sensor

Predictive maintenance is a data-driven closed-loop system. Its core objective is to accurately predict equipment failures. Key components include four modules: data acquisition, transmission and processing, analysis and modeling, and decision execution. Efficient predictive maintenance requires the coordinated operation of each module. 1. Status Awareness Layer: Data Acquisition Module This module collects real-time physical status data of the equipment, forming the foundation of predictive maintenance. The core carriers are various industrial sensors. 2. Network Transmission Layer: Data Transmission and Edge Processing Module This module securely and in real-time transmits the collected raw data to the analysis platform and performs preliminary screening to reduce cloud computing load. 3. Intelligent Analysis Layer: Data Storage and Modeling Analysis Module This module is the core decision-making unit for predictive maintenance. Through analysis of historical and real-time data, it ...