Abstract:In view of the current hardware equipment operation status monitoring system focus on the hardware index of the cluster, the monitoring of the data layer of the power equipment such as line, performance, node status and command feedback is insufficient. This paper uses the big data technology to significantly improve the operating status of the power equipment. Sexual and statistical factor variables are used for corresponding decision analysis to build a multivariate regression system model that actively monitors the potential operational state of the equipment. Thereby effectively solving the real-time monitoring of the operation process of the power equipment, potential failure warning, evaluation, back-track management and other issues. The test results of Ningxia Electric Power Company show that the model platform can expect to capture various influence variable factors under the operating state of power equipment. The control of these factors will be widely used in power equipment operation deployment and operation and maintenance. According to this conclusion, the power equipment operation status monitoring system of the big data platform can customize the equipment operation analysis report, realize the on-demand display of the data analysis result, and ensure the safe and reliable operation of the power equipment, which has certain promotion significance.