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Through the SBIR program, Rochester, New York-based Impact Technologies LLC collaborated with Ames Research Center to commercialize the Center s Hybrid Diagnostic Engine, or HyDE, software. The fault detecting program is now incorporated into a software suite that identifies potential faults early in the design phase of systems ranging from printers to vehicles and robots, saving time and money.
The latest generation of long life, space pulse-tube cryocoolers require electronics capable of controlling self-induced vibration down to a fraction of a newton and coldhead temperature with high accuracy down to a few kelvin. Other functions include engineering diagnostics, heater and valve control, telemetry and safety protection of the cryocooler subsystem against extreme environments and operational anomalies. The electronics are designed to survive the thermal, vibration, shock and radiation environment of launch and orbit, while providing a design life in excess of 10 years on-orbit. A number of our current generation high reliability radiation-hardened electronics units are in various stages of integration on several space flight payloads. This paper describes the features and performance of our latest flight electronics designed for the pulse-tube cryocooler that is the pre-cooler for a closed cycle Joule-Thomson cooler providing 6K cooling for the James Webb Space Telescope (JWST) Mid Infra-Red Instrument (MIRI). The electronics is capable of highly accurate temperature control over the temperature range from 4K to 15K. Self-induced vibration is controlled to low levels on all harmonics up to the 16th. A unique active power filter controls peak-to-peak reflected ripple current on the primary power bus to a very low level. The 9 kg unit is capable of delivering 360W continuous power to NGAS's 3-stage pulse-tube High-Capacity Cryocooler (HCC).
The paper describes a turbofan-engine measurement program utilizing a variety of diagnostic techniques to identify a source of core-generated noise which contributes to the overall external engine noise characteristics. Included in the turbofan engine diagnostics are data examination, time domain correlation, and frequency domain analysis. It is found that the turbulent pressure fluctuations within the combustor are a source for core noise which propagates through the nozzle and radiates to the far-field.
A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.
A retrofit architecture for intelligent turbofan engine control and diagnostics that changes the fan speed command to maintain thrust is proposed and its demonstration in a piloted flight simulator is described. The objective of the implementation is to increase the level of autonomy of the propulsion system, thereby reducing pilot workload in the presence of anomalies and engine degradation due to wear. The main functions of the architecture are to diagnose the cause of changes in the engine s operation, warning the pilot if necessary, and to adjust the outer loop control reference signal in response to the changes. This requires that the retrofit control architecture contain the capability to determine the changed relationship between fan speed and thrust, and the intelligence to recognize the cause of the change in order to correct it or warn the pilot. The proposed retrofit architecture is able to determine the fan speed setting through recognition of the degradation level of the engine, and it is able to identify specific faults and warn the pilot. In the flight simulator it was demonstrated that when degradation is introduced into an engine with standard fan speed control, the pilot needs to take corrective action to maintain heading. Utilizing the intelligent retrofit control architecture, the engine thrust is automatically adjusted to its expected value, eliminating yaw without pilot intervention.
Recent technology reviews have identified the need for objective assessments of aircraft engine health management (EHM) technologies. To help address this issue, a gas path diagnostic benchmark problem has been created and made publicly available. This software tool, referred to as the Propulsion Diagnostic Method Evaluation Strategy (ProDiMES), has been constructed based on feedback provided by the aircraft EHM community. It provides a standard benchmark problem enabling users to develop, evaluate and compare diagnostic methods. This paper will present an overview of ProDiMES along with a description of four gas path diagnostic methods developed and applied to the problem. These methods, which include analytical and empirical diagnostic techniques, will be described and associated blind-test-case metric results will be presented and compared. Lessons learned along with recommendations for improving the public benchmarking processes will also be presented and discussed.
In-flight sensor fault detection and isolation (FDI) is critical to maintaining reliable engine operation during flight. The aircraft engine control system, which computes control commands on the basis of sensor measurements, operates the propulsion systems at the demanded conditions. Any undetected sensor faults, therefore, may cause the control system to drive the engine into an undesirable operating condition. It is critical to detect and isolate failed sensors as soon as possible so that such scenarios can be avoided. A challenging issue in developing reliable sensor FDI systems is to make them robust to changes in engine operating characteristics due to degradation with usage and other faults that can occur during flight. A sensor FDI system that cannot appropriately account for such scenarios may result in false alarms, missed detections, or misclassifications when such faults do occur. To address this issue, an enhanced bank of Kalman filters was developed, and its performance and robustness were demonstrated in a simulation environment. The bank of filters is composed of m + 1 Kalman filters, where m is the number of sensors being used by the control system and, thus, in need of monitoring. Each Kalman filter is designed on the basis of a unique fault hypothesis so that it will be able to maintain its performance if a particular fault scenario, hypothesized by that particular filter, takes place.
In this paper, an approach for in-flight fault detection and isolation (FDI) of aircraft engine sensors based on a bank of Kalman filters is developed. This approach utilizes multiple Kalman filters, each of which is designed based on a specific fault hypothesis. When the propulsion system experiences a fault, only one Kalman filter with the correct hypothesis is able to maintain the nominal estimation performance. Based on this knowledge, the isolation of faults is achieved. Since the propulsion system may experience component and actuator faults as well, a sensor FDI system must be robust in terms of avoiding misclassifications of any anomalies. The proposed approach utilizes a bank of (m+1) Kalman filters where m is the number of sensors being monitored. One Kalman filter is used for the detection of component and actuator faults while each of the other m filters detects a fault in a specific sensor. With this setup, the overall robustness of the sensor FDI system to anomalies is enhanced. Moreover, numerous component fault events can be accounted for by the FDI system. The sensor FDI system is applied to a commercial aircraft engine simulation, and its performance is evaluated at multiple power settings at a cruise operating point using various fault scenarios.
The current status of a rocket exhaust plume diagnostics program sponsored by NASA is reviewed. The near-term objective of the program is to enhance test operation efficiency and to provide for safe cutoff of rocket engines prior to incipient failure, thereby avoiding the destruction of the engine and the test complex and preventing delays in the national space program. NASA programs that will benefit from the nonintrusive remote sensed rocket plume diagnostics and related vehicle health management and nonintrusive measurement program are Space Shuttle Main Engine, National Launch System, National Aero-Space Plane, Space Exploration Initiative, Advanced Solid Rocket Motor, and Space Station Freedom. The role of emission spectrometry and other types of remote sensing in rocket plume diagnostics is discussed.
A description of an intelligent diagnostic system for the Space Shuttle Main Engines (SSME) is presented. This system is suitable for incorporation in an intelligent controller which implements accommodating closed-loop control to extend engine life and maximize available performance. The diagnostic system architecture is a modular, hierarchical, blackboard system which is particularly well suited for real-time implementation of a system which must be repeatedly updated and extended. The diagnostic problem is formulated as a hierarchical classification problem in which the failure hypotheses are represented in terms of predefined data patterns. The diagnostic expert system incorporates techniques for priority-based diagnostics, the combination of analytical and heuristic knowledge for diagnosis, integration of different AI systems, and the implementation of hierarchical distributed systems. A prototype reusable rocket engine diagnostic system (ReREDS) has been implemented. The prototype user interface and diagnostic performance using SSME test data are described.
In this paper, a uniquely structured Kalman filter is developed for its application to in-flight diagnostics of aircraft gas turbine engines. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the in-flight diagnostic system to be updated to the degraded health condition of the engines through a relatively simple process. Through this health baseline update, the effectiveness of the in-flight diagnostic algorithm can be maintained as the health of the engine degrades over time. Another significant aspect of the hybrid Kalman filter methodology is its capability to take advantage of conventional linear and nonlinear Kalman filter approaches. Based on the hybrid Kalman filter, an in-flight fault detection system is developed, and its diagnostic capability is evaluated in a simulation environment. Through the evaluation, the suitability of the hybrid Kalman filter technique for aircraft engine in-flight diagnostics is demonstrated.
The results of a conceptual design study on the feasibility of nonintrusive optical diagnostics have shown that UV laser-excited Raman scattering can furnish reliable and accurate temperature and multiple-species data for the Space Shuttle Main Engine's exhaust flow. Enhanced OH flow tagging by UV photodissociation of H2O was used in velocity measurements; a time-delayed pulsed dye laser beam at 308 nm excites fluorescence from OH, and the location of the convected enhanced OH zone is measured with an optical multichannel detector.
Abstract Core-collapse supernova explosions play a wide role in astrophysics by producing compact remnants (neutron stars or black holes) and the synthesis and injection of many heavy elements into their host galaxy. Because they are produced in some of the most extreme conditions in the universe, they can also probe physics in extreme conditions (matter at nuclear densities and extreme temperatures and magnetic fields). To quantify the impact of supernovae on both fundamental physics and our understanding of the universe, we must leverage a broad set of observables of this engine. In this paper, we study a subset of these probes using a suite of one-dimensional, parameterized mixing models: ejecta remnants from supernovae, ultraviolet, optical and infrared light curves, and transient gamma-ray emission. We review the other diagnostics and show how the different probes tie together to provide a more clear picture of the supernova engine. Join us in improving and evolving this document through active community engagement. Instructions are provided at this link: https://github.com/clfryer/MM-SNe .
This paper investigates the integration of on-line and off-line diagnostic algorithms for aircraft gas turbine engines. The on-line diagnostic algorithm is designed for in-flight fault detection. It continuously monitors engine outputs for anomalous signatures induced by faults. The off-line diagnostic algorithm is designed to track engine health degradation over the lifetime of an engine. It estimates engine health degradation periodically over the course of the engine s life. The estimate generated by the off-line algorithm is used to update the on-line algorithm. Through this integration, the on-line algorithm becomes aware of engine health degradation, and its effectiveness to detect faults can be maintained while the engine continues to degrade. The benefit of this integration is investigated in a simulation environment using a nonlinear engine model.
The application of vibroacoustic techniques for diagnosing aircraft engine malfunctions is discussed. An experiment was conducted to determine the defects introduced by the nature of change in the amplitude-frequency characteristics of the noises and vibrations of an aircraft jet engine. The manner in which the defects were simulated is explained. The test equipment used during the experiment is identified. The results of the amplitude-frequency characteristics investigation are summarized to show optimum location of the microphone pick-up to record the acoustic data.
An overview and progress report of the work performed or sponsored by LeRC toward the development of in-flight plume spectroscopy technology for health and performance monitoring of liquid propellant rocket engines are presented. The primary objective of this effort is to develop technology that can be utilized on any flight engine. This technology will be validated by a hardware demonstration of a system capable of being retrofitted onto the Space Shuttle Main Engines for spectroscopic measurements during flight. The philosophy on system definition and status on the development of instrumentation, optics, and signal processing with respect to implementation on a flight engine are discussed.
An overview and progress report of the work performed or sponsored by LeRC toward the development of in-flight plume spectroscopy technology for health and performance monitoring of liquid propellant rocket engines are presented. The primary objective of this effort is to develop technology that can be utilized on any flight engine. This technology will be validated by a hardware demonstration of a system capable of being retrofitted onto the Space Shuttle Main Engines for spectroscopic measurements during flight. The philosophy on system definition and status on the development of instrumentation, optics, and signal processing with respect to implementation on a flight engine are discussed.
Characteristics such as drop velocity, drop size, number density, volume flow rate, volume flux, and evaporation rate of the fuel spray in a rocket engine are directly related to engine performance. Several studies of shear coaxial atomization have been done in the past. However, additional work related to sprays at supercritical and transcritical conditions would be useful. The author undertook a study of the feasibility of using a phase Doppler particle analyzer (PDPA) for spray measurements in rocket engines as a part of the Summer Faculty Fellowship Program at the NASA Marshall Space Flight Center. The PDPA is a single particle counter (SPC) system based on light scattering from spherical particles. The PDPA instrument is based on refractive and reflective scattering as opposed to other instruments based on diffractive scattering. The main advantage of the PDPA instrument is its ability to provide point-wise information. The following sections describe the principle of operation of the PDPA system and the data obtained using a PDPA instrument in a spray formed by a commercially available fuel injection nozzle.