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This article focuses on the fixed-time stability of a class of nonlinear systems with uncertain disturbances and time-varying delays. Different from other papers, the second-order sliding mode control algorithm (SOSMCA) is developed in this article to study the fixed-time stability of nonlinear systems for the first time. Additionally, the novel sliding mode surface (SMC) and second-order SMC are presented. And the stability and reachability of the sliding-mode dynamics under a faster settling time are demonstrated. Finally, the applicability and validity of the obtained SOSMCA are demonstrated by a simulation example with the F-404 aircraft engine model. [ABSTRACT FROM AUTHOR]

Aircraft encounters with volcanic ash have caused significant damage over the past 40 years, resulting in particular attention being given to the issue. We analyzed the volcanic ash-aircraft encounter database published by the USGS. We added new volcanic eruptions and parameters such as eruption types, and dry–wet. Then, we applied standard and advanced statistical methods. Over 130 encounters have been documented in the mentioned database, with volcanic ash causing severe abrasions to the windshield, airframe, wings, and engine components. In nine cases, aircraft engines failed. We applied the binary regression analysis and some laboratory melting experiments on volcanic ash. Besides phreatomagmatism, we use the term external water in this work to describe meteoric water that enters volcanic plumes through precipitation or melting ice on ice-capped volcanoes. We demonstrated that engine failure occurs when our regression analyses undergo dry-to-wet conditions. In other words, statistically, there is a positive correlation between wet ash encounters with aircraft and engine failure incidents. Moreover, experiments conducted at 900 °C and under 40 bar pressure showed increased sintering in the dry sample, while melting textures were more prevalent in hydrated samples. We concluded that despite the various eruptive dynamics of volcanic ash, the introduction of external water into the volcanic plumes, probably causing instantaneous hydration of volcanic ash, is a common factor in engine failure incidents. Thus, we have identified the reasons behind engine failures during encounters between aircraft and volcanic ash and the specific damage that can occur depending on the type of eruption involved. [ABSTRACT FROM AUTHOR]

In the realm of prognosticating the remaining useful life (RUL) of pivotal components, such as aircraft engines, a prevalent challenge persists where the available historical life data often proves insufficient. This insufficiency engenders obstacles such as impediments in performance degradation feature extraction, inadequacies in capturing temporal relationships comprehensively, and diminished predictive accuracy. To address this issue, a 1D CNN-GRU prediction model for few-shot conditions is proposed in this paper. In pursuit of more comprehensive data feature extraction and enhanced RUL prognostication precision, the Convolutional Neural Network (CNN) is selected for its capacity to discern high-dimensional features amid the intricate dynamics of the data. Concurrently, the Gated Recurrent Unit (GRU) network is leveraged for its robust capability in extracting temporal features inherent within the data. We combine the two to construct a CNN-GRU hybrid network. Moreover, the integration of data distribution alongside correlation and monotonicity indices is employed to winnow the input of multi-sensor monitoring parameters into the CNN-GRU network. Finally, the engine RULs are predicted by the trained model. In this paper, experiments are conducted on a sub-dataset of the National Aeronautics and Space Administration (NASA) C-MAPSS multi-constraint dataset to validate the effectiveness of the method. Experimental results have demonstrated that this method has high accuracy in RUL prediction tasks, which can powerfully demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

One source of modern aircraft engine noise is the fan, which is especially noticeable during takeoff at high angular rotation speeds. In such modes, supersonic flow around the fan blades occurs, which leads to the formation of shock waves that propagate upstream until they exit the engine duct. As a result, specific noise is emitted into the front hemisphere, consisting of a number of harmonics that are multiples of the fan rotation frequency. The paper analyzes this effect using a simple model of the propagation of a system of shock waves. An energy approach is used to demonstrate that a system of shock waves with shocks of equal amplitude attenuates the most rapidly. [ABSTRACT FROM AUTHOR]

Wear is progressive deterioration of machine components by the loss of weight and shape results in generation of wear debris. For the analysis of these wear debris, ferrography method is widely used. This method was successfully used to examine the condition monitoring of martial aircraft engines, gearboxes, bearings, heavy earth moving machineries, turbines etc. Ferrographic condition monitoring as a preventive maintenance done by collecting oil sample. Ferrogram's images taken under a microscope for monitoring wear particle contamination of these oil samples. Both qualitative and quantitative analysis of the wear particles was done from these image analyses. Novelty of this research work is use of hot ferrography for getting detailed information about machine health condition. A detailed Excel sheet containing information about the size distribution of wear particles in terms of count, area, perimeter, aspect ratio, and mean diameter was created using data from the Olympus microscope software and a ferrogram. From this data, wear mode, its source, mechanism can be easily detected. [ABSTRACT FROM AUTHOR]

The chemical composition, microstructure and properties of races of a foreign aircraft engine bearing are studied. The material and the heat treatment method are determined, the microstructure of the diffusion layer is analyzed, the thickness of the diffusion and effective layers is calculated, and curves of the distribution of hardness and residual stresses over the diffusion layer depth are plotted. The data obtained can be used for import substitution of heat-resistant bearings for aerospace applications. [ABSTRACT FROM AUTHOR]

Planned maintenance is required by licensed maintenance organizations to detect and prevent performance degradation in aircraft engines. In the literature, engine performance is evaluated with parameters that show engine performance. Fuel flow parameter is one of the important parameters that shows engine performance. In the models developed earlier, no engine performance evaluation was made with the fuel flow parameter at all stages from the take-off to the landing of the aircraft. In this study, fuel flow parameter is estimated with over 99.9% accuracy by using artificial neural network in MATLAB® software. In order to detect the engine performance deterioration of the aircraft, the fuel flow values obtained from the artificial neural network and confidence intervals with 99% confidence level were established. Each value taken from the fuel flow sensor is evaluated by the model in all flight phases. In the model, engine performance is considered normal if the fuel flow value is within the confidence interval, and abnormal (anomaly) if it is outside the confidence interval. An accuracy of over 99.9% was achieved and results of this study showed that fuel flow rate of the engine of interest was within the confidence interval (no performance deterioration). [ABSTRACT FROM AUTHOR]

The robust guaranteed cost composite anti-bump L2\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$L_2$$\end{document}-gain control for switched systems is investigated in this paper. By constructing a convex combination of positive definite matrices and segmenting the switching interval, a novel multiple convex Lyapunov function suitable for composite anti-bump switching (ABS) control problem is proposed. A new definition of composite ABS performance is presented without reference signals, which restrains the control and rate bumps of the system caused by switchings only at switching instants. Then, imposing a dwell time on the state-dependent switching law, a mixed state-dependent switching scheme is presented based on the multiple convex Lyapunov function. Robust guaranteed cost composite anti-bump control strategy is established for a class of switched systems to overcome the conflicts among guaranteed cost performance, composite bumpless switching performance and L2\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$L_2$$\end{document}-gain performance. Eventually, an actual aircraft engine model is employed to demonstrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]