Research on Fault Warning for Small and Medium Sized Equipment Based on AdaBoost SVM

Abstract

With the establishment of modern enterprise production systems, enterprises attach more importance to the management of machinery and equipment. Using certain technologies to predict possible faults in machine production and repairing machinery and equipment in advance based on predictions is an important guarantee for the continuity of enterprise production and operation. The most common production equipment in oil and gas field exploitation is small and medium-sized rotating equipment. The normal operation of the equipment is conducive to ensuring the smooth implementation of oil and gas field production and is an important equipment foundation for ensuring stable production. With the establishment of the management system for production machinery and equipment in oil and gas fields, oil and gas field enterprises will monitor the data of small and medium-sized rotating equipment, collect operational data of small and medium-sized rotating equipment, and store it, providing a foundation for establishing machine learning methods to early warning of faults in small and medium-sized rotating equipment.