FIELD: elevator equipment.
SUBSTANCE: computer-implemented method of training a machine learning model to detect installation errors in an elevator, particularly an elevator door, wherein the machine learning model is a combination of a Set Function model and a Fourier Transform model, comprising the step of placing multiple sensors of physical parameters near the elevator; the step of detecting values of physical parameters through said sensors to obtain a data set containing at least one time series; the step of obtaining the first input layer by extracting features from the data set; the step of obtaining the second input layer by extracting features from the data set. The first input level is used as input for the Set Function model, and the second input level is used as input for the Fourier Transform model.
EFFECT: improves detection of faulty elevator door installations.
10 cl, 5 dwg
