Engineering topics

Merrill, Walter C.

Publications and source records attributed to Merrill, Walter C..

At least 37 records · Page 2

NASA NTRS1990

A real time microcomputer implementation of sensor failure detection for turbofan engines

An algorithm was developed that detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm has been demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm, which resulted in the successful completion of the algorithm engine demonstration, is described.

Delaat, John C.↗

NASA NTRS1990

Neuromorphic learning of continuous-valued mappings from noise-corrupted data. Application to real-time adaptive control

The ability of feed-forward neural network architectures to learn continuous valued mappings in the presence of noise was demonstrated in relation to parameter identification and real-time adaptive control applications. An error function was introduced to help optimize parameter values such as number of training iterations, observation time, sampling rate, and scaling of the control signal. The learning performance depended essentially on the degree of embodiment of the control law in the training data set and on the degree of uniformity of the probability distribution function of the data that are presented to the net during sequence. When a control law was corrupted by noise, the fluctuations of the training data biased the probability distribution function of the training data sequence. Only if the noise contamination is minimized and the degree of embodiment of the control law is maximized, can a neural net develop a good representation of the mapping and be used as a neurocontroller. A multilayer net was trained with back-error-propagation to control a cart-pole system for linear and nonlinear control laws in the presence of data processing noise and measurement noise. The neurocontroller exhibited noise-filtering properties and was found to operate more smoothly than the teacher in the presence of measurement noise.

Troudet, Terry↗

NASA NTRS1990

Advanced detection, isolation, and accommodation of sensor failures in turbofan engines: Real-time microcomputer implementation

The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming.

Delaat, John C.↗

NASA NTRS1990

Sensor failure detection for jet engines

The use of analytical redundancy to improve gas turbine engine control system reliability through sensor failure detection, isolation, and accommodation is surveyed. Both the theoretical and application papers that form the technology base of turbine engine analytical redundancy research are discussed. Also, several important application efforts are reviewed. An assessment of the state-of-the-art in analytical redundancy technology is given.

Merrill, Walter C.↗

NASA NTRS1989

A real time microcomputer implementation of sensor failure detection for turbofan engines

An algorithm was developed which detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm was demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm which resulted in the successful completion of the algorithm engine demonstration, is described.

Delaat, John C.↗

NASA NTRS1989

A real-time simulator of a turbofan engine

A real-time digital simulator of a Pratt and Whitney F100 engine has been developed for real-time code verification and for actuator diagnosis during full-scale engine testing. This self-contained unit can operate in an open-loop stand-alone mode or as part of closed-loop control system. It can also be used for control system design and development. Tests conducted in conjunction with the NASA Advanced Detection, Isolation, and Accommodation program show that the simulator is a valuable tool for real-time code verification and as a real-time actuator simulator for actuator fault diagnosis. Although currently a small perturbation model, advances in microprocessor hardware should allow the simulator to evolve into a real-time, full-envelope, full engine simulation.

Litt, Jonathan S.↗

NASA NTRS1989

Identification of space shuttle main engine dynamics

System identification techniques are used to represent the dynamic behavior of the Space Shuttle Main Engine. The transfer function matrices of the linearized models of both the closed loop and the open loop system are obtained by using the recursive maximum likelihood method.

Duyar, Ahmet↗

NASA NTRS1989

Neuromorphic learning of continuous-valued mappings in the presence of noise: Application to real-time adaptive control

The ability of feed-forward neural net architectures to learn continuous-valued mappings in the presence of noise is demonstrated in relation to parameter identification and real-time adaptive control applications. Factors and parameters influencing the learning performance of such nets in the presence of noise are identified. Their effects are discussed through a computer simulation of the Back-Error-Propagation algorithm by taking the example of the cart-pole system controlled by a nonlinear control law. Adequate sampling of the state space is found to be essential for canceling the effect of the statistical fluctuations and allowing learning to take place.

Troudet, Terry↗

NASA NTRS1989

Identification of Space Shuttle Main Engine dynamics

Duyar, Ahmet↗

NASA NTRS1988

Advanced detection, isolation, and accommodation of sensor failures - Real-time evaluation

The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundancy to detect sensor failures. The results of a real-time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

Merrill, Walter C.↗

NASA NTRS1988

Sensor failure detection for jet engines

Merrill, Walter C.↗

NASA NTRS1988

A reusable rocket engine intelligen control

An intelligent control system for reusable space propulsion systems for future launch vehicles is described. The system description includes a framework for the design. The framework consists of an execution level with high-speed control and diagnostics, and a coordination level which marries expert system concepts with traditional control. A comparison is made between air breathing and rocket engine control concepts to assess the relative levels of development and to determine the applicability of air breathing control concepts to future reusable rocket engine systems.

Merrill, Walter C.↗

NASA NTRS1988

A reusable rocket engine intelligent control

Merrill, Walter C.↗

NASA NTRS1988

Sensor-Failure Simulator

Outputs of defective sensors simulated for studies of reliability of control systems. Real-time sensor-failure simulator (SFS) designed and built for use with Advance Detection, Isolation, and Accommodation (ADIA) program. Equipment consists of IBM PC/XT computer and associated analog circuitry. User defines failure scenarios to determine which sensor signals fail and method(s) used to simulate failure.

Melcher, Kevin J.↗

NASA NTRS1988

Engine-Monitoring Algorithm

Allowances made for erroneous sensor readings. Algorithm developed to increase reliability of digital electronic control systems for aircraft turbine engines. Detects, isolates, and accommodates failures or errors in engine sensors. Generates engine-output estimates based on measurements of inputs and outputs and detects failures of input- and output-measuring sensors.

Merrill, Walter C.↗

NASA NTRS1988

A microprocessor-based real-time simulator of a turbofan engine

A real-time digital simulator of a Pratt and Whitney F 100 engine is discussed. This self-contained unit can operate in an open-loop stand-alone mode or as part of a closed-loop control system. It can also be used in control system design and development. It accepts five analog control inputs and its sixteen outputs are returned as analog signals.

Litt, Jonathan S.↗

NASA NTRS1987

Advanced detection, isolation and accommodation of sensor failures: Real-time evaluation

The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundacy to detect sensor failures. The results of a real time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

Merrill, Walter C.↗

NASA NTRS1987

Full-scale engine demonstration of an advanced sensor failure detection, isolation and accommodation algorithm: Preliminary results

The objective of the advanced detection, isolation, and accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, algorithms were developed which detect, isolate, and accommodate sensor failures using analytical redundancy. Preliminary results of a full scale engine demonstration of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 turbofan engine control system are determined and compared to those obtained during a previous evaluation of this algorithm using a real-time hybrid computer simulation of the engine.

Merrill, Walter C.↗