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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A labeled dataset for building HVAC systems operating in faulted and fault-free states

Abstract Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes the development and content of the largest known public dataset of building system operations in faulted and fault free states. It covers the most common HVAC systems and configurations in commercial buildings, across a range of climates, fault types, and fault severities. The time series points that are contained in the dataset include measurements that are commonly encountered in existing buildings as well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field operation were used to generate the data. To inform more data-hungry algorithms, most of the simulated data cover a year of operation for each fault-severity combination. The data set is a significant expansion of that first published by the lead authors in 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Automated fault detection and diagnosis of airflow and refrigerant charge faults in residential HVAC systems using IoT-enabled measurements

While automated fault detection and diagnosis (AFDD) in residential heating, ventilation, and air-conditioning (HVAC) using smart thermostat data is gaining increasing attention in recent times, it still requires in-depth investigation for market adoption, especially with real-life data. Furthermore, this paper proposes an Internet of Things (IoT) - based approach that adds a smart sensor to the smart thermostat data to carry out AFDD. The approach uses a model which predicts enthalpy change across the evaporator and compares the prediction to the measured enthalpy change. Deviations which exceed analytically determined thresholds then signal faults in the HVAC system. The faults detected are either installation related or degradation related. Experimental tests were carried out in four homes located in Norman, Oklahoma. From the tests, installation issues like indoor/outdoor mismatch were detected in two homes, while a 30% low charge and low indoor airflow rate were detected in one home. The results show that the proposed AFDD algorithm was able to successfully detect two prevalent faults, namely low indoor airflow and low refrigerant charge. Unlike most of the smart thermostat-based approaches, the proposed IoT-based approach can detect and diagnose both faults but only require one additional sensor which is provided by smart thermostat manufacturers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1978

Critical fault patterns determination in fault-tolerant computer systems

The method proposed tries to enumerate all the critical fault-patterns (successive occurrences of failures) without analyzing every single possible fault. The conditions for the system to be operating in a given mode can be expressed in terms of the static states. Thus, one can find all the system states that correspond to a given critical mode of operation. The next step consists in analyzing the fault-detection mechanisms, the diagnosis algorithm and the process of switch control. From them, one can find all the possible system configurations that can result from a failure occurrence. Thus, one can list all the characteristics, with respect to detection, diagnosis, and switch control, that failures must have to constitute critical fault-patterns. Such an enumeration of the critical fault-patterns can be directly used to evaluate the overall system tolerance to failures. Present research is focused on how to efficiently make use of these system-level characteristics to enumerate all the failures that verify these characteristics.

Mccluskey, E. J.↗
NASA NTRS1980

MIL-M-38510/470 test vectors: Fault detection efficiency measurement via hardware fault simulation

The stuck fault detection efficiency of the test vectors developed for the MIL-M-38510/470 NASA was measured using a hardware stuck fault simulator for the 1802 microprocessor. Thirty-nine stuck faults were not detected out of a total of 874 injected into the combinatorial and sequential parts of the microprocessor. Since undetected faults can create catastrophic errors in equipment designed for high reliability applications, it is recommended that the MIL-M-38510/470 NASA be enhanced with additional test vectors so as to achieve 100% stuck fault detection efficiency.

Timoc, C. C.↗
NASA NTRS1991

The width of fault zones in a brittle-viscous lithosphere: Strike-slip faults

A fault zone in an ideal brittle material overlying a very weak substrate could, in principle, consist of a single slip surface. Real fault zones have a finite width consisting of a number of nearly parallel slip surfaces on which deformation is distributed. The hypothesis that the finite width of fault zones reflects stresses due to quasistatic flow in the ductile substrate of a brittle surface layer is explored. Because of the simplicity of theory and observations, strike-slip faults are examined first, but the analysis can be extended to normal and thrust faulting.

Parmentier, E. M.↗
NASA NTRS1992

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Duyar, A.↗
NASA NTRS1992

Fault detection and fault tolerance in robotics

Robots are used in inaccessible or hazardous environments in order to alleviate some of the time, cost and risk involved in preparing men to endure these conditions. In order to perform their expected tasks, the robots are often quite complex, thus increasing their potential for failures. If men must be sent into these environments to repair each component failure in the robot, the advantages of using the robot are quickly lost. Fault tolerant robots are needed which can effectively cope with failures and continue their tasks until repairs can be realistically scheduled. Before fault tolerant capabilities can be created, methods of detecting and pinpointing failures must be perfected. This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot. The resulting failure flow chart can also be used to analyze the resiliency of the robot in the presence of specific faults. By simulating robot failures and fault detection schemes, the problems involved in detecting failures for robots are explored in more depth.

Visinsky, Monica↗
NASA NTRS1991

Implementation of a model based fault detection and diagnosis technique for actuation faults of the SSME

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the Space Shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the Space Shuttle Main Engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Duyar, A.↗
DOE OSTI2023

Implementation and test of an automated control hunting fault correction algorithm in a fault detection and diagnostics tool

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2007

Fault Injection Campaign for a Fault Tolerant Duplex Framework

Fault tolerance is an efficient approach adopted to avoid or reduce the damage of a system failure. In this work we present the results of a fault injection campaign we conducted on the Duplex Framework (DF). The DF is a software developed by the UCLA group [1, 2] that uses a fault tolerant approach and allows to run two replicas of the same process on two different nodes of a commercial off-the-shelf (COTS) computer cluster. A third process running on a different node, constantly monitors the results computed by the two replicas, and eventually restarts the two replica processes if an inconsistency in their computation is detected. This approach is very cost efficient and can be adopted to control processes on spacecrafts where the fault rate produced by cosmic rays is not very high.

fault injector↗
DOE OSTI2022

Line Faults Classification Using Machine Learning on Three Phase Voltages Extracted from Large Dataset of PMU Measurements

An end-to-end supervised learning method is developed to classify transmission line faults in a twoyear field-recorded dataset that includes synchronized measurements of three-phase voltages recorded by 38 Phasor Measurement Units (PMU) sparsely located in in the US Western Grid interconnection. Statistical analysis is performed to extract features from this large dataset to train Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) classifiers initially. The training further leverages a simulated dataset from a synthetic grid with 12 PMUs to increase the number of faults of types infrequently seen in the field-recorded dataset. Training the classification models with the combined dataset resulted in a classification accuracy of 97.7%. This is a significant improvement over 89.7% to 92.5% accuracy obtained by relying on the field-recorded dataset alone.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A cosine-based correlation information entropy approach for building automatic fault detection baseline construction

Building automatic fault detection and diagnosis (AFDD) technologies have shown great potential for energy savings. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Existing research using physics-based knowledge and models for AFDD has mainly taken a trial-and-error approach to determine if a given baseline is sufficient via empirical experiments. A mechanism to support decisions such as how many samples and what samples should be included in the baseline is currently lacking. In this study, a data-driven method for AFDD baseline construction based on information entropy is developed. The entropy is derived based on cosine similarity among typical building automation system measurements in conjunction with outdoor weather information. The performance of the proposed method is evaluated using real building data. Evaluation results indicate that the fault detection strategy adopting the proposed method has similar or better accuracy in detecting faults compared to the same fault detection strategy using the baseline construction method from the literature. Additionally, the use of entropy enables the proposed method to automatically construct and assess the baseline consisting of information-rich samples.

42 ENGINEERING↗
NASA NTRS1985

Lunar Mascon Loading: an Example of the Importance of Fault Initiation Depth on Fault Type Predictions from Stresses on Planetary Surfaces

Geophysical models that predict fault type from stresses calculated at the planetary surface (zero depth) can be misleading because faults generally initiate at depth under a different stress regime and propagate to the surface. The generally accepted and most commonly employed criteria for fault prediction from calculated stresses on planetary surfaces points out problems in neglecting the effects of non-isotropic overburden stresses and the use of realistic material constants and shows a well known example (mascon loading on the moon) where neglecting this effect predicts a different type of fault than is actually observed.

Golombek, M. P.↗
NASA NTRS1988

A nonlinear least-squares inverse analysis of strike-slip faulting with application to the San Andreas fault

A nonlinear weighted least-squares analysis was performed for a synthetic elastic layer over a viscoelastic half-space model of strike-slip faulting. Also, an inversion of strain rate data was attempted for the locked portions of the San Andreas fault in California. Based on an eigenvector analysis of synthetic data, it is found that the only parameter which can be resolved is the average shear modulus of the elastic layer and viscoelastic half-space. The other parameters were obtained by performing a suite of inversions for the fault. The inversions on data from the northern San Andreas resulted in predicted parameter ranges similar to those produced by inversions on data from the whole fault.

Williams, Charles A.↗
NASA NTRS1988

Dynamic characteristics of a 20 kHz resonant power system - Fault identification and fault recovery

A detailed simulation of a dc inductor resonant driver and receiver is used to demonstrate the transient characteristics of a 20 kHz resonant power system during fault and overload conditions. The simulated system consists of a dc inductor resonant inverter (driver), a 50-meter transmission cable, and a dc inductor resonant receiver load. Of particular interest are the driver and receiver performance during fault and overload conditions and on the recovery characteristics following removal of the fault. The information gained from these studies sets the stage for further work in fault identification and autonomous power system control.

Wasynczuk, O.↗
NASA NTRS1989

The morphology of strike-slip faults - Examples from the San Andreas Fault, California

The dilatational strains associated with vertical faults embedded in a horizontal plate are examined in the framework of fault kinematics and simple displacement boundary conditions. Using boundary element methods, a sequence of examples of dilatational strain fields associated with commonly occurring strike-slip fault zone features (bends, offsets, finite rupture lengths, and nonuniform slip distributions) is derived. The combinations of these strain fields are then used to examine the Parkfield region of the San Andreas fault system in central California.

Bilham, Roger↗