Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “error detection and error correction”

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 235 records · Page 13

Bounds and approximations for rapid evaluation of coherent MPSK error probabilities

The error probability for MPSK detection is expressed here as a sum of a familiar upper-bound approximation and a correction term which is well suited for numerical integration. An asymptotic expansion of the correction term is derived, from which simple and extremely tight upper and lower bounds are obtained. Relative errors in using these bounds and approximations of them are graphed for cases of practical interest.

Chie, C. M.↗

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗

On decoding BCH codes.

Extension, modification and analysis of Gorenstein-Zierler decoding algorithm for binary codes of Bose, Ray-Chaudhuri and Hocquenghem /BCH/ correcting erasures and errors

BINARY CODE↗

Application of a Bank of Kalman Filters for Aircraft Engine Fault Diagnostics

In this paper, a bank of Kalman filters is applied to aircraft gas turbine engine sensor and actuator fault detection and isolation (FDI) in conjunction with the detection of component faults. This approach uses multiple Kalman filters, each of which is designed for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, thereby isolating the specific fault. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The proposed FDI approach is applied to a nonlinear engine simulation at nominal and aged conditions, and the evaluation results for various engine faults at cruise operating conditions are given. The ability of the proposed approach to reliably detect and isolate sensor and actuator faults is demonstrated.

Kobayashi, Takahisa↗

Tropospheric Delay Signal in SAR Interferogram and its Correction for Precise Surface Change Detection

Synthetic Aperture Radar (SAR) interferometry has become an important tool for measuring the surface deformation and mapping topography. The largest error source of the SAR interferometry measurements is differential atmospheric delay of water vapor. It reflects detailed distribution of water vapor in troposphere at data acquisition. We found phase difference associated with atmospheric waves and severe local atmospheric phenomena in interferograms. To distinguish phase difference associated with surface deformation from tropospheric effect, we need several SAR interferograms including the time period of the deformation. Averaging the interferograms is an effective way to reduce the tropospheric delay from horizontal inhomogeneity of the water vapor distribution. Apart from the tropospheric delay of the horizontal water vapor inhomogeneity, we often find the differential phase correlated to the topography (elevation) in interferograms, which might cause error in interpretation of surface deformation. This phase is due to the differential tropospheric delay caused by the topography and vertical change of water vapor between two images in different atmospheric condition. Theoretical calculation shows that the phase difference can be approximated by linear expression of the elevation. We applied a simple and effective correction method that the error is removed by subtracting the DEM (Digital Elevation Model) multiplied a coefficient.

Fujiwara, Satoshi↗

Aircraft Engine Sensor/Actuator/Component Fault Diagnosis Using a Bank of Kalman Filters

In this report, a fault detection and isolation (FDI) system which utilizes a bank of Kalman filters is developed for aircraft engine sensor and actuator FDI in conjunction with the detection of component faults. This FDI approach uses multiple Kalman filters, each of which is designed based on a specific hypothesis for detecting a specific sensor or actuator fault. In the event that a fault does occur, all filters except the one using the correct hypothesis will produce large estimation errors, from which a specific fault is isolated. In the meantime, a set of parameters that indicate engine component performance is estimated for the detection of abrupt degradation. The performance of the FDI system is evaluated against a nonlinear engine simulation for various engine faults at cruise operating conditions. In order to mimic the real engine environment, the nonlinear simulation is executed not only at the nominal, or healthy, condition but also at aged conditions. When the FDI system designed at the healthy condition is applied to an aged engine, the effectiveness of the FDI system is impacted by the mismatch in the engine health condition. Depending on its severity, this mismatch can cause the FDI system to generate incorrect diagnostic results, such as false alarms and missed detections. To partially recover the nominal performance, two approaches, which incorporate information regarding the engine s aging condition in the FDI system, will be discussed and evaluated. The results indicate that the proposed FDI system is promising for reliable diagnostics of aircraft engines.

Kobayashi, Takahisa↗

Cosmic axions revealed via amplified modulation of the ellipticity of a laser

We propose a new axion dark matter detection strategy that employs optical readout of laser beam ellipticity modulations caused by axion-induced electric fields in a microwave cavity, using electro-optic (EO) crystals, enhanced by externally injected radio-frequency (rf) power. Building upon the variance-based probing method [Phys. Rev. D 107, 103005 (2023).], we extend this concept to the optical domain: A weak probe laser interacts with an EO crystal coupled to the resonant microwave cavity field at cryogenic temperatures, and the axion-induced electric field is revealed through induced ellipticity. The injected rf signal coherently interferes with that of the axion field, amplifying the optical response and significantly improving sensitivity. While our EO-based method employs a Fabry-Pérot resonator, we do not require Michelson interferometers. Our method, hence, enables compact, high-frequency axion searches, across the 0.5–50 GHz range. Operating at cryogenic temperatures not only suppresses thermal backgrounds, but, critically, allows the probing method to mitigate the quantum noise. This approach offers a scalable path forward for axion detection over the ∼(few−200) μ⁢eV mass range—covering the preferred parameter space for the postinflationary Peccei-Quinn axion dark matter—using compact, tunable systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quasi-optimal decoding of linear block codes using soft decision detection

A simple but effective decoding procedure, applicable to any (n,k) linear block code with symbols from GF(q), is described. The technique involves a transformation of the parity check equations which focuses the code's correction power on the soft symbol set while still retaining the capability to correct one symbol error from outside this set. The soft symbol set is defined to be the n-k least reliably detected code symbol positions whose parity check row-spaces are linearly independent. The process generates a number of error vector screening candidates, each a solution to the parity check equations, and the maximum-likelihood candidate is accepted.

Greene, E. P.↗

Minimax decoding of cyclic block codes

A minimax decoding algorithm utilizing soft bit detection of an (n,k) cyclic block code is described which will permit the correction of up to n-k bit errors interspersed at random locations throughout the block. The decoding solution consists of: (1) identifying the ordered soft bit set and, (2) finding the minimum order solution to the resulting syndrome equations where the nonzero error vector components are constrained to be a subset of the soft bit set. An efficient implementation of the decoding operation is described. In essence, this algorithm focuses the correction capability of the code on those bit positions which have the lowest a posteriori probabilities of correct detection.

Greene, E. P.↗

Leveraging Quantum Sensors for Dark Matter Detection

Recent measurements have demonstrated that superconducting qubit decoherence is affected by radiation. As a result, many groups around the world are working to better understand the relationship between different types of radiation and qubit response. This crucial to quantum error correction because radiation can cause correlated loss of information across multiple qubits on a chip, defeating error correction algorithms. Additionally, the fundamental energy scale at which superconducting qubits operate may enable their development as meV-scale detectors for HEP applications, such as the direct detection of dark matter. At Fermilab, we have two world-class underground facilities which are already being used to study this problem: NEXUS and QUIET. I will present on results from operating superconducting qubits in each of these facilities, and the potential implications towards utilizing qubits as sensors for a novel dark matter detector.

Baxter, Daniel [Texas U., Arlington]↗

Leveraging Quantum Sensors for Dark Matter Detection

Recent measurements have demonstrated that superconducting qubit decoherence is affected by radiation. As a result, many groups around the world are working to better understand the relationship between different types of radiation and qubit response. This crucial to quantum error correction because radiation can cause correlated loss of information across multiple qubits on a chip, defeating error correction algorithms. Additionally, the fundamental energy scale at which superconducting qubits operate may enable their development as meV-scale detectors for HEP applications, such as the direct detection of dark matter. At Fermilab, we have two world-class underground facilities which are already being used to study this problem: NEXUS and QUIET. I will present on results from operating superconducting qubits in each of these facilities, and the potential implications towards utilizing qubits as sensors for a novel dark matter detector.

Baxter, Daniel [Texas U., Arlington]↗

Observability of fidelity decay at the Lyapunov rate in few-qubit quantum simulations

In certain regimes, the fidelity of quantum states will decay at a rate set by the classical Lyapunov exponent. This serves both as one of the most important examples of the quantum-classical correspondence principle and as an accurate test for the presence of chaos. While detecting this phenomenon is one of the first useful calculations that noisy quantum computers without error correction can perform, a thorough study of the quantum sawtooth map reveals that observing the Lyapunov regime is just beyond the reach of present-day devices. We prove that there are three bounds on the ability of any device to observe the Lyapunov regime and give the first quantitatively accurate description of these bounds: (1) the Fermi golden rule decay rate must be larger than the Lyapunov rate, (2) the quantum dynamics must be diffusive rather than localized, and (3) the initial decay rate must be slow enough for Lyapunov decay to be observable. This last bound, which has not been recognized previously, places a limit on the maximum amount of noise that can be tolerated. The theory implies that an absolute minimum of 6 qubits is required. Recent experiments on IBM-Q and IonQ imply that some combination of a noise reduction by up to 100x per gate and large increases in connectivity and gate parallelization are also necessary. Finally, scaling arguments are given that quantify the ability of future devices to observe the Lyapunov regime based on trade-offs between hardware architecture and performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

All-digital precision processing of ERTS images

The author has identified the following significant results. Digital techniques have been developed and used to apply precision-grade radiometric and geometric corrections to ERTS MSS and RBV scenes. Geometric accuracies sufficient for mapping at 1:250,000 scale have been demonstrated. Radiometric quality has been superior to ERTS NDPF precision products. A configuration analysis has shown that feasible, cost-effective all-digital systems for correcting ERTS data are easily obtainable. This report contains a summary of all results obtained during this study and includes: (1) radiometric and geometric correction techniques, (2) reseau detection, (3) GCP location, (4) resampling, (5) alternative configuration evaluations, and (6) error analysis.

Bernstein, R.↗

A study of redundancy management strategy for tetrad strap-down inertial systems

Algorithms were developed that attempt to identify which sensor in a tetrad configuration has experienced a step failure. An algorithm is also described that provides a measure of the confidence with which the correct identification was made. Experimental results are presented from real-time tests conducted on a three-axis motion facility utilizing an ortho-skew tetrad strapdown inertial sensor package. The effects of prediction errors and of quantization on correct failure identification are discussed as well as an algorithm for detecting second failures through prediction.

Hruby, R. J.↗

Integrating automated structured analysis and design with Ada programming support environments

Ada Programming Support Environments (APSE) include many powerful tools that address the implementation of Ada code. These tools do not address the entire software development process. Structured analysis is a methodology that addresses the creation of complete and accurate system specifications. Structured design takes a specification and derives a plan to decompose the system subcomponents, and provides heuristics to optimize the software design to minimize errors and maintenance. It can also produce the creation of useable modules. Studies have shown that most software errors result from poor system specifications, and that these errors also become more expensive to fix as the development process continues. Structured analysis and design help to uncover error in the early stages of development. The APSE tools help to insure that the code produced is correct, and aid in finding obscure coding errors. However, they do not have the capability to detect errors in specifications or to detect poor designs. An automated system for structured analysis and design TEAMWORK, which can be integrated with an APSE to support software systems development from specification through implementation is described. These tools completement each other to help developers improve quality and productivity, as well as to reduce development and maintenance costs. Complete system documentation and reusable code also resultss from the use of these tools. Integrating an APSE with automated tools for structured analysis and design provide capabilities and advantages beyond those realized with any of these systems used by themselves.

Hecht, Alan↗

Effects of weather on the retrieval of sea ice concentration and ice type from passive microwave data

Effects of wind, water vapor, and cloud liquid water on ice concentration and ice type calculated from passive microwave data are assessed through radiative transfer calculations and observations. These weather effects can cause overestimates in ice concentration and more substantial underestimates in multi-year ice percentage by decreasing polarization and by decreasing the gradient between frequencies. The effect of surface temperature and air temperature on the magnitudes of weather-related errors is small for ice concentration and substantial for multiyear ice percentage. The existing weather filter in the NASA Team Algorithm addresses only weather effects over open ocean; the additional use of local open-ocean tie points and an alternative weather correction for the marginal ice zone can further reduce errors due to weather. Ice concentrations calculated using 37 versus 18 GHz data show little difference in total ice covered area, but greater differences in intermediate concentration classes. Given the magnitude of weather-related errors in ice classification from passive microwave data, corrections for weather effects may be necessary to detect small trends in ice covered area and ice type for climate studies.

Maslanik, J. A.↗

Updating finite element dynamic models using an element-by-element sensitivity methodology

A sensitivity-based methodology for improving the finite element model of a given structure using test modal data and a few sensors is presented. The proposed method searches for both the location and sources of the mass and stiffness errors and does not interfere with the theory behind the finite element model while correcting these errors. The updating algorithm is derived from the unconstrained minimization of the squared L sub 2 norms of the modal dynamic residuals via an iterative two-step staggered procedure. At each iteration, the measured mode shapes are first expanded assuming that the model is error free, then the model parameters are corrected assuming that the expanded mode shapes are exact. The numerical algorithm is implemented in an element-by-element fashion and is capable of 'zooming' on the detected error locations. Several simulation examples which demonstate the potential of the proposed methodology are discussed.

Farhat, Charbel↗

Discontinuity Detection for Analysis of Telerobot Trajectories

To identify spatial and temporal discontinuities in telerobot movement in order to describe the shift in operators control and error correction strategies from continuous control to move-and-wait strategies. This shift was studied under conditions of simulated increasingly time-delayed teleoperation. The ultimate goal is to determine if the time delay associated with the shift is invariant with independently imposed control difficulty. We expect this shift to manifest itself as changes in the number of discontinuity of movement path. We proposed an approach to spatial and temporal discontinuity detection algorithm for analysis of teleoperated trajectory in three dimensional space. The algorithm provides a simple and potentially objective method for detecting the discontinuity during telerobot operation and evaluating the difficulty of rotational coordinate condition in teleoperation.

Yeom, Kiwon↗