Quantitative Model and Application of Equipment Health State Data Based on Improved DBSCAN-GMM
The health status of equipments has an important impact on the production safety and pro-duction efficiency of modern industry.In order to accurately perceive the health status of equipment and real-ize the transition from qualitative analysis to quantitative analysis of equipment status,a density-based spa-tial clustering of applications with noise(DBSCAN)is proposed and combined with Gaussian mixture model(GMM),the former realizes the classification of data,and the latter realizes the modeling of data.A quantita-tive model of equipment health status data based on improved DBSCAN-GMM is established,and an exam-ple analysis is carried out with the historical operation data of rod mill equipment,which verifies the effec-tiveness of the model.
health status of equipmentsDBSCANGaussian mixture modeldata-aware mode
NETL
NSTL
万方数据
