Ecological potentials in spectral signature analysis
Ecological potentials in spectral signature analysis, using laboratory leaf and soil spectral reflectance data
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Ecological potentials in spectral signature analysis, using laboratory leaf and soil spectral reflectance data
Ultrasonic signature analysis shows promise of being a singularly well-suited method for detecting fatigue in structures as complex as aircraft. The method employs instrumentation centered about a Fourier analyzer system, which features analog-to-digital conversion, digital data processing, and digital display of cross-correlation functions and cross-spectra. These features are essential to the analysis of ultrasonic signatures according to the procedure described here. In order to establish the feasibility of the method, the initial experiments were confined to simple plates with simulated and fatigue-induced defects respectively. In the first test the signature proved sensitive to the size of a small hole drilled into the plate. In the second test, performed on a series of fatigue-loaded plates, the signature proved capable of indicating both the initial appearance and subsequent growth of a fatigue crack. In view of these encouraging results it is concluded that the method has reached a sufficiently advanced stage of development to warrant application to small-scale structures or even actual aircraft.
High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.
An analysis is presented for multistage multimesh gear transmission systems. The analysis predicts the overall system dynamics and the transmissibility to the gear box or the enclosed structure. The modal synthesis approach of the analysis treats the uncoupled lateral/torsional model characteristics of each stage or component independently. The vibration signature analysis evaluates the global dynamics coupling in the system. The method synthesizes the interaction of each modal component or stage with the nonlinear gear mesh dynamics and the modal support geometry characteristics. The analysis simulates transient and steady state vibration events to determine the resulting torque variations, speeds, changes, rotor imbalances, and support gear box motion excitations. A vibration signature analysis examines the overall dynamic characteristics of the system, and the individual model component responses. The gear box vibration analysis also examines the spectral characteristics of the support system.
An analysis is presented for multistage multimesh gear transmission systems. The analysis predicts the overall system dynamics and the transmissibility to the gear box or the enclosed structure. The modal synthesis approach of the analysis treats the uncoupled lateral/torsional model characteristics of each stage or component independently. The vibration signature analysis evaluates the global dynamics coupling in the system. The method synthesizes the interaction of each modal component or stage with the nonlinear gear mesh dynamics and the modal support geometry characteristics. The analysis simulates transient and steady state vibration events to determine the resulting torque variations, speeds, changes, rotor imbalances, and support gear box motion excitations. A vibration signature analysis examines the overall dynamic characteristics of the system, and the individual model component responses. The gear box vibration analysis also examines the spectral characteristics of the support system.
The Component-Level Electronic-Assembly Repair (CLEAR) project at the NASA Glenn Research Center is aimed at developing technologies that will enable space-flight crews to perform in situ component-level repair of electronics on Moon and Mars outposts, where there is no existing infrastructure for logistics spares. These technologies must provide effective repair capabilities yet meet the payload and operational constraints of space facilities. Effective repair depends on a diagnostic capability that is versatile but easy to use by crew members that have limited training in electronics. CLEAR studied two techniques that involve extensive precharacterization of "known good" circuits to produce graphical signatures that provide an easy-to-use comparison method to quickly identify faulty components. Analog Signature Analysis (ASA) allows relatively rapid diagnostics of complex electronics by technicians with limited experience. Because of frequency limits and the growing dependence on broadband technologies, ASA must be augmented with other capabilities. To meet this challenge while preserving ease of use, CLEAR proposed an alternative called Complex Signature Analysis (CSA). Tests of ASA and CSA were used to compare capabilities and to determine if the techniques provided an overlapping or complementary capability. The results showed that the methods are complementary.
Successful pulse recording and evaluation is strongly dependent on the instrumentation system selected and the method of analyzing the pulse signature. The paper studies system design, signal analysis techniques, and interdependences with a view toward defining optimal approaches to pulse signal analysis. For this purpose, the instrumentation system is modeled, and analytical pulses, representative of the types of acoustic emissions to be distinguished are passed through the system. Particular attention is given to comparing frequency spectrum analysis and deconvolution referred to as time domain reconstruction of the pulse or pulse train. The possibility of optimal transducer-filter system parameters is investigated. Deconvolution of a pulse is shown to be a superior approach for transient pulse analysis. Reshaping of a transducer output back to the original input pulse is possible and gives an accurate representation of the generating pulse in the time domain. Any definable transducer and filter system can be used for measurement of pulses by means of the deconvolution method. Selection of design variables for general usage is discussed.
Utilizing high-frequency data from a highly instrumented rotor assembly, seeded bearing defect signatures are characterized using both conventional linear approaches, such as power spectral density analysis, and recently developed nonlinear techniques such as bicoherence analysis. Traditional low-frequency (less than 20 kHz) analysis and high-frequency envelope analysis of both accelerometer and acoustic emission data are used to recover characteristic bearing distress information buried deeply in acquired data. The successful coupling of newly developed nonlinear signal analysis with recovered wideband envelope data from accelerometers and acoustic emission sensors is the innovative focus of this research.
The LANDSAT multispectral scanner (MSS) data were analyzed with a view toward classification to identify wheat. The notion of spectral signature of a crop, a commonly used basis for classification, was found to be inadequate. Data analysis has revealed that the MSS data from agricultural sites were essentially two dimensional, and that the data from different sites and different acquisition lay on parallel planes in the four dimensional feature space. These results were exploited to gain new insight into the data and to develop alternate models for classification. In particular, it was found that the temporal pattern of change in the spectral response of a crop constitutes its signature and provides a basis for crop classification.
The Landsat multispectral scanner (MSS) data have been analyzed with a view toward classification to identify wheat. The notion of spectral signature of a crop, a commonly used basis for classification, has been found to be inadequate. Data analysis has revealed that the MSS data from agricultural sites are essentially two dimensional, and that the data from different sites and different acquisitions lie on parallel planes in the four-dimensional feature space. These results have been exploited to gain new insight into the data and to develop alternate models for classification. In particular, it has been found that the temporal pattern of change in the spectral response of a crop constitutes its signature and provides a basis for crop classification.
The goal of this research is to develop a viable NDE technique for the inspection of orbiter thermal protection system (TPS) tile bonds. Phase 2, discussed here, concentrated on developing an empirical understanding of the bonded and unbonded vibration signatures of acreage tiles. Controlled experiments in the laboratory have provided useful information on the dynamic response of TPS tiles. It has been shown that several signatures are common to all the pedigree tiles. This degree of consistency in the tile-SIP (strain isolation pad) dynamic response proves that an unbond can be detected for a known tile and establish the basis for extending the analysis capability to arbitrary tiles for which there are no historical data. The field tests of the noncontacting laser acoustic sensor system, conducted at the Kennedy Space Center (KSC), investigated the vibrational environment of the Orbiter Processing Facility (OPF) and its effect on the measurement and analysis techniques being developed. The data collected showed that for orbiter locations, such as the body flap and elevon, the data analysis scheme, and/or the sensor, will require modification to accommodate the ambient motion. Several methods were identified for accomplishing this, and a solution is seen as readily achievable. It was established that the tile response was similar to that observed in the laboratory. Of most importance, however, is that the field environment will not affect the physics of the dynamic response that is related to bond condition. All of this information is fundamental to any future design and development of a prototype system.
The point-spread function is an important factor in determining the nature of feature types on the basis of multispectral recorded radiance, particularly from heterogeneous scenes and particularly from scenes which are imaged repetitively, in order to provide thematic characterization by means of multitemporal signature. To demonstrate the effect of the interaction of scene heterogeneity with the point spread function (PSF)1, a template was constructed from the line spread function (LSF) data for the thematic mapper photoflight model. The template was in 0.25 (nominal) pixel increments in the scan line direction across three scenes of different heterogeneity. The sensor output was calculated by considering the calculated scene radiance from each scene element occurring between the contours of the PSF template, plotted on a movable mylar sheet while it was located at a given position.
Acoustic emission data were obtained from a series of tensile tests on specially designed graphite-epoxy unidirectional laminates. The design was such that the specimens would preferentially fail first by fiber breakage and later by matrix splitting. The AE signals for each of these events was analyzed and some typical results are reported. Patterns characteristic of each failure mechanism were noted for both the time signatures and the corresponding frequency spectra.
The NASA Orbital Debris Program Office has acquired telescopic lightcurve data on massive intact objects, specifically spent rocket bodies, in order to ascertain tumble rates in support of the Active Debris Removal (ADR) task to help remediate the LEO environment. Rotation rates are needed to plan and develop proximity operations for potential future ADR operations. To better characterize and model optical data acquired from ground-based telescopes, the Optical Measurements Center (OMC) at NASA/JSC emulates illumination conditions in space using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. The OMC employs a 75-watt Xenon arc lamp as a solar simulator, an SBIG CCD camera with standard Johnson/Bessel filters, and a robotic arm to simulate an object's position and rotation. The light source is mounted on a rotary arm, allowing access any phase angle between 0 -- 360 degrees. The OMC does not attempt to replicate the rotation rates, but focuses on how an object is rotating as seen from multiple phase angles. The two targets studied are scaled (1:48), SL-8 Cosmos 3M second stages. The first target is painted in the standard government "gray" scheme and the second target is primary white, as used for commercial missions. This paper summarizes results of the two scaled rocket bodies, each rotated about two primary axes: (a) a spin-stabilized rotation and (b) an end-over-end rotation. The two rotation states are being investigated as a basis for possible spin states of rocket bodies, beginning with simple spin states about the two primary axes. The data will be used to create a database of potential spin states for future works to convolve with more complex spin states. The optical signatures will be presented for specific phase angles for each rocket body and shown in conjunction with acquired optical data from multiple telescope sources.
High altitude analysis of wetland resources and the use of such information in an operational mode to address specific problems of wetland preservation at a state level are discussed. Work efforts were directed toward: (1) developing techniques for using large scale color IR photography in state wetlands mapping program, (2) developing methods for obtaining wetlands ecology information from high altitude photography, (3) developing means by which spectral data can be more accurately analyzed visually, and (4) developing spectral data for automatic mapping of wetlands.
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The feasibility of designing a prediction and warning system for severe weather conditions on the basis of time series analysis and pattern recognition is examined. Data accumulated by Taylor (1972) on the rate of atmospherics produced by severe, tornado-producing storms that struck Oklahoma City during April 1970 are analyzed by time series analysis and pattern recognition. Power spectra, cross-power spectra, coherence functions, and time-varying patterns are analyzed.