Industrial equipment operation state monitoring data feature extraction and mining method

• Main Authors: XUE ZHIQING, XIAO XUE, CHEN SHIRU, QIN NIANBIN, SONG ZHIGANG
• Format: Patent
• Language: Chinese; English
• Published: 13.08.2024
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention belongs to the technical field of industrial internet equipment health management, and particularly relates to an industrial equipment operation state monitoring data feature extraction and mining method. The method comprises the following steps: S1, acquiring sensor monitoring data, and inputting the sensor monitoring data into a window function to obtain a window function output sequence; and S2, based on the window function output sequence, data features are extracted, and the data features comprise data statistical distribution features, density distribution features and time distribution features. The method can be applied to abnormal operation state recognition, fault classification, health assessment and the like of industrial equipment in the field of the Internet of Things, so as to solve the technical problems of complex computing power, high computing power cost and the like in the prior art. 本发明属于工业互联网设备健康管理的技术领域，更具体地，涉及一种工业设备运行状态监测数据特征提取与挖掘方法。所述方法包括：S1、获取传感器监测数据，将所述传感器监测数据输入窗函数，得到窗函