landing gear
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2022 ◽  
pp. 541-571
Snorri Gudmundsson

2021 ◽  
Vol 12 (1) ◽  
pp. 400
Quoc-Viet Luong ◽  
Bang-Hyun Jo ◽  
Jai-Hyuk Hwang ◽  
Dae-Sung Jang

This paper adopts an intelligent controller based on supervised neural network control for a magnetorheological (MR) damper in an aircraft landing gear. An MR damper is a device capable of adjusting the damping force by changing the magnetic field generated in electric coils. Applying an MR damper to the landing gears of an aircraft could minimize the impact at landing and increase the impact absorption efficiency. Various techniques proposed for controlling the MR damper in aircraft landing gears require information on the damper force or the mass of the aircraft to determine optimal parameters and control commands. This information is obtained by estimation with a model in a practical operating environment, and the accompanying inaccuracies cause performance degradation. Machine learning-based controllers have also been proposed to address model dependency but require a large number of drop test data. Unlike simulations, which can conduct a large number of virtual drop tests, the cost and time are limited in the actual experimental environment. Therefore, a neural network controller with supervised learning is proposed in this paper to simulate the behavior of a proven controller only with system states. The experimental data generated by applying the hybrid controller with the exact mass and force information, which has demonstrated high performance among the existing techniques, are set as the target for supervised learning. To verify the effectiveness of the proposed controller, drop test experiments using the intelligent controller and the hybrid controller with and without exact information about aircraft mass and force are executed. The experimental results from the drop tests of a landing gear show that the proposed controller maintains superior performance to the hybrid controller without using explicit damper models or any information on the aircraft mass or strut force.

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8440
Fuyang Li ◽  
Zhiguo Wu ◽  
Jingyu Li ◽  
Zhitong Lai ◽  
Botong Zhao ◽  

This paper presents a method for measuring aircraft landing gear angles based on a monocular camera and the CAD aircraft model. Condition monitoring of the aircraft landing gear is a prerequisite for the safe landing of the aircraft. Traditional manual observation has an intense subjectivity. In recent years, target detection models dependent on deep learning and pose estimation methods relying on a single RGB image have made significant progress. Based on these advanced algorithms, this paper proposes a method for measuring the actual angles of landing gears in two-dimensional images. A single RGB image of an aircraft is inputted to the target detection module to obtain the key points of landing gears. The vector field network votes the key points of the fuselage after extraction and scale normalization of the pixels inside the aircraft prediction box. Knowing the pixel position of the key points and the constraints on the aircraft, the angle between the landing gear and fuselage plane can be calculated even without depth information. The vector field loss function is improved based on the distance between pixels and key points, and synthetic datasets of aircraft with different angle landing gears are created to verify the validity of the proposed algorithm. The experimental results show that the mean error of the proposed algorithm for the landing gears is less than 5 degrees on the light-varying dataset.

2021 ◽  
pp. 1-20
S. Gan ◽  
X. Fang ◽  
X. Wei

Abstract This paper investigates the feasibility of improving the aircraft landing performance by design the damping orifice parameters of the landing gear using lattice Boltzmann method coupled with the response surface method. The LBM is utilised to simulate characteristics of the damping orifice after model validation. The numerical model of the landing gear using simulated damping force is validated by single landing gear drop test. Based on the numerical model and the response surface functions, the sensitivity analysis and the optimisation design are performed. The maximum error of mean velocity simulated using LBM with experimental data is 7.07% for sharp-edged orifices. Moreover, the numerical model predicts the landing responses adequately, the maximum error with drop test data is 2.51%. The max overloading of the aircraft decreases by 5.44% after optimisation, which proves that this method is feasible to design the damping orifice for good landing performance.

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8188
Tommaso Campi ◽  
Silvano Cruciani ◽  
Francesca Maradei ◽  
Mauro Feliziani

A wireless charging pad for drones based on resonant magnetic technology to recharge the internal battery is presented. The goal of the study was to design a robust, reliable and efficient charging station where a drone can land to automatically recharge its battery. The components of the wireless power transfer (WPT) system on board the drone must be compact and light in order not to alter the payload of the drone. In this study, the non-planar receiving coil of the WPT system is integrated into the drone’s landing gear while the transmitting pad is designed to be efficient for any landing point and orientation of the drone in the charging pad area. To meet these requirements, power transmission is accomplished by an array of planar coils integrated into the ground base station. The configuration of the WPT coil system, including a three-dimensional receiving coil and a multicoil transmitter, is deeply analyzed to evaluate the performance of the WPT, considering potential lateral misalignment and rotation of the receiving coil due to imprecise drone landing. According to the proposed configuration, the battery of a light drone (2 kg in weight and 0.5 kg in payload) is recharged in less than an hour, with an efficiency always greater than 75%.

2021 ◽  
Vol 11 (23) ◽  
pp. 11235
Longlong Huang ◽  
Kun Zhao ◽  
Junbiao Liang ◽  
Victor Kopiev ◽  
Ivan Belyaev ◽  

The landing gear is widely concerned as the main noise source of airframe noise. The flow characteristics and aerodynamic noise characteristics of the landing gear were numerically simulated based on Large Eddy Simulation and Linearized Euler Equation, and the feasibility of the simulation model was verified by experiments. Then the wind speed effect on the flow and acoustic characteristics of the minor cavity structures in a two-wheel landing gear were analyzed. The results show that the interaction of vortices increases with the increase of velocity at the brake disc, resulting in a slight increase in the amplitude of pressure fluctuation at 55 m·s−1~75 m·s−1. With the increase of speed, the obstruction at the lower hole of torque link decreases, and many vortical structures flow out of the lower hole and are dissipated, so that the pressure fluctuation amplitude of 75 m·s−1 almost does not increase relative to 55 m·s−1. The contribution of each part in the landing gear to the overall noise is as follows: shock strut > tire > torque link > brake disc. At the speed of 34 m·s−1~55 m·s−1, the contribution of each component to the total noise increases with the increase of speed, and the small components such as torque link and brake disc contribute more to the total noise. At the speed of 55 m·s−1~75 m·s−1, the increase of overall noise mainly comes from the main components such as shock strut and tire, and the brake disc and torque link contribute very little to the overall noise. It provides a reference for the further noise reduction optimization design of the landing gear.

2021 ◽  
Paulina Zenowicz

There is a need to design new, lighter aircraft structures, which has a direct impact on the safety and costs of aircraft maintenance. One of basic parts of an aircraft is ites landing gear, whose main functions are to enable taxiing, safe landing, take-off, and to assist the remainder of ground operations. Landing gear failures are usually related to metallurgy, processing, environment, design, and causes of overload. These are conditions that can be prevented using modern methods to calculate the strength of such a landing gear in various conditions. The paper presents stages of a simulation study of the fixed three-wheeled spring landing gear for an ultralight aircraft. Analysis of forces acting on the landing gear during drop test and their implementation by numerical computer methods allowed for the creation of a model in the CAD (Computer-Aided Design) tool and its FEA (Finite Element Analysis). These results were compared between a modeled classic spring landing gear and the one made of composite materials. The further goal of the research will be to build a drop test stand for a small landing gear used in airplanes and drones. This method has a significant impact on simplifying the design of the landing gear, its modeling, and optimization.

2021 ◽  
Vol 13 (4) ◽  
pp. 205-212
Ilie NICOLIN ◽  
Bogdan Adrian NICOLIN

Failure Mode and Effect Analysis (FMEA) techniques were originally developed by the US Military and have been used as techniques for assessing the reliability and effects of equipment failures. However, the first notable applications of FMEA techniques are related to the impressive development of the aerospace industry in the mid-1960s. FMEA is a methodology for systematically analyzing the failure modes of a project, product or process, prioritizing their importance, identifying system failure mechanisms, analyzing potential failure modes and the effects of these failures, followed by corrective actions, which are applied in the stage of conceptual and detailed design of the product. All approaches to FMEA methods in the scientific literature converge to achieve three goals, namely: the ability to predict the type of failure that may occur, the ability to predict the effects of the failure on system operation, and the establishment of the steps to prevent failure and its effects on the system operation. The FMEA for the project of a nose landing gear analyzes the failure modes of the product and their effects in operation, as a consequence of project deficiencies and identifies or confirms critical functions. To apply the FMEA method to the project of the nose landing gear of a military training aircraft, the following steps need to be accomplished: product description and identification of components; identification of functions; identification of potential ways of failure; estimating the frequency of causes of failure; appreciation of the severity of effects; assessment of difficulties in detecting defects; calculation of the Risk Priority Number (RPN); establishing the measures and corrective actions for the analyzed project.

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