A Gas Turbine Health Monitoring (GTHM) system has been installed to monitor a fleet of compression equipment on a natural gas pipeline in China. The fleet consists of 22 General Electric PGT25+, 15 Rolls-Royce Coberra 6562, and 4 Siemens Variable Speed Drive (VSD) packages. Using the China pipeline project as an example, this paper describes the implementation of this unique Gas Turbine Health Management system. The GTHM system is an aftermarket solution that allows operators employing different makes, models and vintages of equipment to implement a PI System with customized gas turbine analysis tools. For the China project, a PI System data historian has been installed to archive the continuous analog signals representing temperatures, pressures, flows and other dynamic process parameters of a gas turbine, power turbine and driven centrifugal compressor. The ability to analyze the actual historical data—and not summarized, averaged or otherwise interpolated data—is crucial to gaining better insights into performance. The data collection network consists of systems and devices using several different protocols and methods of communication. The solution to resolving communication issues was to convert each protocol to OPC because the PI System supports a simple, robust OPC client interface. The value of the GTHM system lies primarily in the analysis of the data being collected. The Gas Turbine Analysis Program (GTAPTM) uses a physics-based engine model and the actual engine instrumentation data to calculate performance degradation. Trending of the performance degradation can assist the operator in scheduling condition based maintenance (CBM) activities, such as compressor washing. The component lifing model uses the hot section metal temperatures calculated by GTAPTM in conjunction with a damage accumulation model to calculate the equivalent operating hours (EOH) of the engine. EOH replaces the time based (hours and starts) method traditionally used for scheduling the removal of hot gas path components. This allows for the maximum service interval period leading to significant cost savings while ensuring components will still be repairable at time of overhaul. The focus of the user interface is analysis activities like status monitoring, trending and reporting. GTHM utilizes the PI Asset Framework, PI DataLink and PI Notifications in particular to provide functionality. The completed GTHM system is the tool for providing the operator up to the minute status, troubleshooting capabilities and true condition based maintenance leading to prolonged equipment life and substantial economic value.
From 1998-2006, John worked at Liburdi Automation Inc. as a Software Engineer. He Designed and developed control software for automated turbine component repair systems using multi-axis coordinated motion and machine vision. From 2006-present, he has worked at Liburdi Automation Inc. as a Senior Software Engineering Manager. He is responsible for the automated welding products software group. Chief architect of Liburdi's automated welding controllers. From 2001-2003, he was a Software Engineer and designed and developed Gas Turbine Analysis Program for the Web (webGTAP), a hosted Web service for power generation utilities that exchanges data with the historian and provides GTAP performance and degradation reports. He designed and developed Component Tracking and Management System (CTMS), an enterprise system for managing work flows in turbine repair and refurbishment operations and maintaining records of component repair history. From 2007-present, he has worked as a GTHM Program Manager, chief architect and program manager of the Liburdi GTHM system, a condition-based maintenance solution for gas turbine operators. John received a Bachelor's degree in Computer Engineering and Management from McMaster University in 1998.