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At least 397 records · Page 22

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NASA NTRS1994

A PC based time domain reflectometer for space station cable fault isolation

Significant problems are faced by astronauts on orbit in the Space Station when trying to locate electrical faults in multi-segment avionics and communication cables. These problems necessitate the development of an automated portable device that will detect and locate cable faults using the pulse-echo technique known as Time Domain Reflectometry. A breadboard time domain reflectometer (TDR) circuit board was designed and developed at the NASA-JSC. The TDR board works in conjunction with a GRiD lap-top computer to automate the fault detection and isolation process. A software program was written to automatically display the nature and location of any possible faults. The breadboard system can isolate open circuit and short circuit faults within two feet in a typical space station cable configuration. Follow-on efforts planned for 1994 will produce a compact, portable prototype Space Station TDR capable of automated switching in multi-conductor cables for high fidelity evaluation. This device has many possible commercial applications, including commercial and military aircraft avionics, cable TV, telephone, communication, information and computer network systems. This paper describes the principle of time domain reflectometry and the methodology for on-orbit avionics utility distribution system repair, utilizing the newly developed device called the Space Station Time Domain Reflectometer (SSTDR).

Pham, Michael↗

NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗

NASA NTRS1996

Unsupervised Pattern Classifier for Abnormality-Scaling of Vibration Features for Helicopter Gearbox Fault Diagnosis

A new unsupervised pattern classifier is introduced for on-line detection of abnormality in features of vibration that are used for fault diagnosis of helicopter gearboxes. This classifier compares vibration features with their respective normal values and assigns them a value in (0, 1) to reflect their degree of abnormality. Therefore, the salient feature of this classifier is that it does not require feature values associated with faulty cases to identify abnormality. In order to cope with noise and changes in the operating conditions, an adaptation algorithm is incorporated that continually updates the normal values of the features. The proposed classifier is tested using experimental vibration features obtained from an OH-58A main rotor gearbox. The overall performance of this classifier is then evaluated by integrating the abnormality-scaled features for detection of faults. The fault detection results indicate that the performance of this classifier is comparable to the leading unsupervised neural networks: Kohonen's Feature Mapping and Adaptive Resonance Theory (AR72). This is significant considering that the independence of this classifier from fault-related features makes it uniquely suited to abnormality-scaling of vibration features for fault diagnosis.

Jammu, Vinay B.↗

NASA NTRS1998

An Analysis of Failure Handling in Chameleon, A Framework for Supporting Cost-Effective Fault Tolerant Services

The desire for low-cost reliable computing is increasing. Most current fault tolerant computing solutions are not very flexible, i.e., they cannot adapt to reliability requirements of newly emerging applications in business, commerce, and manufacturing. It is important that users have a flexible, reliable platform to support both critical and noncritical applications. Chameleon, under development at the Center for Reliable and High-Performance Computing at the University of Illinois, is a software framework. for supporting cost-effective adaptable networked fault tolerant service. This thesis details a simulation of fault injection, detection, and recovery in Chameleon. The simulation was written in C++ using the DEPEND simulation library. The results obtained from the simulation included the amount of overhead incurred by the fault detection and recovery mechanisms supported by Chameleon. In addition, information about fault scenarios from which Chameleon cannot recover was gained. The results of the simulation showed that both critical and noncritical applications can be executed in the Chameleon environment with a fairly small amount of overhead. No single point of failure from which Chameleon could not recover was found. Chameleon was also found to be capable of recovering from several multiple failure scenarios.

Haakensen, Erik Edward↗

NASA NTRS1997

Multiple Fault Isolation in Redundant Systems

Fault diagnosis in large-scale systems that are products of modern technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption.

Pattipati, Krishna R.↗

NASA NTRS1997

Multiple Fault Isolation in Redundant Systems

Fault diagnosis in large-scale systems that are products of modem technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption.

Pattipati, Krishna R.↗

NASA NTRS2001

Thermal Fault Tolerance Analysis of Carbon Fiber Rope Barrier Systems for Use in the Reusable Solid Rocket Motor ( RSRM) Nozzle Joints

Carbon Fiber Rope (CFR) thermal barrier systems are being considered for use in several RSRM (Reusable Solid Rocket Motor) nozzle joints as a replacement for the current assembly gap close-out process/design. This study provides for development and test verification of analysis methods used for flow-thermal modeling of a CFR thermal barrier subject to fault conditions such as rope combustion gas blow-by and CFR splice failure. Global model development is based on a 1-D (one dimensional) transient volume filling approach where the flow conditions are calculated as a function of internal 'pipe' and porous media 'Darcy' flow correlations. Combustion gas flow rates are calculated for the CFR on a per-linear inch basis and solved simultaneously with a detailed thermal-gas dynamic model of a local region of gas blow by (or splice fault). Effects of gas compressibility, friction and heat transfer are accounted for the model. Computational Fluid Dynamic (CFD) solutions of the fault regions are used to characterize the local flow field, quantify the amount of free jet spreading and assist in the determination of impingement film coefficients on the nozzle housings. Gas to wall heat transfer is simulated by a large thermal finite element grid of the local structure. The employed numerical technique loosely couples the FE (Finite Element) solution with the gas dynamics solution of the faulted region. All free constants that appear in the governing equations are calibrated by hot fire sub-scale test. The calibrated model is used to make flight predictions using motor aft end environments and timelines. Model results indicate that CFR barrier systems provide a near 'vented joint' style of pressurization. Hypothetical fault conditions considered in this study (blow by, splice defect) are relatively benign in terms of overall heating to nozzle metal housing structures.

Clayton, J. Louie↗

NASA NTRS2002

Classification of Aircraft Maneuvers for Fault Detection

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data is a reasonable match to known examples of proper operation. In our domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. We explain where this subsystem fits into our envisioned fault detection system as well its experiments showing the promise of this classification subsystem.

Oza, Nikunj C.↗

NASA NTRS2002

Classification of Aircraft Maneuvers for Fault Detection

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Oza, Nikunj↗

NASA NTRS2003

Maneuver Classification for Aircraft Fault Detection

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, identifying all possible faulty and proper operating modes is clearly impossible. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Oza, Nikunj C.↗

NASA NTRS2003

Fault Creep along the Southern San Andreas from Interferometric Synthetic Aperture Radar, Permanent Scatterers, and Stacking

Interferometric synthetic aperture radar (InSAR) provides a practical means of mapping creep along major strike-slip faults. The small amplitude of the creep signal (less than 10 mm/yr), combined with its short wavelength, makes it difficult to extract from long time span interferograms, especially in agricultural or heavily vegetated areas. We utilize two approaches to extract the fault creep signal from 37 ERS SAR images along the southem San Andreas Fault. First, amplitude stacking is utilized to identify permanent scatterers, which are then used to weight the interferogram prior to spatial filtering. This weighting improves correlation and also provides a mask for poorly correlated areas. Second, the unwrapped phase is stacked to reduce tropospheric and other short-wavelength noise. This combined processing enables us to recover the near-field (approximately 200 m) slip signal across the fault due to shallow creep. Displacement maps fiom 60 interferograms reveal a diffuse secular strain buildup, punctuated by localized interseismic creep of 4-6 mm/yr line of sight (LOS, 12-18 mm/yr horizontal). With the exception of Durmid Hill, this entire segment of the southern San Andreas experienced right-lateral triggered slip of up to 10 cm during the 3.5-year period spanning the 1992 Landers earthquake. The deformation change following the 1999 Hector Mine earthquake was much smaller (4 cm) and broader than for the Landers event. Profiles across the fault during the interseismic phase show peak-to-trough amplitude ranging from 15 to 25 mm/yr (horizontal component) and the minimum misfit models show a range of creeping/locking depth values that fit the data.

Lyons, Suzanne↗

NASA NTRS2003

Detection of High-impedance Arcing Faults in Radial Distribution DC Systems

High voltage, low current arcing faults in DC power systems have been researched at the NASA Glenn Research Center in order to develop a method for detecting these 'hidden faults', in-situ, before damage to cables and components from localized heating can occur. A simple arc generator was built and high-speed and low-speed monitoring of the voltage and current waveforms, respectively, has shown that these high impedance faults produce a significant increase in high frequency content in the DC bus voltage and low frequency content in the DC system current. Based on these observations, an algorithm was developed using a high-speed data acquisition system that was able to accurately detect high impedance arcing events induced in a single-line system based on the frequency content of the DC bus voltage or the system current. Next, a multi-line, radial distribution system was researched to see if the arc location could be determined through the voltage information when multiple 'detectors' are present in the system. It was shown that a small, passive LC filter was sufficient to reliably isolate the fault to a single line in a multi-line distribution system. Of course, no modification is necessary if only the current information is used to locate the arc. However, data shows that it might be necessary to monitor both the system current and bus voltage to improve the chances of detecting and locating high impedance arcing faults

Gonzalez, Marcelo C.↗

NASA NTRS2004

Optimal Sensor Allocation for Fault Detection and Isolation

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Azam, Mohammad↗

NASA NTRS2005

Fault Diagnosis in HVAC Chillers

Modern buildings are being equipped with increasingly sophisticated power and control systems with substantial capabilities for monitoring and controlling the amenities. Operational problems associated with heating, ventilation, and air-conditioning (HVAC) systems plague many commercial buildings, often the result of degraded equipment, failed sensors, improper installation, poor maintenance, and improperly implemented controls. Most existing HVAC fault-diagnostic schemes are based on analytical models and knowledge bases. These schemes are adequate for generic systems. However, real-world systems significantly differ from the generic ones and necessitate modifications of the models and/or customization of the standard knowledge bases, which can be labor intensive. Data-driven techniques for fault detection and isolation (FDI) have a close relationship with pattern recognition, wherein one seeks to categorize the input-output data into normal or faulty classes. Owing to the simplicity and adaptability, customization of a data-driven FDI approach does not require in-depth knowledge of the HVAC system. It enables the building system operators to improve energy efficiency and maintain the desired comfort level at a reduced cost. In this article, we consider a data-driven approach for FDI of chillers in HVAC systems. To diagnose the faults of interest in the chiller, we employ multiway dynamic principal component analysis (MPCA), multiway partial least squares (MPLS), and support vector machines (SVMs). The simulation of a chiller under various fault conditions is conducted using a standard chiller simulator from the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE). We validated our FDI scheme using experimental data obtained from different types of chiller faults.

Choi, Kihoon↗

NASA NTRS2009

Estimation of Faults in DC Electrical Power System

This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

Gorinevsky, Dimitry↗

NASA NTRS2007

Algorithm-Based Fault Tolerance for Numerical Subroutines

A software library implements a new methodology of detecting faults in numerical subroutines, thus enabling application programs that contain the subroutines to recover transparently from single-event upsets. The software library in question is fault-detecting middleware that is wrapped around the numericalsubroutines. Conventional serial versions (based on LAPACK and FFTW) and a parallel version (based on ScaLAPACK) exist. The source code of the application program that contains the numerical subroutines is not modified, and the middleware is transparent to the user. The methodology used is a type of algorithm- based fault tolerance (ABFT). In ABFT, a checksum is computed before a computation and compared with the checksum of the computational result; an error is declared if the difference between the checksums exceeds some threshold. Novel normalization methods are used in the checksum comparison to ensure correct fault detections independent of algorithm inputs. In tests of this software reported in the peer-reviewed literature, this library was shown to enable detection of 99.9 percent of significant faults while generating no false alarms.

Tumon, Michael↗

NASA NTRS2011

Fault recovery for real-time, multi-tasking computer system

System and methods for providing a recoverable real time multi-tasking computer system are disclosed. In one embodiment, a system comprises a real time computing environment, wherein the real time computing environment is adapted to execute one or more applications and wherein each application is time and space partitioned. The system further comprises a fault detection system adapted to detect one or more faults affecting the real time computing environment and a fault recovery system, wherein upon the detection of a fault the fault recovery system is adapted to restore a backup set of state variables.

Hess, Richard↗

NASA NTRS2005

Fault-Tolerant Heat Exchanger

A compact, lightweight heat exchanger has been designed to be fault-tolerant in the sense that a single-point leak would not cause mixing of heat-transfer fluids. This particular heat exchanger is intended to be part of the temperature-regulation system for habitable modules of the International Space Station and to function with water and ammonia as the heat-transfer fluids. The basic fault-tolerant design is adaptable to other heat-transfer fluids and heat exchangers for applications in which mixing of heat-transfer fluids would pose toxic, explosive, or other hazards: Examples could include fuel/air heat exchangers for thermal management on aircraft, process heat exchangers in the cryogenic industry, and heat exchangers used in chemical processing. The reason this heat exchanger can tolerate a single-point leak is that the heat-transfer fluids are everywhere separated by a vented volume and at least two seals. The combination of fault tolerance, compactness, and light weight is implemented in a unique heat-exchanger core configuration: Each fluid passage is entirely surrounded by a vented region bridged by solid structures through which heat is conducted between the fluids. Precise, proprietary fabrication techniques make it possible to manufacture the vented regions and heat-conducting structures with very small dimensions to obtain a very large coefficient of heat transfer between the two fluids. A large heat-transfer coefficient favors compact design by making it possible to use a relatively small core for a given heat-transfer rate. Calculations and experiments have shown that in most respects, the fault-tolerant heat exchanger can be expected to equal or exceed the performance of the non-fault-tolerant heat exchanger that it is intended to supplant (see table). The only significant disadvantages are a slight weight penalty and a small decrease in the mass-specific heat transfer.

Izenson, Michael G.↗