The system of monitoring and classification of vibration measurements of rotary equipment using deep neural network

The article discusses a system for processing and monitoring diagnostic information using deep neural networks. Collection and preliminary analysis using control sensors and the method of analyzing vibration signals with the preparation of a training sample. Presentation of information in the form of an indicative space for the classification of malfunctions of rotary equipment. It also provides for the introduction of a developed neural network classifier for recognizing defects in technical equipment.

vibration diagnostics, monitoring and classification system, training sample, machine learning, deep neural networks, neural network classifier, Technical equipment, processing and analysis of diagnostic information, expert system, IoT.