Abnormal detection technique for civil aircraft antiskid brake system based on LOF algorithm

Brake system is a crucial component for aircraft landing deceleration, and its malfunction poses a direct threat to landing safety. Currently, brake system is predominantly diagnosed post-event using the fault tree analysis method, which has limited effectiveness in preventing failures. Based on vast amount of experimental data accumulated from aircraft, this paper utilizes the LOF (Local Outlier Factor) algorithm to calculate the local reachability density of the experimental data points, thereby obtaining the LOF distribution for the normal operation of the antiskid brake system. On this basis, the local reachability density of new experimental points is calculated to identify whether they are abnormal outliers, thus enabling the detection of abnormal states in the antiskid brake system. The results of the case study demonstrate that this method can effectively identify abnormal states in the antiskid brake system. By isolating and rectifying these detected abnormalities using engineering expertise, the frequency of failures during brake system operation can be significantly reduced, thereby enhancing fault prevention measures and offering promising application prospects.