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Identification breakdown chart that lists the component parts required for any specific end item is used to identify rapidly and accurately, from numerous drawings, all the component parts of a complex design assembly. Cylindrical and complex configurations are depicted as continuous flat surfaces for ready identification.
Pattern recognition techniques applied to process identification, examining capability of mode learning machines for on-line identification of both linear and nonlinear processes
Ordered qualitative test sequence, presented in flow chart form, permits identification of all common metallurgical elements and many high-temperature, stainless, high and low carbon, and tool steels within about 30 minutes. Identification is made from colors or specific reactions produced by the addition of standard chemical reagents.
A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.
Algorithms for failure detection and identification for redundant noncolinear arrays of single degree of freedom gyros and accelerometers are described. These algorithms are optimum in the sense that detection occurs as soon as it is no longer possible to account for the instrument outputs as the outputs of good instruments operating within their noise tolerances, and identification occurs as soon as it is true that only a particular instrument failure could account for the actual instrument outputs within the noise tolerance of good instruments. An estimation algorithm is described which minimizes the maximum possible estimation error magnitude for the given set of instrument outputs. Monte Carlo simulation results are presented for the application of the algorithms to an inertial reference unit consisting of six gyros and six accelerometers in two alternate configurations.
Program coordination activities were shifted from the Space Oceanography Program of NAVOCEANO to the National Environmental Satellite Service as part of NOAA in October 1970. Program activities in remote sensing continued in the development of low-light-level image intensifiers, spectrometers, aerial photography, and lasers for the location, identification, and quantification of living marine resources at or near the sea surface. Other studies included the development of a biologically controlled impoundment for remote sensor investigations and limited activities in fish oil film research. In addition to these remote sensing studies, the National Marine Fisheries Service (NMFS) program at the Mississippi Test Facility is participating in space oceanography studies related to fisheries and in the ERTS-A and Skylab experiments. Aspects of the NMFS program related to fisheries resource identification and assessment during the period 1970 and 1971 are discussed.
Study of solvent extractable acidic constituents of oil shale from the Colorado Green River Formation. Identification of individual components is based on gas chromatographic and mass spectrometric data obtained for their respective methyl esters. Normal acids, isoprenoidal acids, alpha, omega-dicarboxylic acids, mono-alpha-methyl dicarboxylic acids and methyl ketoacids were identified. In addition, the presence of monocyclic, benzoic, phenylalkanoic and naphthyl-carboxylic acids, as well as cycloaromatic acids, is demonstrated by partial identification.
A parameter identification method is presented which combines the best features of two well-established, existing methods: Continuous Parameter Tracking and Acceleration Search (Partan). In this paper the equations are developed for the general n-parameter identification problem, and results are given for a specific two parameter application.
An algorithm for failure detection and identification for redundant non-orthogonal arrays of single degree of freedom gyros and accelerometers is described which is optimum in the sense that detection occurs as soon as it is no longer possible to account for the instrument outputs as the outputs of good instruments operating within their noise tolerances, and identification occurs as soon as it is true that only a particular instrument failure could account for the actual instrument outputs within the noise tolerance of good instruments. An estimation algorithm is described which minimizes the maximum possible error magnitude for the given set of instrument outputs. Monte Carlo simulation results are presented for the application of the algorithms to an inertial reference unit consisting of six gyros and six accelerometers in two alternate configurations.
A series of photographic, photoelectric, and spectroscopic observations beginning June 1, 1972 has led to the optical identification of Her X-1 (2U 1705 + 34), a pulsed X-ray source in an eclipsing binary system, with the thirteenth magnitude blue variable star HZ Herculis. The detection of optical pulses at the frequency of the X-ray pulsar on three nights makes the identification conclusive and establishes HZ Her as the second known optical pulsar. The strength of the optical pulses may be correlated with the orbital phase but is not obviously related to the high or low intensity states of the X-ray source.
A laboratory study was undertaken to provide simplified procedures leading to the presumptive identification (I/D) of defined microorganisms on-board an orbiting spacecraft. Identifications were to be initiated by nonprofessional bacteriologists, (crew members) on a contingency basis only. Key objectives/constraints for this investigation were as follows:(1) I/D procedures based on limited, defined diagnostic tests, (2) testing oriented about ten selected microorganisms, (3) provide for definitive I/D key and procedures per selected organism, (4) define possible occurrences of false positives for the resulting I/D key by search of the appropriate literature, and (5) evaluation of the I/D key and procedure through a limited field trial on randomly selected subjects using the I/D key.
A new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion. It is shown that this new method is capable of processing data from both linear and nonlinear models, both with and without process noise and includes output error and equation error methods as special cases. The first application of this method to flight test data is reported for lateral maneuvers of the HL-10 and M2/F3 lifting bodies, including the extraction of stability and control derivatives in the presence of wind gusts. All the problems encountered in this identification study are discussed. Several different methods (including a priori weighting, parameter fixing and constrained parameter values) for dealing with identifiability and uniqueness problems are introduced and the results given. The method for the design of optimal inputs for identifying the parameters of linear dynamic systems is also given. The criterion used for the optimization is the sensitivity of the system output to the unknown parameters. Several simple examples are first given and then the results of an extensive stability and control dervative identification simulation for a C-8 aircraft are detailed.
The Apollo 16 panoramic camera photographed the impact locations of the Ranger 7 and 9 spacecraft and the S-4B stage of the Apollo 14 Saturn launch vehicle. Identification of the Ranger craters was very simple because each photographed its target point before impact. Identification of the S-4B impact crater proved to be a simple matter because the impact location, as derived from earth-based tracking, displayed a prominent and unique system of mixed light and dark rays. By using the criterion of a dark ray pattern, a reexamination of the Apollo 14 500 mm Hasselblad sequence taken of the Apollo 13 S-4B impact area was made. This examination quickly led to the discovery of the ray system and the impact crater. The study of artificial lunar impact craters, ejecta blankets, and ray systems provides the long-needed link between the various experimental terrestrial impact and explosion craters, and the naturally occurring impact craters on the moon. This elementary study shows that lunar impact crater diameters are closely predictable from a knowledge of the energies involved, at least in the size range considered, and suggests that parameters, such as velocity, may have a profound effect on crater morphology and ejecta blanket albedo.
The adaptive control and identification problems for single input, single output, time invariant systems with unknown parameters are considered here. A model reference is used and Liapunov's direct method provides the mechanisms for deriving the adaptive and identification algorithms. The Kalman Lemma (derived in connection with the Lure' problem) is shown to be extremely helpful in the design of these systems.
Minimax algorithms for failure detection and identification for redundant noncolinear arrays of single-degree-of-freedom gyros and accelerometers are described. These algorithms are optimum in the sense that detection occurs as soon as it is no longer possible to account for the instrument outputs as the outputs of good instruments operating within their noise tolerances, and identification occurs as soon as it is true that only a particular instrument failure could account for the actual instrument outputs within the noise tolerance of good instruments. An estimation algorithm is described which minimizes the maximum possible estimation error magnitude for the given set of instrument outputs. Monte Carlo simulation results are presented for the application of the algorithms to an inertial reference unit consisting of six gyros and six accelerometers in two alternate configurations.
System identification methods have been applied to rotorcraft to estimate stability derivatives from transient flight control response data. While these applications assumed a linear constant coefficient representation of the rotorcraft, the computer experiments used transient responses in flap-bending and torsion of a rotor blade at high advance ratio which is a rapidly time varying periodic system. It was found that a simple system identification method applying a linear sequential estimator also called least square estimator or equation of motion estimator, is suitable for this periodic system and can be used directly if only the acceleration data are noise polluted. In the case of noise being present also in the state variable data the direct application of the estimator gave poor results.
The application of the maximum likelihood identification technique to M2/F3 lifting body flight data containing wind gust effects is discussed. With the objective of this effort being the identification of the stability and control derivatives, it is shown first that the output error technique (or modified Newton-Raphson) fails to fit the recorded data accurately. The means of applying the maximum likelihood technique to this problem are then discussed and the results given which indicate an accurate fit to the data. The question of derivative signs opposite to the wind tunnel values is then addressed and the results of three techniques for dealing with this problem are presented. These techniques are a priori weighting, fixing parameter values, and rank deficient inverses.
The growth of the field of system identification is discussed along with changes in methodology which have taken place in recent years. The similarity between pattern recognition and system identification is pointed out, involving the modelling in the latter and the feature selection problem in the former. It is stated that once a model is formulated, including the disturbances and measurement errors, the parameter finding can be formulated as a statistical estimation problem. The various techniques and their application are discussed.