https://research.birmingham.ac.uk/portal/files/53643809/APEN2017.pdf

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Engine diagnostic practices are as old as the gas turbine itself. Monitoring and analysis methods have progressed in sophistication over the past 6 decades as the gas turbine evolved in form and complexity. While much of what will be presented here may equally apply to both stationary power plants and aero-engines, the emphasis will be on aero propulsion.Beginning with primarily empirical methods centering around monitoring the mechanical integrity of the machine, the evolution of engine diagnostics has benefited from advances in sensing, electronic monitoring devices, increased fidelity in engine modeling and analytical methods. The primary motivation in this development is, not surprisingly, cost. The ever increasing cost of fuel, engine prices, spare parts, maintenance and overhaul, all contribute to the cost of an engine over its entire life cycle. Diagnostics can be viewed as a means to mitigate risk in decisions that impact operational integrity. This can have a profound impact on safety, such as In-Flight Shut Downs (IFSD) for aero applications, (outages for land based applications) and economic impact caused by Unscheduled Engine Removals (UERs), part life, maintenance and overhaul and the overall logistics of maintaining an aircraft fleet or power generation plants.This paper will review some of the methods used in the preceding decades to address these issues, their evolution to current practices and some future trends. While several different monitoring and diagnostic systems will be addressed, the emphasis in this paper will be centered on those dealing with the aero-thermodynamic performance of the engine.© 2013 ASME

Gas Turbine Engine Health Management: Past, Present and Future Trends

Gas turbine diagnostics has a history almost as long as gas turbine development itself. Early engine fault diagnosis was carried out based on manufacturer information supplied in a technica...

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Performance-analysis-based gas turbine diagnostics: A review:

The goal of gas turbine performance diagnositcs is to accurately detect, isolate, and assess the changes in engine module performance, engine system malfunctions and instrumentation problems from knowledge of measured parameters taken along the engine’s gas path. The method has been applied to a wide variety of commercial and military engines in the three decades since its inception as a diagnostic tool and has enjoyed a reasonable degree of success. During that time many methodologies and implementations of the basic concept have been investigated ranging from the statistically based methods to those employing elements from the field of artificial intelligence. The two most publicized methods involve the use of either Kalman filters or artificial neural networks (ANN) as the primary vehicle for the fault isolation process. The present paper makes a comparison of these two techniques. @DOI: 10.1115/1.1419016#

The Use of Kalman Filter and Neural Network Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study

Intelligent Control and Health Management technology for aircraft propulsion systems is much more developed in the laboratory than in practice. With a renewed emphasis on reducing engine life cycle costs, improving fuel efficiency, increasing durability and life, etc., driven by various government programs, there is a strong push to move these technologies out of the laboratory and onto the engine. This paper describes the existing state of engine control and on-board health management, and surveys some specific technologies under development that will enable an aircraft propulsion system to operate in an intelligent way--defined as self-diagnostic, self-prognostic, self-optimizing, and mission adaptable. These technologies offer the potential for creating extremely safe, highly reliable systems. The technologies will help to enable a level of performance that far exceeds that of today s propulsion systems in terms of reduction of harmful emissions, maximization of fuel efficiency, and minimization of noise, while improving system affordability and safety. Technologies that are discussed include various aspects of propulsion control, diagnostics, prognostics, and their integration. The paper focuses on the improvements that can be achieved through innovative software and algorithms. It concentrates on those areas that do not require significant advances in sensors and actuators to make them achievable, while acknowledging the additional benefit that can be realized when those technologies become available. The paper also discusses issues associated with the introduction of some of the technologies.

/pdf/a-survey-of-intelligent-control-and-health-management-3nnpk1vi58.pdf

L. A. Urban

Papers

Parameter Selection for Multiple Fault Diagnostics of Gas Turbine Engines