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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

Huang, Yiteng↗
NASA NTRS1992

Signal processing methodologies for an acoustic fetal heart rate monitor

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Pretlow, Robert A., III↗
NASA NTRS1973

Acoustic-emission signal-processing analog unit for locating flaws in large tanks

Technique monitors structural flaws in 105-in. diameter tanks. Tank surface is divided into many areas and each area is sectioned into 20 equilateral triangles that form icosahedron. Twelve transducers are equally positioned on tank surface at vertex of each triangle. Transducers monitor area for flaws by detecting any increase in acoustical activity.

Moskal, F. J.↗
NASA NTRS2014

Acoustic Data Processing and Transient Signal Analysis for the Hybrid Wing Body 14- by 22-Foot Subsonic Wind Tunnel Test

An advanced vehicle concept, the HWB N2A-EXTE aircraft design, was tested in NASA Langley's 14- by 22-Foot Subsonic Wind Tunnel to study its acoustic characteristics for var- ious propulsion system installation and airframe con gurations. A signi cant upgrade to existing data processing systems was implemented, with a focus on portability and a re- duction in turnaround time. These requirements were met by updating codes originally written for a cluster environment and transferring them to a local workstation while en- abling GPU computing. Post-test, additional processing of the time series was required to remove transient hydrodynamic gusts from some of the microphone time series. A novel automated procedure was developed to analyze and reject contaminated blocks of data, under the assumption that the desired acoustic signal of interest was a band-limited sta- tionary random process, and of lower variance than the hydrodynamic contamination. The procedure is shown to successfully identify and remove contaminated blocks of data and retain the desired acoustic signal. Additional corrections to the data, mainly background subtraction, shear layer refraction calculations, atmospheric attenuation and microphone directivity corrections, were all necessary for initial analysis and noise assessments. These were implemented for the post-processing of spectral data, and are shown to behave as expected.

Bahr, Christopher J.↗
NASA NTRS2003

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Huang, Norden E.↗
NASA NTRS1987

Punch stretching process monitoring using acoustic emission signal analysis. II - Application of frequency domain deconvolution

The coloring effect on the acoustic emission signal due to the frequency response of the data acquisition/processing instrumentation may bias the interpretation of AE signal characteristics. In this paper, a frequency domain deconvolution technique, which involves the identification of the instrumentation transfer functions and multiplication of the AE signal spectrum by the inverse of these system functions, has been carried out. In this way, the change in AE signal characteristics can be better interpreted as the result of the change in only the states of the process. Punch stretching process was used as an example to demonstrate the application of the technique. Results showed that, through the deconvolution, the frequency characteristics of AE signals generated during the stretching became more distinctive and can be more effectively used as tools for process monitoring.

Liang, Steven Y.↗
NASA NTRS2015

NASA's Aeroacoustic Tools and Methods for Analysis of Aircraft Noise

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The ability to quantify aircraft noise at the source and ultimately at observers is required to develop low noise aircraft designs and flight procedures. Predicting noise at the source, accounting for scattering and propagation through the atmosphere to the observer, and assessing the perception and impact on a community requires physics-based aeroacoustics tools. Along with the analyses for aero-performance, weights and fuel burn, these tools can provide the acoustic component for aircraft MDAO (Multidisciplinary Design Analysis and Optimization). Over the last decade significant progress has been made in advancing the aeroacoustic tools such that acoustic analyses can now be performed during the design process. One major and enabling advance has been the development of the system noise framework known as Aircraft NOise Prediction Program2 (ANOPP2). ANOPP2 is NASA's aeroacoustic toolset and is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. The toolset includes a framework that integrates noise prediction and propagation methods into a unified system for use within general aircraft analysis software. This includes acoustic analyses, signal processing and interfaces that allow for the assessment of perception of noise on a community. ANOPP2's capability to incorporate medium fidelity shielding predictions and wind tunnel experiments into a design environment is presented. An assessment of noise from a conventional and Hybrid Wing Body (HWB) aircraft using medium fidelity scattering methods combined with noise measurements from a model-scale HWB recently placed in NASA's 14x22 wind tunnel are presented. The results are in the form of community noise metrics and auralizations.

Rizzi, Stephen A.↗
NASA NTRS1975

Electrophysiological measurement of human auditory function

Knowledge of the human auditory evoked response is reviewed, including methods of determining this response, the way particular changes in the stimulus are coupled to specific changes in the response, and how the state of mind of the listener will influence the response. Important practical applications of this basic knowledge are discussed. Measurement of the brainstem evoked response, for instance, can state unequivocally how well the peripheral auditory apparatus functions. It might then be developed into a useful hearing test, especially for infants and preverbal or nonverbal children. Clinical applications of measuring the brain waves evoked 100 msec and later after the auditory stimulus are undetermined. These waves are clearly related to brain events associated with cognitive processing of acoustic signals, since their properties depend upon where the listener directs his attention and whether how long he expects the signal.

Galambos, R.↗
NASA NTRS1975

Electrophysiological measurement of human auditory function

Contingent negative variations in the presence and amplitudes of brain potentials evoked by sound are considered. Evidence is produced that the evoked brain stem response to auditory stimuli is clearly related to brain events associated with cognitive processing of acoustic signals since their properties depend upon where the listener directs his attention, whether the signal is an expected event or a surprise, and when sound that is listened-for is heard at last.

Galambos, R.↗
NASA NTRS2014

NDE Software Developed at NASA Glenn Research Center

NASA Glenn Research Center has developed several important Nondestructive Evaluation (NDE) related software packages for different projects in the last 10 years. Three of the software packages have been created with commercial-grade user interfaces and are available to United States entities for download on the NASA Technology Transfer and Partnership Office server (https://sr.grc.nasa.gov/). This article provides brief overviews of the software packages.

image processing↗
NASA NTRSDate not supplied

EVALUATION OF ACOUSTIC SNAPSHOT ARRAYS FOR ROTORCRAFT SOURCE NOISE CHARACTERIZATION

Historical development of acoustic hemispheres has required steady flight of a rotorcraft vehicle across a large linear array of microphones. The US Army, NASA, and Navy recently conducted a rotorcraft acoustics flight test in which multiple “snapshot” microphone arrays were used alongside a traditional linear microphone array. The snapshot arrays allow for a near instantaneous capture of rotorcraft acoustic emissions, without the need for steady flight. Development of the snapshot array is contained herein, and an evaluation of effectiveness of the array during adverse weather conditions. The snapshot arrays captured significant variation in acoustic emissions throughout a single run and between multiple runs of similar conditions. Hemispheres were created and modelled in land-use planning software and an investigation of A-weighted Sound Exposure Level (SEL [dBA]) was conducted. Sideline predictions of SEL compared well (within 0.1 dBA) between traditional and snapshot arrays, while centre line locations were less favourable with a difference of 1.6 dBA. Future refinement is required for the snapshot array technique, including advanced design of microphone placement and employing a semiempirical method to interpolate between measurement points, instead of the linear frequency weighting conventionally employed.

Rotorcraft↗
NASA NTRS2015

Removing Background Noise with Phased Array Signal Processing

Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

Background Noise↗
NASA NTRS2003

Passive Fetal Heart Monitoring System

A fetal heart monitoring system and method for detecting and processing acoustic fetal heart signals transmitted by different signal transmission modes. One signal transmission mode, the direct contact mode, occurs in a first frequency band when the fetus is in direct contact with the maternal abdominal wall. Another signal transmission mode, the fluid propagation mode, occurs in a second frequency band when the fetus is in a recessed position with no direct contact with the maternal abdominal wall. The second frequency band is relatively higher than the first frequency band. The fetal heart monitoring system and method detect and process acoustic fetal heart signals that are in the first frequency band and in the second frequency band.

Zuckerwar, Allan J.↗
NASA NTRS2012

Debris Impact Detection Instrument for Crewed Modules

When micrometeoroid or debris impacts occur on a space habitat, crew members need to be quickly informed of the likely extent of damage, and be directed to the impact location for possible repairs. This is especially important because the outer walls of pressurized volumes are often not easily accessible, blocked by racks or cabinets. The goal of the Habitat Particle Impact Monitoring System (HIMS) is to develop a fully automated, end-to-end particle impact detection system for crewed space exploration modules. The HIMS uses multiple passive, thin film piezo-polymer vibration sensors to detect impacts on a surface, and computer processing of the acoustical signals to characterize the impacts. Development and demonstration of the HIMS is proceeding in concert with NASA's Habitat Demonstration Unit (HDU) Project. The HDU Project is designed to develop and test various technologies, configurations, and operational concepts for exploration habitats. This paper describes the HIMS development, initial testing, and HDU integration efforts. Initial tests of the system on the HDU were conducted at NASA s 2010 and 2011 Desert Research and Technologies Studies (Desert-RATS or D-RATS). The HDU lab module, as seen from above, has an open circular floorplan divided into eight wedge-shaped Segments. The side wall of the module -- the surface used for this technology demonstration -- is a hard fiberglass composite covered with a layer of sprayed-on foam insulation. Four sensor locations were assigned near the corners of a rectangular pattern on the wall of one segment of the HDU lab module. The flat, self-adhesive sensors were applied to the module during its initial outfitting. To study the influence of the wall s construction (thickness and materials), three sets of four sensors were installed at different layer depths: on the interior of the module s wall, on the exterior of the same wall, and on the exterior of the foam insulation. The signal produced when a vibration passes through a sensor is first sent through a pre-amplifier. The amplified signal then is sent to the data acquisition and data processing systems. The vibration data from the sensors are then processed and reduced to a form suitable for presentation to the crew.

Opiela, J.↗
NASA NTRS1975

Application of acoustic surface wave technology to shuttle radar

The application of surface acoustic wave (SAW) signal processing devices in the space shuttle was explored. In order to demonstrate the functions which a SAW device might perform, a breadboard pulse compression filter (PCF) module was assembled. The PCF permits a pulse radar to operate with a large duty cycle and low peak power, a regime favorable to the use of solid state RF sources. The transducer design, strong coupling compensation, circuit model analysis, fabrication limitations, and performance evaluation of a PCF are described. The nominal value of the compression ratio is 100:1 with 10-MHz bandwidth centered at 60 MHz and 10-microsecond dispersive delay. The PCF incorporates dispersive interdigital transducers and a piezoelectric lithium niobate substrate.

Source record↗
NASA NTRS1983

Introduction to acoustic emission

Typical acoustic emission signal characteristics are described and techniques which localize the signal source by processing the acoustic delay data from multiple sensors are discussed. The instrumentation, which includes sensors, amplifiers, pulse counters, a minicomputer and output devices is examined. Applications are reviewed.

Possa, G.↗
NASA NTRS2011

Demonstration of a Particle Impact Monitoring System for Crewed Space Exploration Modules

When micrometeorite or debris impacts occur on a space habitat, crew members need to be quickly informed of the likely extent of damage, and be directed to the impact location for possible repairs. The goal of the Habitat Particle Impact Monitoring System (HIMS) is to develop a fully automated, end-to-end particle impact detection system for crewed space exploration modules, both in space and on the surfaces of Solar System bodies. The HIMS uses multiple thin film piezo-polymer vibration sensors to detect impacts on a surface, and computer processing of the acoustical signals to characterize the impacts. Development and demonstration of the HIMS is proceeding in concert with NASA's Habitat Demonstration Unit (HDU) Project. The HDU Project is designed to develop and test various technologies, configurations, and operational concepts for exploration habitats. This paper describes the HIMS development, initial testing, and HDU integration efforts. Initial tests of the system on the HDU were conducted at NASA?s 2010 Desert Research and Technologies Studies (Desert-RATS). Four sensor locations were assigned near the corners of a rectangular pattern. To study the influence of wall thickness, three sets of four sensors were installed at different layer depths: on the interior of the PEM wall, on the exterior of the same wall, and on the exterior of a layer of foam insulation applied to the exterior wall. Once the system was activated, particle impacts were periodically applied by firing a pneumatic pellet gun at the exterior wall section. Impact signals from the sensors were recognized by a data acquisition system when they occurred, and recorded on a computer for later analysis. Preliminary analysis of the results found that the HIMS system located the point of impact to within 8 cm, provided a measure of the impact energy / damage produced, and was insensitive to other acoustic events. Based on this success, a fully automated version of this system will be completed and demonstrated as part of a crew "Caution/Warning" system at the 2011 Desert-RATS, along with a crew response procedure.

Opiela, J. N.↗
NASA NTRS1993

Effects of atmospheric variations on acoustic system performance

Acoustic propagation over medium to long ranges in the atmosphere is subject to many complex, interacting effects. Of particular interest at this point is modeling low frequency (less than 500 Hz) propagation for the purpose of predicting ranges and bearing accuracies at which acoustic sources can be detected. A simple means of estimating how much of the received signal power propagated directly from the source to the receiver and how much was received by turbulent scattering was developed. The correlations between the propagation mechanism and detection thresholds, beamformer bearing estimation accuracies, and beamformer processing gain of passive acoustic signal detection systems were explored.

Nation, Robert↗