The invention discloses an
elevator failure recognition method based on a
convolutional neural network. The
elevator failure recognition method comprises the steps that 1,
elevator motion data are collected and are converted into a time-
spectrogram as a sample set through
wavelet transform; 2, the time-
spectrogram in the sample set is divided into a
training set and a
test set, failure types and failure degrees of samples in the
training set are marked as known labels of data samples; 3, the
convolutional neural network is built, the time-
spectrogram in the
training set is input to the
convolutional neural network, and the characteristics of the previous layer are extracted and classified; 4, according to the labels given in the step 2 and the characteristics extracted in the step 3, a multi-class
SVM classifier is trained; 5, after training, the prediction rates, for all types of failures, obtained through the
SVM classifier are obtained; and 6, detection and recognition are conducted. The elevator failure recognition method which is novel in angle, consistent to actual situation and high in accuracy is achieved, the requirement for hardware is low, and portability is high.