Degradation level prediction method and degradation level prediction system

Abstract

A degradation level of a noise source is predicted by performing deep learning using frequency data indicating a vibration of the noise source during a time period and degradation data indicating degradation of the noise source during the predetermined period to determine a state estimation model. First vibration signals are measured at the noise point during a monitoring period. The first vibration signals are converted into a frequency domain, and the frequency domain converted first vibration signals are input into the state estimation model to estimate time series degradation data of degradation of the noise source during the monitoring period. A degradation prediction model is determined by deep learning using the time series degradation data. Degradation data indicating predicted degradation of the noise source during a prediction period are predicted via the degradation prediction model. A remaining useful life of the noise source may be calculated.