Operational Load Monitoring System Implementation for Su-22UM3K Aging Aircraft

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The paper presents experimental verification of customized resistive crack propagation sensors as an alternative method for other common structural health monitoring (SHM) techniques. Most of these are sensitive to changes in the sensor network configuration and a baseline dataset must be collected for the analysis of the structure condition. Sensors investigated within the paper are manufactured by the direct-write process with electrically conductive, silver-microparticle-filled paint to prepare a tailored measuring grid on an epoxy or polyurethane coating as a driving/insulating layer. This method is designed to enhance the functionality and usability compared to commercially available crack gauges. By using paint with conductive metal particles, the shape of the sensor measuring grid can be more easily adapted to the structure, while, in the previous approach, only a few grid-fixed sensors are available. A fatigue test on the compact tension (CT) specimen is presented and discussed to evaluate the ability of the developed sensors to detect and monitor fatigue cracks. Additionally, the ARIMA time series algorithm is developed both for monitoring and predicting crack growth, based on the acquired data. The proposed sensors’ verification reveal their good performance to detect and monitor fatigue fractures with a relatively low measurement error and ARIMA estimated crack length compared with the crack opening displacement (COD) gauge.

Section: Introductionmentioning

confidence: 99%

The Experimental Verification of Direct-Write Silver Conductive Grid and ARIMA Time Series Analysis for Crack Propagation

Kurnyta

Baran

Kurnyta-Mazurek

et al. 2021

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“…OLM is particularly useful in aeronautical and aerospace industries [7,8] where continual monitoring allows one to reduce the costs of maintenance actions (assessment of structural components condition based on visual inspections, X-ray analysis, eddy-current testing, etc.) and increase aircraft availability (aircraft does not have to be taken out of service for maintenance and it may have a prolonged life) [1].…”

Section: Introductionmentioning

confidence: 99%

Operational Load Monitoring of a Composite Panel Using Artificial Neural Networks

Mucha

Kuś

Viana

et al. 2020

Operational Load Monitoring consists of the real-time reading and recording of the number and level of strains and stresses during load cycles withstood by a structure in its normal operating environment, in order to make more reliable predictions about its remaining lifetime in service. This is particularly important in aeronautical and aerospace industries, where it is very relevant to extend the components useful life without compromising flight safety. Sensors, like strain gauges, should be mounted on points of the structure where highest strains or stresses are expected. However, if the structure in its normal operating environment is subjected to variable exciting forces acting in different points over time, the number of places where data will have be acquired largely increases. The main idea presented in this paper is that instead of mounting a high number of sensors, an artificial neural network can be trained on the base of finite element simulations in order to estimate the state of the structure in its most stressed points based on data acquired just by a few sensors. The model should also be validated using experimental data to confirm proper predictions of the artificial neural network. An example with an omega-stiffened composite structural panel (a typical part used in aerospace applications) is provided. Artificial neural network was trained using a high-accuracy finite element model of the structure to process data from six strain gauges and return information about the state of the panel during different load cases. The trained neural network was tested in an experimental stand and the measurements confirmed the usefulness of presented approach.

“…This paper presents the preparation and execution of that type of pre-flight verification experiment on an example of a UAV used in the Polish Air Force [6] as remotely piloted aerial system (RPAS). Although that UAV has already been used for many years, proposed structural (example in Reference [7] for manned fighter-bomber). The operation of monitoring system elements will also be tested during static investigation.…”

Section: Introductionmentioning

confidence: 99%

“…For the front fuselage, The supplementary information from the engine test was the evaluation of the joint operation of two wireless data links: one for UAV control and telemetry and the second for a strain and acceleration monitoring system for future activities during the flight test. Real-time load monitoring system implementation for the aircraft is currently one of the main tasks to ensure the optimal maintenance and utilization strategy as a part of health and usage monitoring for technical objects [7,18] for the individual aircraft tracking (IAT) concept. Regarding wireless data links, one of the concerns was the fact that both are using the same frequency of 2.4 GHz.…”

mentioning

confidence: 99%

Numerical and Experimental UAV Structure Investigation by Pre-Flight Load Test

Kurnyta

Zieliński

Reymer

et al. 2020

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This paper presents the preparation and execution of on-ground static and engine load tests for the composite unmanned aerial vehicle (UAV). The test was conducted for pre-flight structural strength verification of the remotely piloted aerial target named HORNET, after introducing some structural modifications. The ground tests were performed before the flight test campaign, to ensure the strength and operational safety of the modified structure. The panel method and Computer Aided Design (CAD) modelling were adopted for numerical evaluation of aerodynamic and inertial forces’ distribution to simulate loading scenarios for launch, flight and parachute deploying conditions during the static test. Then, the multi-stage airframe static test was prepared and executed with the use of a designed modular test rig, artificial masses, as well as a wireless strain measurement system to perform structure verification. The UAV was investigated with 150% of the typical load spectrum. Furthermore, an engine test was also conducted on a ground test stand to verify strain and vibration levels in correspondence to engine speed, as well as the reliability of data link and the lack of its interferences with wireless control and telemetry. In the article, data achieved from the numerical and experimental parts of the test are discussed, as well as post-test remarks are given.