Dynamic Prediction of Performance Degradation Characteristics of Direct-Drive Electro-Hydraulic Servo Valves

Abstract

Direct-drive electro-hydraulic servo valves are widely used in the aerospace industry, in the military, and in remote sensing control, but there is little research and discussion on their performance degradation and service life prediction. Based on previous research, erosion wear is the primary physical failure form of direct-drive electro-hydraulic servo valves, and parameters such as opening, oil contamination, and pressure difference are used as influencing factors of direct-drive electro-hydraulic servo valves. Pressure gain and leakage are used as performance degradation indicators of servo valves, and multiple types of sensors are used for data monitoring. Experimental benches are arranged and verified through experiments. Based on the data and laws obtained from the experiments, the exponential smoothing algorithm and the ARIMA model algorithm were used to establish a prediction model for the servo valve, and the dynamic prediction of the performance indexes was carried out. The error calculation and analysis of the prediction results and the experimental results were then carried out using the Copula function and other mathematical knowledge to verify the accuracy and applicability of this prediction model. This study provides theoretical support and practical guidance for applying and designing direct-drive electro-hydraulic servo valves in industrial applications such as aerospace, sensor experiments, and remote sensing control.

Keywords

• direct-drive electro-hydraulic servo valves
• performance degradation
• erosion and wear
• dynamic forecasting
• machine learning