Design of Status Analysis System for Brick Machines Based on Industrial Internet of Things

Status analysis of machines is important for the factories to reduce the breakdown of machines and improve the quality of the products. Most existing solutions are limited to manual data collection and analysis, which has poor real-time performance and low data utilization. To solve this problem, this paper proposes a health status analysis for brick machines based on industrial internet of things. We firstly introduce the framework of industrial internet of things to obtain the operation data of brick machines. Then the data are analyzed to derive the features that presents the status of the brick machine. The preprocessed data are further evaluated based on the clustering algorithm. Based on the clustering results, the status of brick machines can be classified as shutdown, standby, abnormal, voltage loss and normal. The experimental results are provided to prove the effectiveness of the proposed system.