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Combustion instabilities in gas turbine engines are most frequently encountered during the late phases of engine development, at which point they are difficult and expensive to fix. The ability to replicate an engine-traceable combustion instability in a laboratory-scale experiment offers the opportunity to economically diagnose the problem more completely (to determine the root cause), and to investigate solutions to the problem, such as active control. The development and validation of active combustion instability control requires that the casual dynamic processes be reproduced in experimental test facilities which can be used as a test bed for control system evaluation. This paper discusses the process through which a laboratory-scale experiment and be designed to replicate an instability observed in a developmental engine. The scaling process used physically-based analyses to preserve the relevant geometric, acoustic, and thermo-fluid features, ensuring that results achieved in the single-nozzle experiment will be scalable to the engine.

Combustion instabilities in gas turbine engines are most frequently encountered during the late phases of engine development, at which point they are difficult and expensive to fix. The ability to replicate an engine-traceable combustion instability in a laboratory-scale experiment offers the opportunity to economically diagnose the problem (to determine the root cause), and to investigate solutions to the problem, such as active control. The development and validation of active combustion instability control requires that the causal dynamic processes be reproduced in experimental test facilities which can be used as a test bed for control system evaluation. This paper discusses the process through which a laboratory-scale experiment was designed to replicate an instability observed in a developmental engine. The scaling process used physically-based analyses to preserve the relevant geometric, acoustic and thermo-fluid features. The process increases the probability that results achieved in the single-nozzle experiment will be scalable to the engine.

Combustion instabilities can lead to increased development time and cost for aeroengine gas turbines. This problem has been evident in the development of very-low emissions stationary gas turbines, and will likely be encountered in the newer, more aggressive aeroengine designs. In order to minimize development time and cost, it is imperative that potential combustion dynamics issues be resolved using analyses and smaller-scale experimentation. This paper discusses a methodology through which a problem in a full-scale engine was replicated in a single-nozzle laboratory combustor. Specifically, this approach is valid for longitudinal and "bulk" mode combustion instabilities. An explanation and partial validation of the acoustic analyses that were used to achieve this replication are also included. This approach yields a testbed for the diagnosis of combustion dynamics problems and for their solution through passive and active control techniques.

An advanced sensor failure detection, isolation, and accommodation (ADIA) algorithm has been developed for use with an aircraft turbofan engine control system. In a previous paper the authors described the ADIA algorithm and its real-time implementation. Subsequent improvements made to the algorithm and implementation are discussed, and the results of an evaluation presented. The evaluation used a real-time, hybrid computer simulation of an F100 turbofan engine.

A real-time Sensor Failure Simulator (SFS) was designed and assembled for the Advanced Detection, Isolation, and Accommodation (ADIA) program. Various designs were considered. The design chosen features an IBM-PC/XT. The PC is used to drive analog circuitry for simulating sensor failures in real-time. A user defined scenario describes the failure simulation for each of the five incoming sensor signals. Capabilities exist for editing, saving, and retrieving the failure scenarios. The SFS has been tested closed-loop with the Controls Interface and Monitoring (CIM) unit, the ADIA control, and a real-time F100 hybrid simulation. From a productivity viewpoint, the menu driven user interface has proven to be efficient and easy to use. From a real-time viewpoint, the software controlling the simulation loop executes at greater than 100 cycles/sec.

An advanced, sensor failure detection, isolation, and accomodation algorithm has been developed by NASA for the F100 turbofan engine. The algorithm takes advantage of the analytical redundancy of the sensors to improve the reliability of the sensor set. The method requires the controls computer, to determine when a sensor failure has occurred without the help of redundant hardware sensors in the control system. The controls computer provides an estimate of the correct value of the output of the failed sensor. The algorithm has been programmed in FORTRAN using a real-time microprocessor-based controls computer. A detailed description of the algorithm and its implementation on a microprocessor is given.

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation. Previously announced in STAR as N84-13140

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.

High speed minicomputers were used in the past to implement advanced digital control algorithms for turbine engines. These minicomputers are typically large and expensive. It is desirable for a number of reasons to use microprocessor-based systems for future controls research. They are relatively compact, inexpensive, and are representative of the hardware that would be used for actual engine-mounted controls. The Control, Interface, and Monitoring Unit (CIM) contains a microprocessor-based controls computer, necessary interface hardware and a system to monitor while it is running an engine. It is presently being used to evaluate an advanced turbofan engine control algorithm.

A logarithmic current-measuring instrument was developed to measure plasma coupling currents at a common mode voltage of 5 kilovolts. Positive or negative currents can be measured from 10 to the -9th power to .001 ampere direct current. Optical isolation is used to control input switching and to provide data referenced to ground potential. Analog meter readouts as well as zero to five volt outputs are provided for peripheral data collection. Six independent channels are provided. Three measure positive currents, and three measure negative currents. Although designed for vacuum operation, it can be used equally well in air to measure low currents at high common mode voltages.