NOISE POINT FAULT DIAGNOSIS METHOD AND FAULT DIAGNOSIS SYSTEM

Noise point data is generated by converting a vibration signal, measured at a source (noise point) of the vibration signal at a first time, into a frequency domain. Sound point data is generated by converting the vibration signal, measured at a sound point (different from the noise point) at the first time, into a frequency domain. Deep learning is applied to the noise point data and the sound point data to generate a noise prediction model for predicting frequency data of a vibration at the noise point using frequency data indicating a vibration at the sound point. The noise prediction model is applied to target vibration signal, measured at the sound point at a second time, to predicting target noise point data indicating vibration at the noise point. The predicted target noise point data is used to diagnose a fault at the noise point.