Earticle

Flight simulators are crucial devices for aircraft piloting training and simulation, requiring regular inspections to maintain performance and operational quality. This study explores the development of an automated inspection system for flight simulators to automate quality inspections of control loading systems (CLS). While quality inspection of the control loading system (CLS) is essential for flight simulators, manual inspections are common practice. To address this, we developed an Auto Qualification Test Guide (Auto QTG) using artificial control logic and sensor data and applied it to the militarily simulator. Experimental results demonstrate that Auto QTG successfully automates quality inspections of CLS, enhancing accuracy and efficiency. This automated inspection system is expected to contribute to improving the operation and maintenance of flight simulators.

In this study, to investigate the effects of omitting low-amplitude cycles from a flight-simulation loading, crack growth tests are conducted on 2124-T851 aluminum alloy specimens. Three test spectra are generated by omitting small load ranges as counted by the rain-flow count method. The crack growth test results are compared with the data obtained from the flight-simulation loading. The experimental results show that omission of the load ranges below 5% of the maximum load does not significantly affect crack growth behavior, because these are below the initial stress intensity factor range. However, in the case of omitting the load ranges below 15% of the maximum load, crack growth rates decrease, and therefore crack growth curve deviates from the crack growth data under the flight-simulation loading. To optimize the load range that can be omitted, crack growth curves are simulated by the stochastic crack growth model. The prediction shows that the omission level can be extended to 8% of the maximum load and test time can be reduced by 59%.