Development of a condition monitoring system for compressor equipment with neural network data analysis

Currently, one of the most widely used and effective types of technological equipment is screw compressor equipment. Along with the fact, that such equipment has a number of advantages that determine its high efficiency, it is characterized by increased wear of important structural elements. This can lead to reduced compressor efficiencies and malfunctions that can result in emergencies. In this regard, the paper presents the results of developing a scheme for continuous monitoring of the technical condition of screw compressor units. Variants of installing vibration sensors that provide data collection of vibration diagnostics are determined. In order to automate the analysis of the collected data, it is proposed to use the method of data mining based on neural networks to recognize the technical condition. The results of testing the neural network data method of a real compressor unit are presented.