On real-time fatigue damage prediction for steam turbine

Abstract

This paper presents a real-time prediction method for fatigue damage of steam turbine. The temperature data and thermal stress data of the key parts are extracted by calculating the temperature field and the stress field. The composite stress is calculated according to the fourth strength theory, and the measured stress data are normalized. Support vector regression model is established, input and output data are trained and predicted. The relationship between stress and damage function is analyzed and fitted, and the framework of the real time fatigue damage prediction system is established. In the end, the effectiveness of the method is verified by simulation experiment.