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Open AccessArticle

Detection of Common Causes between Air Traffic Serious and Major Incidents in Applying the Convolution Operator to Heinrich Pyramid Theory

1
Department of Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos, School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM), Plaza Cardenal Cisneros n3., 28040 Madrid, Spain
2
Aeronautic, Space & Defence Division, ALTRAN Innovation S.L., Calle Campezo 1, 28022 Madrid, Spain
3
Centre for Aeronautics, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, Bedford MK43 0AL, UK
*
Authors to whom correspondence should be addressed.
Entropy 2019, 21(12), 1166; https://doi.org/10.3390/e21121166
Received: 28 October 2019 / Revised: 25 November 2019 / Accepted: 26 November 2019 / Published: 28 November 2019
(This article belongs to the Section Information Theory, Probability and Statistics)
Heinrich’s pyramid theory is one of the most influential theories in accident and incident prevention, especially for industries with high safety requirements. Originally, this theory established a quantitative correlation between major injury accidents, minor injury accidents and no-injury accidents. Nowadays, researchers from different fields of engineering also apply this theory in establishing quantitatively the correlation between accidents and incidents. In this work, on the one hand, we have detected the applicability of this theory by studying incident reports of different severities occurred in air traffic management. On the other hand, we have deepened the analysis of this theory from a qualitative perspective. For this purpose, we have applied the convolution operator in identifying correlations between contributing causes to different incident severities, also known as precursors to accidents, and system failures. The results suggested that system failures are mechanisms by which the causes are manifested. In particular, the same underlying cause can be manifested through different failures which contribute to incidents with different severities. Finally, deriving from this result, an artificial neuronal network model is proposed to recognize future causes and their possible associated incident severities.
Keywords: Heinrich’s pyramid theory; convolutional matrix; ATM incident analysis; information theory; aviation safety Heinrich’s pyramid theory; convolutional matrix; ATM incident analysis; information theory; aviation safety
MDPI and ACS Style

Liang Cheng, S.Z.; Arnaldo Valdés, R.M.; Gómez Comendador, F.; Sáez Nieto, F.J. Detection of Common Causes between Air Traffic Serious and Major Incidents in Applying the Convolution Operator to Heinrich Pyramid Theory. Entropy 2019, 21, 1166.

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