Development and application of Internet-based remote monitoring and diagnostic platform for key equipment

Requirements for high efficiency in manufacturing, while pushing the development of key equipment, need high-performance maintenance as a safeguard. Internet-related techniques are enabling remote monitoring and maintenance to extend beyond local areas. Considering the need for software architecture with openness and interchangeability for flexible selection and replacement of data analysis techniques, this research develops a standardized multi-layer platform using Web services, realizing data transmission among networks. The independence between the software platform and data analysis guarantees their research and development in parallel. Studies were done on nonlinear-data-analysis techniques, such as wavelet neural networks for fault diagnostics, particle filters for estimates, and support vector regression for condition prediction. These studies were included in a comprehensive application. The experimental results support condition-based maintenance for key equipment.