Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft

KILIC, UGUR

Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft

Uğur Kılıç (Erzincan Binali Yıldırım Üniversitesi, Ali Cavit Çelebioğlu Sivil Havacılık Yüksekokulu, Aviyonik Bölümü, Erzincan, Türkiye)

Havacılık ve Uzay Teknolojileri Dergisi

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Yıl: 2023 Cilt: 16 Sayı: 2 Sayfa Aralığı: 20 - 35 Metin Dili: İngilizce İndeks Tarihi: 12-02-2024

Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft

Öz:

Airspeed data is so important for an aircraft operation. This study is focused on the estimation of the airspeed data without any additional measurement source such as hardware redundancy. The flight data obtained from a commercial aircraft is processed with a deep learning algorithm, particularly LSTM recurrent neural networks that are developed based on Matrix Laboratory (MATLAB). Correlation analysis is carried out for related data according to a 95% confidence interval for each coefficient in the study to show strong predictor candidates. Data related to the airspeed are processed using Holdout Cross-Validation Technique. According to the results, the designed model achieved an R-squared of 0.9999, a root-mean-squared error of 0.8303 knots, and a standard error of 0.0092 knots. These results show that it is possible to accurately estimate aircraft airspeed data using LSTM recurrent neural network in case of the airspeed data cannot be provided to the flight crew.

Anahtar Kelime: Aircraft Sensor Estimation Machine Learning Deep Learning

Ticari Uçaklar için Derin Öğrenme Tabanlı Hava Hızı Tahmin Sistemi

Öz:

Hava hızı verisi, bir uçak operasyonu için çok önemlidir. Bu çalışma, donanım yedekliliği gibi herhangi bir ek ölçüm kaynağı olmadan hava hızı verisinin tahminine odaklanmıştır. Ticari bir uçaktan elde edilen uçuş verileri, özellikle LSTM tekrarlayan sinir ağları kullanılarak Matrix Laboratuvarı (MATLAB) tabanlı geliştirilen bir derin öğrenme algoritması ile işlenmiştir. Güçlü yordayıcı adaylarını göstermek için çalışmadaki her katsayı %95 güven aralığına göre ilgili verilere yönelik korelasyon analizine tabi tutulmuştur. Hava hızıyla ilgili veriler, Uzun Süreli Çapraz Doğrulama Tekniği kullanılarak işlenmiştir. Sonuçlara göre, tasarlanan model 0,9999 R-kare, 0,8303 knot kök-ortalama kare hatası ve 0,0092 knot standart hata elde etmiştir. Bu sonuçlar, hava hızı verisinin uçuş ekibine sağlanamaması durumunda LSTM tekrarlayan sinir ağı kullanılarak uçak hava hızı verisinin doğru bir şekilde tahmin edilmesinin mümkün olduğunu göstermektedir.

Anahtar Kelime: Uçak Sensörü Tahmin Makine Öğrenmesi Derin Öğrenme

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	KILIC U (2023). Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. , 20 - 35.
Chicago	KILIC UGUR Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. (2023): 20 - 35.
MLA	KILIC UGUR Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. , 2023, ss.20 - 35.
AMA	KILIC U Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. . 2023; 20 - 35.
Vancouver	KILIC U Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. . 2023; 20 - 35.
IEEE	KILIC U "Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft." , ss.20 - 35, 2023.
ISNAD	KILIC, UGUR. "Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft". (2023), 20-35.

APA	KILIC U (2023). Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. Havacılık ve Uzay Teknolojileri Dergisi, 16(2), 20 - 35.
Chicago	KILIC UGUR Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. Havacılık ve Uzay Teknolojileri Dergisi 16, no.2 (2023): 20 - 35.
MLA	KILIC UGUR Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. Havacılık ve Uzay Teknolojileri Dergisi, vol.16, no.2, 2023, ss.20 - 35.
AMA	KILIC U Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. Havacılık ve Uzay Teknolojileri Dergisi. 2023; 16(2): 20 - 35.
Vancouver	KILIC U Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft. Havacılık ve Uzay Teknolojileri Dergisi. 2023; 16(2): 20 - 35.
IEEE	KILIC U "Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft." Havacılık ve Uzay Teknolojileri Dergisi, 16, ss.20 - 35, 2023.
ISNAD	KILIC, UGUR. "Deep Learning-Based Airspeed Estimation System for a Commercial Aircraft". Havacılık ve Uzay Teknolojileri Dergisi 16/2 (2023), 20-35.