Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Faulting”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Protecting Against Faults in JPL Spacecraft

A paper discusses techniques for protecting against faults in spacecraft designed and operated by NASA s Jet Propulsion Laboratory (JPL). The paper addresses, more specifically, fault-protection requirements and techniques common to most JPL spacecraft (in contradistinction to unique, mission specific techniques), standard practices in the implementation of these techniques, and fault-protection software architectures. Common requirements include those to protect onboard command, data-processing, and control computers; protect against loss of Earth/spacecraft radio communication; maintain safe temperatures; and recover from power overloads. The paper describes fault-protection techniques as part of a fault-management strategy that also includes functional redundancy, redundant hardware, and autonomous monitoring of (1) the operational and health statuses of spacecraft components, (2) temperatures inside and outside the spacecraft, and (3) allocation of power. The strategy also provides for preprogrammed automated responses to anomalous conditions. In addition, the software running in almost every JPL spacecraft incorporates a general-purpose "Safe Mode" response algorithm that configures the spacecraft in a lower-power state that is safe and predictable, thereby facilitating diagnosis of more complex faults by a team of human experts on Earth.

Morgan, Paula↗
NASA NTRS2010

An Integrated Architecture for On-Board Aircraft Engine Performance Trend Monitoring and Gas Path Fault Diagnostics

Aircraft engine performance trend monitoring and gas path fault diagnostics are closely related technologies that assist operators in managing the health of their gas turbine engine assets. Trend monitoring is the process of monitoring the gradual performance change that an aircraft engine will naturally incur over time due to turbomachinery deterioration, while gas path diagnostics is the process of detecting and isolating the occurrence of any faults impacting engine flow-path performance. Today, performance trend monitoring and gas path fault diagnostic functions are performed by a combination of on-board and off-board strategies. On-board engine control computers contain logic that monitors for anomalous engine operation in real-time. Off-board ground stations are used to conduct fleet-wide engine trend monitoring and fault diagnostics based on data collected from each engine each flight. Continuing advances in avionics are enabling the migration of portions of the ground-based functionality on-board, giving rise to more sophisticated on-board engine health management capabilities. This paper reviews the conventional engine performance trend monitoring and gas path fault diagnostic architecture commonly applied today, and presents a proposed enhanced on-board architecture for future applications. The enhanced architecture gains real-time access to an expanded quantity of engine parameters, and provides advanced on-board model-based estimation capabilities. The benefits of the enhanced architecture include the real-time continuous monitoring of engine health, the early diagnosis of fault conditions, and the estimation of unmeasured engine performance parameters. A future vision to advance the enhanced architecture is also presented and discussed

Simon, Donald L.↗
NASA NTRS2010

Robust Fault Detection and Isolation for Stochastic Systems

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

George, Jemin↗
NASA NTRS2010

Diagnosing Intermittent and Persistent Faults using Static Bayesian Networks

Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly, while maintaining strong performance on persistent faults.

Megshoel, Ole Jakob↗
NASA NTRS2013

Automated Generation of Fault Management Artifacts from a Simple System Model

Our understanding of off-nominal behavior - failure modes and fault propagation - in complex systems is often based purely on engineering intuition; specific cases are assessed in an ad hoc fashion as a (fallible) fault management engineer sees fit. This work is an attempt to provide a more rigorous approach to this understanding and assessment by automating the creation of a fault management artifact, the Failure Modes and Effects Analysis (FMEA) through querying a representation of the system in a SysML model. This work builds off the previous development of an off-nominal behavior model for the upcoming Soil Moisture Active-Passive (SMAP) mission at the Jet Propulsion Laboratory. We further developed the previous system model to more fully incorporate the ideas of State Analysis, and it was restructured in an organizational hierarchy that models the system as layers of control systems while also incorporating the concept of "design authority". We present software that was developed to traverse the elements and relationships in this model to automatically construct an FMEA spreadsheet. We further discuss extending this model to automatically generate other typical fault management artifacts, such as Fault Trees, to efficiently portray system behavior, and depend less on the intuition of fault management engineers to ensure complete examination of off-nominal behavior.

Spinup and Orient↗
NASA NTRS2015

A Self-Stabilizing Hybrid Fault-Tolerant Synchronization Protocol

This paper presents a strategy for solving the Byzantine general problem for self-stabilizing a fully connected network from an arbitrary state and in the presence of any number of faults with various severities including any number of arbitrary (Byzantine) faulty nodes. The strategy consists of two parts: first, converting Byzantine faults into symmetric faults, and second, using a proven symmetric-fault tolerant algorithm to solve the general case of the problem. A protocol (algorithm) is also present that tolerates symmetric faults, provided that there are more good nodes than faulty ones. The solution applies to realizable systems, while allowing for differences in the network elements, provided that the number of arbitrary faults is not more than a third of the network size. The only constraint on the behavior of a node is that the interactions with other nodes are restricted to defined links and interfaces. The solution does not rely on assumptions about the initial state of the system and no central clock nor centrally generated signal, pulse, or message is used. Nodes are anonymous, i.e., they do not have unique identities. A mechanical verification of a proposed protocol is also present. A bounded model of the protocol is verified using the Symbolic Model Verifier (SMV). The model checking effort is focused on verifying correctness of the bounded model of the protocol as well as confirming claims of determinism and linear convergence with respect to the self-stabilization period.

Malekpour, Mahyar R.↗
NASA NTRS2015

Achieving Agreement in Three Rounds With Bounded-Byzantine Faults

A three-round algorithm is presented that guarantees agreement in a system of K (nodes) greater than or equal to 3F (faults) +1 nodes provided each faulty node induces no more than F faults and each good node experiences no more than F faults, where, F is the maximum number of simultaneous faults in the network. The algorithm is based on the Oral Message algorithm of Lamport et al. and is scalable with respect to the number of nodes in the system and applies equally to the traditional node-fault model as well as the link-fault model. We also present a mechanical verification of the algorithm focusing on verifying the correctness of a bounded model of the algorithm as well as confirming claims of determinism.

Malekpour, Mahyar R.↗
NASA NTRS2016

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Hybrid Systems Diagnosis↗
NASA NTRS2014

Qualitative Event-Based Fault Isolation under Uncertain Observations

For many systems, automatic fault diagnosis is critical to ensuring safe and efficient operation. Fault isolation is performed by analyzing measured signals from the system, and reasoning over the system behavior to determine which faults have occurred, based on models of predicted faulty behavior. For dynamic systems, reasoning may be performed using qualitative analysis of the differences between measured signals and their predicted values, in which observations take the form of qualitative symbols. Such an approach is quick to isolate faults, but depends critically on correct generation of the qualitative symbols from the signals. In this paper, we develop an approach to qualitative event-based fault isolation for dynamic systems that is robust to incorrect qualitative observations. Observations are treated as uncertain, where multiple interpretations of an observation, each with its own probability, are considered. By interpreting observed symbols in a probabilistic manner, the approach degrades gracefully as the number of incorrectly-generated symbols increases. The approach is demonstrated on an electrical power system testbed, and experiments using real data obtained from the hardware demonstrate the improved fault isolation performance in the presence of incorrect symbol generation.

Daigle, Matthew↗
NASA NTRS2016

The Soil Moisture Acttive Passive Mission: Fault Protection Performance and Lessons Learned

Fault protection as a discipline involves a collection of flight software logic and operational processes for detecting unacceptable anomalous behavior, responding prior to reaching criticality, restricting the propagation of a failure beyond a fault containment region, and recovering the vehicle back to full or degraded functionality if possible. The System Fault Protection (SFP) design for the SMAP Earth orbiter was put to the test during its 90-day vehicle commissioning activities. During this time, the SFP software autonomously protected the vehicle from multiple faults to critical hardware, and the operations team successfully returned the observatory to its science state. The SFP also performed well in the presence of anomalous behavior below true safety limits by not taking unnecessary response actions, instead allowing the operations team time to monitor the behavior. Certain aspects of the SFP design were modified during operations via both parameter updates and a full flight software update in order to better match the vehicle behavior in the flight environment. An evaluation of the SMAP SFP performance during vehicle Commissioning will be provided in this paper, as well as a set of lessons learned largely focused on visibility, SFP mutability in operations, responses to peripheral device faults, and Safe Mode recovery and design. By capturing some of the knowledge gained during SMAP Commissioning, it is intended that this paper provide guidance for making future System Fault Protection designs more robust and supportive of operations.

Clark, Jessica↗
NASA NTRS2019

Investigation of Stacking Fault and Antiphase Boundary Segregation in Ni-Based Superalloys Using Density Functional Theory

Ni-base superalloys have a long history of use in jet turbine engines, and efforts to improve their performance in that application are ongoing. It is known that the precipitation of the Ni3Al γ' phase within the disordered FCCγ phase strengthens the overall material. However, in the high-temperature environment found inside a turbine engine during operation, creep can cause the γ' phase to transform to different, weaker phases along stacking faults, leading to a deterioration of performance. In the γ' phase one mode of creep deformation is the formation of stacking fault ribbons, which consist of intrinsic stacking faults further shearing into antiphase boundaries (APBs). It is also known that certain alloying additions exhibit segregation to stacking faults. If segregating elements could be identified which segregate to the intrinsic stacking fault, but not to the APB, the inclusion of such elements could lead to improved creep strength in these alloys. To investigate this possibility, a density functional investigation of the segregation of W, Mo and Cr to both a superlattice intrinsic stacking fault (SISF) and an APB was performed. It was found that W, Mo and Cr all exhibit segregation to the SISF. In contrast, for the APB, Cr was either energy-neutral, or segregates, depending on the presence of additional nearby Cr, or on the specific lattice site upon which it was placed, while Mo and W did not segregate. Because W and Mo segregate to the SISF but not to the APB, the inclusion of these elements could provide a degree of protection against creep-related deterioration.

Good, Brian S.↗
NASA NTRS1995

System Fault Protection Design for the Cassini Spacecraft

Fault protection can include a wide range of topics, ranging from fault prevention to autonomous fault detection and recovery. This paper will address a portion of the autonomous fault detection and recovery implemented onboard the Cassini spacecraft. Specifically, the topic is system fault protection design, as opposed to subsystem fault protection design.

Cassini↗
NASA NTRS2020

Evolution of the Preliminary Fault Management Architecture and Design for the Psyche Mission

The Psyche Mission presents the first opportunity toexplore the largest metal asteroid in the solar system, (16)Psyche, which is believed to be the exposed core of a largerplanetesimal that was stripped of its rocky mantle throughmultiple collisions during early solar system formation. Themission was selected in January 2017 for a 2022 launch as partof NASA’s Discovery Program and is uniquely enabled by theintegration of a Solar Electric Propulsion (SEP) Chassisdelivered by Maxar Space Solutions with JPL’s core deepspace avionics, flight software, and fault managementarchitectures. One of the key design tasks is the development ofa fault management system capable of being responsive to theunique elements of the combined JPL and Maxar spacecraftarchitecture. This new design leverages the strengths of eachorganization, with Maxar delivering its well-proven highvoltage power bus and low-thrust electric propulsionsubsystem from its GEO communications satellite product line,and JPL delivering its deep space mission expertise and thehardware and software most critical to deep space missiondesign. The development of a robust low-thrust mission andthe integration of design philosophies and hardware from twoorganizations is not without its challenges though.A key challenge in the development of the Psyche faultmanagement architecture and design is in the integration ofdesign philosophies and hardware from JPL and Maxar. Atthe architecture level, Maxar GEO communications satellitesare developed under the premise of highly responsive groundin the loop for the resolution of anomalies, and theimplementation takes a fail-operational approach to minimizedown time for its customers. In contrast, a deep space missionmust be able to maintain safety with long periods of groundcommunication outage. Additionally, with no time-criticalevents after launch, the Psyche spacecraft will generally failsafe in the presence of anomalous conditions; specialconsideration is being given to this approach, however, tominimize the loss of electric propulsion thrust time, which iscritical to low-thrust missions. At the hardware level, thedetailed definition of interfaces between JPL and Maxarhardware presents a unique challenge in the development andflowdown of fault management requirements, the developmentand implementation of fault monitors and responses, and thedevelopment and verification of fault containment boundaries.This paper describes the evolution of the Psyche faultmanagement architecture and design from the concept studyinto the preliminary design phase, with a focus on the uniquechallenges associated with flying GEO communicationssatellite hardware in deep space, implementing a robust lowthrust mission, and the integration of design philosophies andhardware from JPL and Maxar. Details regarding how thesechallenges are addressed in the fault management design inorder to maximize heritage, leverage the strengths of eachorganization, and minimize risk across the design are alsodiscussed.

Marsh, Danielle↗
NASA NTRS2022

Validation of the Mars 2020 Fault Protection Design: Navigating the Infinity of the Off-Nominal

On July 30th 2020, the Mars 2020 mission successfully launched out of Cape Canaveral, Florida, passed through the Earth’s shadow, and began its short cruise to Mars. Less than seven months later, the Perseverance rover touched down safely in Jezero Crater to begin its ambitious mission that includes looking for signs of ancient life and collecting samples for future return to Earth. Getting to the successful landing, or “Tango Delta Nominal,” could not have been achieved without also considering the off-nominal. One of the teams supporting this ambitious mission is the fault protection (FP) team. This team is tasked with assessing the various failures, or faults, that could prevent mission success and with ensuring that the autonomous behaviors built into the software and hardware can detect faults and recover the vehicle to a safe state. As part of its charter, the FP team designed a test campaign to provide confidence in the system’s robustness to off-nominal scenarios across all of Mars 2020’s mission phases. The greatest challenge associated with designing such a validation campaign was reducing the infinite number of anomalous scenarios into a finite test suite. In addition, the tests needed to be executed efficiently in order to utilize the team’s limited test venue access, but still needed to maintain a level of rigor that guaranteed confidence in the test outcomes. Given that each test scenario generated massive amounts of data, the team also developed methods for quickly ascertaining whether the autonomous fault protection behaviors maintained vehicle safety in the presence of an anomaly. This paper summarizes the processes that the Mars 2020 fault protection team employed to execute its off-nominal validation campaign. It captures both the methods of generating a suite of off-nominal tests, as well as reducing it to a subset that can be realistically executed within schedule and resource constraints. It also describes the various processes and philosophies that the team utilized to execute the tests efficiently, including creating a standardized procedure template, keeping the test cases modular so that they could be easily interchanged, and capturing common fault injections in a change-controlled database. Finally, it will describe the tools and processes for assessing the test data, focusing in particular on a tool that evaluated vehicle state using “secondary” sources of data to validate that the software had truly configured the spacecraft to the expected safe state.

Morantz, Chaz↗
DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization

The nuclear industry is beginning to see reactors shut down—even after their operating licenses have been extended—because they are not economically competitive with other energy sources. These early closures happen primarily due to economic reasons, despite excellent safety records. Therefore, it is imperative to reduce costs in order to prevent these early closures. One of the contributors to these economic reasons is the large operations and maintenance costs. This paper showcases recent research on advanced fault diagnostics techniques and preventative maintenance optimization (PMO) for reducing NPP maintenance costs. Specifically, it focuses on the feedwater and condensate system (FWCS) for both pressurized- and boiling-water reactor (BWR) systems. The computerized maintenance management system (CMMS), which contains the plant’s digital record of all corrective maintenance (CM) and preventative maintenance (PM) work orders, provided the ground truth for locating potential faults and labeling the process data as either healthy or faulted. Various feature extraction techniques were used to further differentiate the faulted data from the healthy data. Through a cross-validation procedure, support vectors machines were used to label other test sets of process data as either healthy or faulted. With relatively few faults identified in the BWR system, the potential for PMO opens up, since an unnecessary amount of PM leads to inflated maintenance costs. The steps for PMO are summarized, from component health determinations to recommendations for action. An example of PMO assessment is presented for condensate pumps, condensate booster pumps, and the respective motors that drive them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Fault detection in a three-phase dab converter

A system and method of fault detection based on a detailed waveform analysis is presented for transient and steady-state fault operation of 3-Φ DAB converter. Main symptoms of the converter during normal and fault conditions have been identified and a unique pattern in DC bias of phase currents under fault mode is noted. The logic-based fault diagnosis scheme is used to detect the fault and identify the faulty transistor.

Rastogi, Sagar K.↗
DOE OSTI2025

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2023

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗