Intelligent Monitoring Method of Aircraft Swashplate Plunger Pump Fluidity Based on Different Working Conditions

Abstract

The swashplate plunger pump is one of the key components of the aircraft hydraulic transmission system, and its reliable operation is directly related to the flight safety of the aircraft. The key factor affecting the safety of swashplate plunger pumps is flowability. Therefore, an intelligent monitoring method for the flowability of aircraft swashplate plunger pumps based on different operating conditions is proposed. By analyzing the structure and working principle of the swashplate plunger pump, the types of abnormal flow phenomena are identified. Based on this, a multi-scale permutation entropy algorithm is used to extract the features of monitoring data. Due to the large amount of monitoring data features, fusion rules have been developed based on the feature fusion results of its traffic monitoring data. Based on the characteristics of abnormal flow data, an extreme learning machine is used to determine whether the flow of the swashplate plunger pump is abnormal, thereby achieving intelligent monitoring. The experimental data shows that under different experimental conditions, the flow monitoring results of the swash plate plunger pump obtained after the proposed method application are completely consistent with the actual results, with an accuracy of 100%; The monitoring time ranges from 0.20 s to 0.48 s, consistently not exceeding 0.5 s, and the monitoring efficiency is higher, fully confirming the better application performance of the proposed method.