Automated verification complex for cockpit display systems of next-generation civil aircraft


DOI: 10.34759/trd-2023-131-18

Аuthors

Dyachenko S. A.

e-mail: sergey.dyachenko@uac-ic.ru

Abstract

According to accident statistics provided by international aviation authorities and leading airplane manufacturers, loss of control in-flight stands as the primary cause of air crashes in terms of the number of victims. One of the contributing factors to loss of control in-flight is the failure or malfunction of aircraft systems, which may result from undetected errors during the design phase. To address this issue, reducing the influence of the human factor in the development of on-board systems is crucial, and this can be achieved through the implementation of automation instruments.

The article encompasses an analysis of verification automation tools for civil aircraft on-board systems currently available on the market, including formal verification and system testing instruments, as well as complex solutions. Moreover, the research highlights that the growth potential of these tools lies in graphic and aural information testing. This aspect becomes relevant when assessing the human-machine interface within cockpit displays and flight warning systems verification.

Additionally, the article proposes the architecture, algorithms, and software of such a complex providing text information recognition for cockpit display systems. The conducted tool testing confirmed its high effectiveness. While the complete exclusion of an operator from the verification process is deemed unacceptable due to safety concerns, the aforementioned type of tools can potentially enhance the human-machine interface systems’ reliability by mitigating the influence of the human factor, and it can also lead to savings in time and financial resources.

Concurrently, the underlying methods of computer image processing are universal, enabling the developed complex to be adapted to diverse technical systems featuring human-machine interfaces (including industries beyond aviation).

Keywords:

civil aircraft, avionics, automation, verification, flight safety, human-machine interface, image recognition

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