Abstract: In response to the health monitoring needs of hydraulic components of railway large-scale maintenance machinery, this paper designed and developed a big data platform for hydraulic health monitoring of railway large-scale maintenance machinery. The paper adopted a development approach of front-end and back-end separation, relied on technologies such as big data, Internet of Things, and cloud computing to implement real-time display of working conditions, data storage, health analysis, and dynamic monitoring and warning of large-scale railway maintenance machinery. The application shows that this platform can provide decision-making basis for quality management, condition repair, and other aspects of railway hydraulic components, and has a promoting effect on the intelligent development of railway maintenance machinery.