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At least 271 records · Page 15

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NASA NTRS2005

Attitude Control System Design for the Solar Dynamics Observatory

The Solar Dynamics Observatory mission, part of the Living With a Star program, will place a geosynchronous satellite in orbit to observe the Sun and relay data to a dedicated ground station at all times. SDO remains Sun- pointing throughout most of its mission for the instruments to take measurements of the Sun. The SDO attitude control system is a single-fault tolerant design. Its fully redundant attitude sensor complement includes 16 coarse Sun sensors, a digital Sun sensor, 3 two-axis inertial reference units, 2 star trackers, and 4 guide telescopes. Attitude actuation is performed using 4 reaction wheels and 8 thrusters, and a single main engine nominally provides velocity-change thrust. The attitude control software has five nominal control modes-3 wheel-based modes and 2 thruster-based modes. A wheel-based Safehold running in the attitude control electronics box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. The paper details the mode designs and their uses.

Starin, Scott R.↗

NASA NTRS2018

Self Diagnostic Accelerometer Field Programmable Gate Array (SDA FPGA)

A self-diagnostic accelerometer (SDA) field programmable gate array (FPGA) may be capable of real time or near-real time diagnostic processing to determine potential accelerometer issues during flight or other mission critical operational situations. The SDA FPGA may determine accelerometer structural health and an attachment condition using an electronics system that is smaller, more energy efficient, and more cost effective than previous diagnostic tools. Advantages of the system may include diagnosing sensors automatically, immediately, actively (i.e., confirming the fault), and consistently, without the influence of a human operator. Customizable SDA algorithms may be adjusted to the specific needs of the sensor/environment.

Tokars, Roger P.↗

DOE OSTI2024

PIP-II Beam Current Monitor Fault Case & Beam Position Monitor Linearity Studies in CST Studio

The use of non-invasive sensors & systems to measure particle beam characteristics is a crucial part of modern accelerator control systems. As such, simulations predicting the behavior of these sensors are essential for guiding beamline control system design. This poster details the results returned by two beam sensor models created using CST Studio software: the signal linearity of an elliptical beam position monitor (BPM), and the fault cases of an AC current transformer (ACCT) beam current monitor (BCM).

Rouzky, Adam↗

NASA NTRS1992

Real-time diagnostics for a reusable rocket engine

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.

Guo, T. H.↗

DOE OSTI2021

Modelica-based system modeling for studying control-related faults in chiller plants and boiler plants serving large office buildings

System modeling is critical when studying operation faults in chiller plants and boiler plants. However, current fault models have difficulties faithfully representing the operation of chiller plants and boiler plants under the effects of those faults, especially the control-related ones. In this study, we present a systematic method to develop high-fidelity models for approximating the behaviors of chiller plants and boiler plants under faulty conditions. Compared to existing ones, the resulting fault models have two advantages: first, they better characterize the dynamic patterns in the system operation. In those models, control architecture and control logic are faithfully implemented. Thus, they can be used to study control-related faults, such as incorrect staging control due to sensor bias and mistuned feedback control. Second, they are readily extensible and can support large-scale investigations to explore different faulty conditions/scenarios. Those models are established in a hierarchical structure while modules in each layer can be redeclared and parameterized at upper layers. In such a case, modifications to the models can be realized through model modifiers and the process can be easily streamlined with scripts. We applied the proposed models in a comprehensive fault impact evaluation of the 13 control-related faults of chiller and boiler plants. In this evaluation, the proposed plant model is coupled with the EnergyPlus thermal load model to study the impact of various faulty scenarios. Based on the evaluation results, we identified the faults that have the most significant impacts on the operation of the chiller and boiler plants, respectively. We also found that the relationship between the impacts of the studied faults and the severity level of the faults are highly non-linear

Huang, Sen↗

NASA NTRSDate not supplied

Enhancing Fault Isolation for Health Monitoring of Electric Aircraft Propulsion by Embedding Failure Mode and Effect Analysis into Bayesian Networks

This paper describes a fault isolation approach for electric powertrains of unmanned aerial vehicles. The approach leverages the combination of failure mode and effect analysis (FMEA) and Bayesian networks, thus introducing depend-ability structures into a diagnostic framework. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. This framework helps the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. The framework is applied to an electric power-train system of a small, rotary-wing unmanned aerial vehicle, demonstrating how a Bayesian network enhanced by FMEA helps disambiguate between root causes of incipient failures, which would otherwise be considered as equally probable.

Fault Isolation↗

NASA NTRS1999

Partitioning in Avionics Architectures: Requirements, Mechanisms, and Assurance

Automated aircraft control has traditionally been divided into distinct "functions" that are implemented separately (e.g., autopilot, autothrottle, flight management); each function has its own fault-tolerant computer system, and dependencies among different functions are generally limited to the exchange of sensor and control data. A by-product of this "federated" architecture is that faults are strongly contained within the computer system of the function where they occur and cannot readily propagate to affect the operation of other functions. More modern avionics architectures contemplate supporting multiple functions on a single, shared, fault-tolerant computer system where natural fault containment boundaries are less sharply defined. Partitioning uses appropriate hardware and software mechanisms to restore strong fault containment to such integrated architectures. This report examines the requirements for partitioning, mechanisms for their realization, and issues in providing assurance for partitioning. Because partitioning shares some concerns with computer security, security models are reviewed and compared with the concerns of partitioning.

Rushby, John↗

DOE OSTI2022

A Hybrid DC Fault Primary Protection Algorithm for Multi-Terminal HVdc Systems

Protection against dc faults is one of the main technical hurdles faced when operating converter-based HVdc systems. Protection becomes even more challenging for multi-terminal dc (MTdc) systems with more than two terminals/converter stations. In this paper, a hybrid primary fault detection algorithm for MTdc systems is proposed to detect a broad range of failures. Sensor measurements, i.e., line currents and dc reactor voltages measured at local terminals, are first processed by a top-level context clustering algorithm. For each cluster, the best fault detector is selected among a detector pool according to a rule resulting from a learning algorithm. The detector pool consists of several existing detection algorithms, each performing differently across fault scenarios. The proposed hybrid primary detection algorithm: i) offers superior performance compared to an individual detector through a data-driven approach; ii) detects all major fault types including pole-to-pole (P2P), pole-to-ground (P2G), and external dc faults; iii) identifies faults with various fault locations and impedances; iv) is more robust to noisy sensor measurements compared to existing methods; v) does not require exhaustive simulation and sampling for training the model. Performance and effectiveness of the proposed algorithm are evaluated and verified based on time-domain simulations in the PSCAD/EMTDC software environment. The results confirm satisfactory operation, accuracy, and detection speed of the proposed algorithm under various fault scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗

NASA NTRS1975

A study of the use of vibration and stress wave sensing for the detection of bearing failure

Results from an experimental study of vibrations and stress waves emitted from ball bearings are presented. Fatique tests were run with both high quality bearings and man faulted bearings, all of one size. Tests were instrumented with different sensors to detect the noises from 10 Hz to 1 MHz. Frequency spectrum plots are presented. The modulation characteristics of the ultrasonic noises were analyzed, and acoustic emission type measurements were conducted. Results are presented which show that there are usable acoustic signal levels even beyond 500 KHz. These signal levels are modulated by a low frequency carrier which is a function of the stress loading and acoustic transmissibility. The results were correlated to fault size in the bearings. The correlation shows that the sensor used for signals from 100 KHz to 1 MHz gave the best sensitivity and detected the generation of very small spalls or pits.

Ensor, L. C.↗

NASA NTRS1975

Design and test status for life support applications of SPE oxygen generation systems

An advanced six-man rated oxygen generation system has been fabricated and tested as part of a NASA/JSC technology development program for a long lived, manned spacecraft life support system. Details of the design and tests results are presented. The system is based on the Solid Polymer Electrolyte (SPE) water electrolysis technology and its nominal operating conditions are 2760 kN/sq m (400 psia) and 355 K (180 F) with an electrolysis module current density capability up to 350 mA/sq cm (326 ASF). The system is centered on a 13-cell SPE water electrolysis module having a single cell active area of 214 sq cm (33 sq in) and it incorporates instrumentation and controls for single pushbutton automatic startup/shutdown, component fault detection and isolation, and self-contained sensors and controls for automatic safe emergency shutdown. The system has been tested in both the orbital cyclic and continuous mode of operation. Various parametric tests have been completed to define the system capability for potential application in spacecraft environmental systems.

Titterington, W. A.↗

NASA NTRS1984

Using Ada for a distributed, fault tolerant system

It is pointed out that advanced avionics applications increasingly require underlying machine architectures which are damage and fault tolerant, and which provide access to distributed sensors, effectors and high-throughput computational resources. The Advanced Information Processing System (AIPS), sponsored by NASA, is to provide an architecture which can meet the considered requirements. Ada was selected for implementing the AIPS system software. Advantages of Ada are related to its provisions for real-time programming, error detection, modularity and separate compilation, and standardization and portability. Chief drawbacks of this language are currently limited availability and maturity of language implementations, and limited experience in applying the language to real-time applications. The present investigation is concerned with current plans for employing Ada in the design of the software for AIPS. Attention is given to an overview of AIPS, AIPS software services, and representative design issues in each of four major software categories.

Dewolf, J. B.↗

NASA NTRS1992

Power system monitoring and source control of the Space Station Freedom DC power system testbed

Unlike a terrestrial electric utility which can purchase power from a neighboring utility, the Space Station Freedom (SSF) has strictly limited energy resources; as a result, source control, system monitoring, system protection, and load management are essential to the safe and efficient operation of the SSF Electric Power System (EPS). These functions are being evaluated in the DC Power Management and Distribution (PMAD) Testbed which NASA LeRC has developed at the Power System Facility (PSF) located in Cleveland, Ohio. The testbed is an ideal platform to develop, integrate, and verify power system monitoring and control algorithms. State Estimation (SE) is a monitoring tool used extensively in terrestrial electric utilities to ensure safe power system operation. It uses redundant system information to calculate the actual state of the EPS, to isolate faulty sensors, to determine source operating points, to verify faults detected by subsidiary controllers, and to identify high impedance faults. Source control and monitoring safeguard the power generation and storage subsystems and ensure that the power system operates within safe limits while satisfying user demands with minimal interruptions. System monitoring functions, in coordination with hardware implemented schemes, provide for a complete fault protection system. The objective of this paper is to overview the development and integration of the state estimator and the source control algorithms.

Kimnach, Greg L.↗

NASA NTRS1992

Power system monitoring and source control of the Space Station Freedom dc-power system testbed

Unlike a terrestrial electric utility which can purchase power from a neighboring utility, the Space Station Freedom (SSF) has strictly limited energy resources; as a result, source control, system monitoring, system protection, and load management are essential to the safe and efficient operation of the SSF Electric Power System (EPS). These functions are being evaluated in the dc Power Management and Distribution (PMAD) Testbed which NASA LeRC has developed at the Power System Facility (PSF) located in Cleveland, Ohio. The testbed is an ideal platform to develop, integrate, and verify power system monitoring and control algorithms. State Estimation (SE) is a monitoring tool used extensively in terrestrial electric utilities to ensure safe power system operation. It uses redundant system information to calculate the actual state of the EPS, to isolate faulty sensors, to determine source operating points, to verify faults detected by subsidiary controllers, and to identify high impedance faults. Source control and monitoring safeguard the power generation and storage subsystems and ensure that the power system operates within safe limits while satisfying user demands with minimal interruptions. System monitoring functions, in coordination with hardware implemented schemes, provide for a complete fault protection system. The objective of this paper is to overview the development and integration of the state estimator and the source control algorithms.

Kimnach, Greg L.↗

NASA NTRS2010

Self-Validating Thermocouple

Self-Validating Thermocouple (SVT) Systems capable of detecting sensor probe open circuits, short circuits, and unnoticeable faults such as a probe debonding and probe degradation are useful in the measurement of temperatures. SVT Systems provide such capabilities by incorporating a heating or excitation element into the measuring junction of the thermocouple. By heating the measuring junction and observing the decay time for the detected DC voltage signal, it is possible to indicate whether the thermocouple is bonded or debonded. A change in the thermal transfer function of the thermocouple system causes a change in the rise and decay times of the thermocouple output. Incorporation of the excitation element does not interfere with normal thermocouple operation, thus further allowing traditional validation procedures as well.

Perotti, Jose M.↗

NASA NTRS1990

Fiber optic systems for mobile platforms III; Proceedings of the Meeting, Boston, MA, Sept. 7, 8, 1989

Various papers on fiber optic systems for mobile platforms are presented. Individual topics addressed include: architecture for fiber optic sensors and actuators in aircraft propulsion systems, fiber optic sensor system readiness for aircraft, microphone headset compatible with power by light, wavelength-division-multiplexed fiber optic sensors for aircraft applications, development of fly-by-light systems, fiber-optic-based inertial measurement unit, fault-tolerant architecture for a fly-by-light flight control computer, optically powered sensors for EMI-immune aviation sensing systems, infrared fiber optic fire sensors for space station applications. Papers on shipboard and automotive applications of fiber optic systems are also included.

Lewis, Norris E.↗

DOE OSTI2021

Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) for Monitoring and Control of Medium Voltage Distribution Systems with High Penetration of Intermittent Distributed Energy Resources

The primary focus of the SIMPLE project was to develop, commission, test and introduce intelligent voltage and current sensor platform with enhanced characteristics (accuracy, bandwidth and harmonic range) and high measurement granularity for medium voltage distribution system monitoring, protection and control. The enhancements incorporated existing (commercially available) sensors and made them suitable for applications such as voltage regulation, frequency support, fault detection and location, distribution system state estimation, power quality measurements and electrical distribution network topology processing. The development of the intelligent sensor platform was driven by the need for high-fidelity monitoring and control of medium voltage distribution feeder to enable higher penetration of renewable resources and microgrid operation.

14 SOLAR ENERGY↗

NASA NTRS2007

Hybrid Automated Diagnosis of Discrete/Continuous Systems

A recently conceived method of automated diagnosis of a complex electromechanical system affords a complete set of capabilities for hybrid diagnosis in the case in which the state of the electromechanical system is characterized by both continuous and discrete values (as represented by analog and digital signals, respectively). The method is an integration of two complementary diagnostic systems: (1) beacon-based exception analysis for multi-missions (BEAM), which is primarily useful in the continuous domain and easily performs diagnoses in the presence of transients; and (2) Livingstone, which is primarily useful in the discrete domain and is typically restricted to quasi-steady conditions. BEAM has been described in several prior NASA Tech Briefs articles: "Software for Autonomous Diagnosis of Complex Systems" (NPO-20803), Vol. 26, No. 3 (March 2002), page 33; "Beacon-Based Exception Analysis for Multimissions" (NPO-20827), Vol. 26, No. 9 (September 2002), page 32; "Wavelet-Based Real-Time Diagnosis of Complex Systems" (NPO-20830), Vol. 27, No. 1 (January 2003), page 67; and "Integrated Formulation of Beacon-Based Exception Analysis for Multimissions" (NPO-21126), Vol. 27, No. 3 (March 2003), page 74. Briefly, BEAM is a complete data-analysis method, implemented in software, for real-time or off-line detection and characterization of faults. The basic premise of BEAM is to characterize a system from all available observations and train the characterization with respect to normal phases of operation. The observations are primarily continuous in nature. BEAM isolates anomalies by analyzing the deviations from nominal for each phase of operation. Livingstone is a model-based reasoner that uses a model of a system, controller commands, and sensor observations to track the system s state, and detect and diagnose faults. Livingstone models a system within the discrete domain. Therefore, continuous sensor readings, as well as time, must be discretized. To reason about continuous systems, Livingstone uses monitors that discretize the sensor readings using trending and thresholding techniques. In development of the a hybrid method, BEAM results were sent to Livingstone to serve as an independent source of evidence that is in addition to the evidence gathered by Livingstone standard monitors. The figure depicts the flow of data in an early version of a hybrid system dedicated to diagnosing a simulated electromechanical system. In effect, BEAM served as a "smart" monitor for Livingstone. BEAM read the simulation data, processed the data to form observations, and stored the observations in a file. A monitor stub synchronized the events recorded by BEAM with the output of the Livingstone standard monitors according to time tags. This information was fed to a real-time interface, which buffered and fed the information to Livingstone, and requested diagnoses at the appropriate times. In a test, the hybrid system was found to correctly identify a failed component in an electromechanical system for which neither BEAM nor Livingstone alone yielded the correct diagnosis.

Park, Han↗