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EUROCAE Symposium and 56th General Assembly held in ENAC

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EUROCAE Symposium and 56th General Assembly held in ENAC on 25-26 April 2019. With a participation of more than 200 guests, chaire drone is represented by Elgiz Baskaya as one of the moderators of the fruitful sessions of the symposium.

The main focus was on automatization both for airborne and ground systems. 

Most of the parties agreed the fact that machine learning systems will have a bigger part in the years to come but not many people are working on the certification of such adaptive systems. 

Automatization was also mentioned largely for manned aviation such as for the purpose of decreasing the required number of pilots onboard while still keeping them in the loop. Since automatization was the main topic of the event, it was almost agreed by all parties that ICAO’s definition for autonomy was not sufficient or precise anymore. So there is a need for autonomy levels for aviation as is the case for car industry.

Automatization in case of safety critical situations is discussed by European Defence Agency. They stated that they are interested in fault detection and safe ditch systems for drones, which lies parallel to the topics of interests of drone chair.

For further conclusions and highlights of the conference, please refer to link.

Thesis defense by Elgiz Baskaya on Fault diagnosis for drones

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Our member Elgiz Baskaya will defend her thesis on 16/05/2019 at 10:00 am in room G11 in ENAC. We welcome you all.

Titre : ‘Fault detection and diagnosis for drones using machine learning’

Resume :

This new era of small UAVs currently populating the airspace introduces many safety concerns, due to the absence of a pilot onboard and the less accurate nature of the sensors. This necessitates intelligent approaches to address the emergency situations that will inevitably arise for all classes of UAV operations as defined by EASA (European Aviation Safety Agency). Hardware limitations for these small vehicles point to the utilization of analytical redundancy, rather than to the usual practice of hardware redundancy in manned aviation. In the course of this study, machine learning practices are implemented in order to diagnose faults on a small fixed-wing UAV to avoid the burden of accurate modeling needed in model-based fault diagnosis. A supervised classification method, SVM (Support Vector Machines) is used to classify the faults. The data used to diagnose the faults are gyro and accelerometer measurements. The idea to restrict the data set to accelerometer and gyro measurements is to check the method’s classification ability, with a small and inexpensive chip set and without the need to access the data from the autopilot, such as the control input information.

This work addresses the faults in the control surfaces of a UAV. More specifically, the faults considered are the control surface stuck at an angle and the loss of effectiveness. First, a model of an aircraft is simulated. This model is not used for the design of Fault Detection and Diagnosis (FDD) algorithms, but is instead utilized to generate data. Simulated data are used instead of flight data in order to isolate the probable effects of the controller on the diagnosis, which may complicate a preliminary study on FDD for drones. The results show that for simulated measurements, SVM gives very accurate results on the classification of the loss of effectiveness faults on the control surfaces. These promising results call for further investigation so as to assess SVM performance on fault classification with flight data. Real flights were arranged to generate faulty flight data by manipulating the open source autopilot, Paparazzi. All data and the code are available in the code sharing and versioning system, Github. Training is held offline due to the need for labeled data and the computational burden of the tuning phase of the classifiers. Results show that from the flight data, SVM yields an F1 score of 0.98 for the classification of control surface stuck faults. For the loss of efficiency faults, some feature engineering, involving the addition of past measurements is needed in order to attain the same classification performance. A promising result is discovered when spinors are used as features instead of angular velocities. Results show that by using spinors for classification, there is a vast improvement in classification accuracy, especially when the classifiers are untuned. Using spinors and a Gaussian Kernel, an untuned classifier gives an F1 score of 0.9555, which was 0.2712 when gyro measurements were used as features. In summary, this work shows that SVM gives a satisfactory performance for the classification of faults on the control surfaces of a drone using flight data.

Jury members:

– Prof. Dr. Daniel Delahaye
– Asc. Prof. Dr. Murat Bronz
– Prof. Dr. Eric Feron
– Prof. Dr. Chingiz Hajiyev
– Asc. Prof. Philippe Truillet
– Asc. Prof. Janset Dasdemir

ENAC to host the 56th EUROCAE Symposium on the 25th and 26th April

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The European Organization for Civil Aviation Equipment (EUROCAE) brings together stakeholders in the field of civil aviation with a view to establishing rules for the standardization of aeronautical systems at European and global level.

ENAC is an active member of EUROCAE, and has been supporting the European standardization activity for many years, actively participating in EUROCAE working groups and disseminating information on standards at the international level. Among the 266 EUROCAE members, from more than 37 countries, we count: manufacturers (aircraft, air and ground-based equipment, ATM systems); air service providers; national civil aviation authorities, and users (airlines, airport operators, other operators). EUROCAE works closely with the RTCA in the United States to ensure global harmonization of standards.
The conference that will take place at ENAC will cover the following areas:
– Trends for new vehicles and autonomy
– Connectivity and digital services
– Benefits and potential of ATM digital solutions
– Airport developments
– Innovations of avionics systems
– Provision of satellite services.

For information on the Symposium, please see
2019/ . Students and staff of ENAC are welcome and encouraged to participate. To participate, all you have to do is register. Online registration is free and mandatory before 17/04 at .

Enquête : Quelle maîtrise des drones civils dans l’espace aérien français ?

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Nous avons reçu récemment Maud CAZABET et Marine CLETTE, étudiantes à l’École de journalisme de Toulouse, au sein de notre laboratoire Drones à l’ENAC. Maud et Marine souhaitaient rédiger un article sur l’intégration des drones dans l’espace aérien, et nous avons répondu à certaines de leurs interrogations. Ci dessous, le fruit de leur travail, qui constitue une excellente synthèse quant à la situation actuelle.

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Yannick Jestin -WAC 2019 Madrid

VIDEO – World ATC Congress : highlight on the Drone Systems Chair

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The Chair presented its scientific work at the World ATM Congress in Madrid on March 12-14th, 2019, as part of the World ATC Congress. The conference, entitled “The ENAC – Groupe ADP – Sopra Seria research Chair on drone systems: a new way to explore drones integration into airspace” was presented by the Chairholder Yannick Jestin. The Chair was also presented throughout the exhibition on the ENAC – DSNA booth.

Read the abstract of the conference here >>>