MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641106107 A) filed by Sri Eshwar College Of Engineering on September 03, 2026, for Digital Twin-Based Predictive Maintenance And Remote Condition Monitoring System For Industrial Steam Traps.
Inventors include Dr G Gokilakrishnan; Goforth Walker P; and Jeevan T.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention relates to a digital twin-based predictive maintenance and remote condition monitoring system for industrial steam traps, configured to continuously acquire operating information from a physical steam trap and maintain a corresponding virtual representation of its operating condition. The system comprises a physical steam trap monitoring arrangement having one or more operating-condition sensors, an ESP32-based data acquisition and processing module, a wireless communication arrangement, a cloud-based data platform, a digital twin module, an interactive monitoring dashboard, and an automated alert mechanism. The operating-condition sensors preferably comprise a temperature sensor and a vibration sensor positioned on or adjacent to the steam trap for continuously acquiring thermal and mechanical information associated with steam trap operation. The ESP32 receives the sensor measurements, processes the acquired information, and transmits the corresponding data through a wireless communication network to the cloud-based data platform, wherein the acquired information is stored and made remotely accessible for real-time monitoring and historical analysis. The digital twin module receives the transmitted operating information and continuously updates a virtual representation of the physical steam trap according to changes in the measured operating conditions. The interactive monitoring dashboard provides real-time visualization of the digital twin together with temperature, vibration, system status, parameter trends, and fault indications through graphical representations, indicators, and other visual monitoring elements. The system further comprises a condition-analysis arrangement configured to compare real-time sensor information with predefined or expected operating conditions and identify deviations associated with abnormal steam trap behavior. Abnormal vibration, abnormal temperature variation, sudden parameter changes, or deviations from expected operating conditions can thereby be identified as potential fault conditions, wherein the alert mechanism generates a corresponding notification to support early maintenance intervention. The cloud-based platform further enables storage of historical sensor information and visualization of operating trends over time, thereby supporting identification of recurring abnormalities, condition assessment, and predictive maintenance decision- making. By integrating real-time temperature and vibration sensing, ESP32-based processing, wireless communication, cloud data management, digital twin representation, remote visualization, historical trend analysis, condition comparison, and automated fault notification into a unified monitoring architecture, the invention provides continuous visibility of industrial steam trap operating conditions, enables early identification of abnormal behavior, reduces dependence on periodic manual inspection, supports remote predictive maintenance, and contributes to improved equipment reliability, reduced energy loss, and enhanced operational efficiency of industrial steam systems.
Disclaimer: Curated by HT Syndication.
