Added Scope: Beta experiment
Beta flight test data analysis, LDV signal processing analysis and simulation, data processing code, and CESTIM, signal processing code are presented.
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An integrated manifold learning approach for high-dimensional data feature extractions and its applications to online process monitoring of additive manufacturing
As an effective dimension reduction and feature extraction technique, manifold learning has been successfully applied to high-dimensional data analysis. With the rapid development of sensor technology, a large amount of high-dimensional data such as image streams can be easily available. Thus, a promising application of manifold learning is in the field of sensor signal analysis, particular for the applications of online process monitoring and control using high-dimensional data. The objective of this study is to develop a manifold learning-based feature extraction method for process monitoring of Additive Manufacturing (AM) using online sensor data. Due to the non-parametric nature of most existing manifold learning methods, their performance in terms of computational efficiency, as well as noise resistance has yet to be improved. To address this issue, this study proposes an integrated manifold learning approach termed multi-kernel metric learning embedded isometric feature mapping (MKML-ISOMAP) for dimension reduction and feature extraction of online high-dimensional sensor data such as images. Based on the extracted features with the utilization of supervised classification and regression methods, an online process monitoring methodology for AM is implemented to identify the actual process quality status. Finally, in the numerical simulation and real-world case studies, the proposed method demonstrates excellent performance in both prediction accuracy and computational efficiency.
36 MATERIALS SCIENCE↗
Optimal band selection for dimensionality reduction of hyperspectral imagery
Hyperspectral images have many bands requiring significant computational power for machine interpretation. During image pre-processing, regions of interest that warrant full examination need to be identified quickly. One technique for speeding up the processing is to use only a small subset of bands to determine the 'interesting' regions. The problem addressed here is how to determine the fewest bands required to achieve a specified performance goal for pixel classification. The band selection problem has been addressed previously Chen et al., Ghassemian et al., Henderson et al., and Kim et al.. Some popular techniques for reducing the dimensionality of a feature space, such as principal components analysis, reduce dimensionality by computing new features that are linear combinations of the original features. However, such approaches require measuring and processing all the available bands before the dimensionality is reduced. Our approach, adapted from previous multidimensional signal analysis research, is simpler and achieves dimensionality reduction by selecting bands. Feature selection algorithms are used to determine which combination of bands has the lowest probability of pixel misclassification. Two elements required by this approach are a choice of objective function and a choice of search strategy.
Stearns, Stephen D.↗
Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting
A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.
Huang, Norden E.↗
Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting
A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.
Huang, Norden E.↗
Multipath induced errors in meteorological Doppler/interferometer location systems
One application of an RF interferometer aboard a low-orbiting spacecraft to determine the location of ground-based transmitters is in tracking high-altitude balloons for meteorological studies. A source of error in this application is reflection of the signal from the sea surface. Through propagating and signal analysis, the magnitude of the reflection-induced error in both Doppler frequency measurements and interferometer phase measurements was estimated. The theory of diffuse scattering from random surfaces was applied to obtain the power spectral density of the reflected signal. The processing of the combined direct and reflected signals was then analyzed to find the statistics of the measurement error. It was found that the error varies greatly during the satellite overpass and attains its maximum value at closest approach. The maximum values of interferometer phase error and Doppler frequency error found for the system configuration considered were comparable to thermal noise-induced error.
Wallace, R. G.↗
Crop identification using ERTS imagery
Digital analysis of August 15 ERTS-I imagery for southeastern South Dakota was performed to determine the feasibility of conducting crop surveys from satellites. Selected areas of bands 4, 5, 6, and 7 positive transparencies were converted to digital form utilizing Signal Analysis and Dissemination Equipment (SADE). The optical transmission values were printed out in a spatial format. Visual analysis of the printouts indicated that cultivated areas were readily distinguished from non-cultivated areas in all four bands. Bare soil was easily recognized in all four bands. Corn and soybeans, the two major crops in the area, were treated as separate classes rather than as a single class called row crops. Bands 6 and 7 provided good results in distinguishing between corn and soybeans.
Horton, M. L.↗
Measurement of Rayleigh Scattering in Liquid Argon at Vacuum Ultraviolet Wavelengths
Liquid argon based experiments are limited in scintillation light analysis capabilities due to inconsistent measured values of fundamental constants essential for reconstructing scintillation events. This experiment measures the Rayleigh scattering length of vacuum ultraviolet light propagating in liquid argon to support liquid argon experiments by expanding the scope of scintillation signal analysis. Preliminary results are presented for the Rayleigh scattering length in arange of vacuum ultraviolet wavelengths, including the liquid argon scintillation peak wavelength. Currently, further data collection and analysis is required to reduce measurement uncertainty as well as quantify and correct for other effects such as the photon detector temperature dependence. Results will contribute to the development of new photon detector system analysis methods for liquid argon experiments.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Preliminary Analysis of X-Band and Ka-Band Radar for Use in the Detection of Icing Conditions Aloft
NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. Radar has been identified as a strong tool for this work. However, since the remote detection of icing conditions with the intent to identify areas of icing hazard is a new and evolving capability, there are no set requirements for radar sensitivity. This work is an initial attempt to quantify, through analysis, the sensitivity requirements for an icing remote sensing radar. The primary radar of interest for cloud measurements is Ka-band, however, since NASA is currently using an X-band unit, this frequency is also examined. Several aspects of radar signal analysis were examined. Cloud reflectivity was calculated for several forms of cloud using two different techniques. The Air Force Geophysical Laboratory (AFGL) cloud models, with different drop spectra represented by a modified gamma distribution, were utilized to examine several categories of cloud formation. Also a fundamental methods approach was used to allow manipulation of the cloud droplet size spectra. And an analytical icing radar simulator was developed to examine the complete radar system response to a configurable multi-layer cloud environment. Also discussed is the NASA vertical pointing X-band radar. The radar and its data system are described, and several summer weather events are reviewed.
Reehorst, Andrew L.↗
Comparative Analysis of Explosion Signals on Smartphone and Legacy Infrasound Microphones
University Program Review (UPR) 2023 Meeting Comparative Analysis of Explosion Signals on Smartphone and Legacy Infrasound Microphones MTV – Consortium for Monitoring, Technology, and Verification
and Verification↗
Computer implemented empirical mode decomposition method apparatus, and article of manufacture utilizing curvature extrema
A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.
Huang, Norden Eh↗
A study of subterahertz HEMT monolithic oscillators
A detailed study of monolithic InP-based HEMT oscillators for subterahertz operation is presented. InAlAs/InGaAs HEMT's have been optimized for high frequency operation and showed very high maximum oscillation frequencies (f(sub max)) of 310 GHz using offset self-aligned gamma-gate technology. Power characteristics of HEMT oscillators are reported. An oscillation power of more than 10 mW was evaluated by large-signal analysis at 320 GHz using HEMT's with f(sub max) = 450 GHz, V(sub br) = 10 V and a gate width (W(sub g)) of 8 x 22.5 microns. Oscillator topology studies showed that complex feedback schemes such as dual and active feedback enhance the negative resistance. Push-push oscillator designs based on harmonic signal generation can finally be used to overcome the frequency barrier imposed by f(sub max).
Kwon, Youngwoo↗
A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN
Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.
36 MATERIALS SCIENCE↗
Computer implemented empirical mode decomposition method, apparatus and article of manufacture
A computer implemented physical signal analysis method is invented. This method includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.
Huang, Norden E.↗
Monitoring flood damage with satellite imagery
During analysis of ERTS-1 imagery for land use patterns a large impoundment of water was observed in a location that was normally farmland. Subsequent investigation revealed that the satellite had recorded the remaining floodwaters from a severe local rainstorm that had occurred four days prior to the overpass. The inundated area was measured using the automatic planimeter associated with the signal analysis and dissemination equipment located at the Remote Sensing Institute. The area measurement coupled with estimates of the land use and productivity of the region permitted an estimate of the crop damage loss for the inundated area.
Benson, L. A.↗
Stability analysis and compensation of a boost regulator with two-loop control
A useful stability measure has been demonstrated by Wester (1973) for switching regulators with a single feedback loop by applying the Nyquist criterion to the approximate loop gain determined by a time-averaging technique. This approach is extended and applied to the characterization, stability analysis, and compensation design of a switching regulator with two-loop control. The role and relative significance of each control loop is clarified on the basis of a description of circuit operation, and the major and minor loops are identified. In view of the inapplicability of linear feedback theory, describing functions of the feedback loops and power stage are derived, using small-signal analysis. Several phenomena revealed from an analysis of the major loop gain are discussed.
Wester, G. W.↗
An Integrated Imaging Detector of Polarization and Spectral Content
A new type of image detector has been designed to simultaneously analyze the polarization of light at all picture elements in a scene. The Integrated Dual Imaging Detector (IDID) consists of a polarizing beamsplitter bonded to a charge-coupled device (CCD), with signal-analysis circuitry and analog-to-digital converters, all integrated on a silicon chip. It should be capable of 1:10(exp 4) polarization discrimination. The IDID should simplify the design and operation of imaging polarimeters and spectroscopic imagers used, for example, in atmospheric and solar research. Innovations in the IDID include (1) two interleaved 512 x 1024-pixel imaging arrays (one for each polarization plane); (2) large dynamic range (well depth of 10(exp 6) electrons per pixel); (3) simultaneous readout of both images at 10 million pixels per second each; (4) on-chip analog signal processing to produce polarization maps in real time; (5) on-chip 10-bit A/D conversion. When used with a lithium-niobate Fabry-Perot etalon or other color filter that can encode spectral information as polarization, the IDID can collect and analyze simultaneous images at two wavelengths. Precise photometric analysis of molecular or atomic concentrations in the atmosphere is one suggested application. When used in a solar telescope, the IDID will charge the polarization, which can then be converted to maps of the vector magnetic fields on the solar surface.
Rust, D. M.↗
Short-period circumnutations found in sunflower hypocotyls in satellite orbit. A reappraisal of data from Spacelab-1
We have further analysed data from an experiment performed in satellite orbit, in Spacelab-1. In micro-gravity the hypocotyls of Helianthus annuus, cv. "Teddy Bear", showed short period circumnutations (periods around 30 minutes) as well as the already reported long period nutations (with an average period of about 115 minutes). We applied various types of signal analysis (Fourier and wavelet analysis) to the data series. The long period circumnutations have a larger amplitude than the short term circumnutations. Both short and long period circumnutations exist in one and the same hypocotyl. (This is in contrast to our ground control experiments, where were found only the long-period nutations.) The period of the nutations changed throughout the experiment. These results are extending the conclusions drawn after the Spacelab experiment (Brown et al. 1990). In particular they emphasize the existence of both short- and long-period circumnutations in micro-gravity.
short duration↗