Application of neural network technologies to load monitoring in aircraft structure bearing elements

Abstract

Economic efficiency in the operation of aircraft local air lines (LA) can be improved by increasing the awareness of the loading and aircraft structure integrity, with the subsequent adjustment of the maintenance program in accordance with the actual operating conditions. The allowance for specific features of loading load-bearing elements at transport aircraft during particular operations provides a significant extending in the safe life (in some cases, by several times). However, at the moment, load monitoring systems in the aviation industry have not yet been implemented universally. The implementation of the well-known approaches developed for monitoring and analyzing loads requires significant changes in the programs and procedures for maintaining airworthiness, including the need to install additional sophisticated measuring equipment. We propose an alternative approach to existing methods of load monitoring without using additional measuring equipment. The main stage is formation of the relationship between the flight parameters recorded by the standard on-board recorder and the loading parameters, which are determined by computational and experimental methods as a result of processing strain gauge data. A sufficient bulk of the strain data is usually obtained during the flight tests at the certification stage. Testing of this technique is considered with reference to the example of the loads in the elements of high lift devices of aircraft flaps. The average error in the estimates of the forces in the connecting rods of the inner flaps does not exceed 6%. The results obtained make it possible to determine with the acceptable accuracy the individual accumulated damageability of an aircraft structure and to assess the residual safe life. The presented approach is a part of the methodological framework necessary for the development and implementation of modern means of analyzing the integrity of the structure, implemented on the basis of on-board monitoring systems of local airlines aircraft.