ON LATENT DIRICHLET ALLOCATION
Abstract. The continuous growth of unstructured textual data volumes in aircraft maintenance systems creates a demand for automated analysis methods. Traditional defect categorization using standard codes is often insufficiently detailed to reveal the true root causes of failures, as routine operations and critical malfunctions are frequently combined within a single system category. The subject of […]
EVALUATION OF THE EFFECTIVENESS OF THE DEVELOPED METHOD FOR CLASSIFYING EMOTIONAL STATES THROUGH SPEECH SIGNALS
Abstract. This study presents an innovative method for classifying emotional states through speech signals, leveraging advanced signal processing and machine learning techniques. The proposed method incorporates a multi-step approach, including feature extraction, selection, and classification. Initially, key acoustic features such as pitch, intensity, formants, and Mel-frequency cepstral coefficients (MFCCs) are extracted from the speech signals. […]