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Automatic method for selection of proper guard band eliminates human error and speeds up calibration process. There is also an option which allows a single channel to be calibrated, independently of other channels. Entire system is designed on 3- by 4-inch printed-circuit cards and may be used with any pulse code modulation system.
A system for automatically calibrating the accuracy of a flowmeter is described. The system includes a calculator capable of performing mathematical functions responsive to receiving data signals and function command signals. A prover cylinder is provided for measuring the temperature, pressure, and time required for accumulating a predetermined volume of fluid. Along with these signals, signals representing the temperature and pressure of the fluid going into the meter are fed to a plurality of data registers. Under control of a progress controller, the data registers are read out and the information is fed through a data select circuit to the calculator. Command signals are also produced by a function select circuit and are fed to the calculator set indicating the desired function to be performed. The reading is then compared with the reading produced by the flowmeter.
Automatic Digital Noise Checker determines the noise content of the many analog imputs of a data acquisition system and whether the Electronic Calibrations /EC/ on some data channels are operating properly.
The NASA Langley Research Center (LARC) participated in a national cooperative evaluation of the Israel Aircraft Industries (IAI) automatic balance calibration machine at Microcraft, San Diego in September 1995. A LaRC-designed six-component strain gauge balance was selected for test and calibration during LaRC's scheduled evaluation period. Eight calibrations were conducted using three selected experimental designs. Raw data were exported to LaRC facilities for reduction and statistical analysis using the techniques outlined in Tripp and Tcheng (1994). This report presents preliminary assessments of the results, and compares IAI calibration results with manual calibration results obtained at the Modern Machine and Tool Co., Inc. (MM & T). Newport News, VA. A more comprehensive report is forthcoming.
A system for automatically calibrating force balances is provided. The invention uses a reference balance aligned with the balance being calibrated to provide superior accuracy while minimizing the time required to complete the calibration. The reference balance and the test balance are rigidly attached together with closely aligned moment centers. Loads placed on the system equally effect each balance, and the differences in the readings of the two balances can be used to generate the calibration matrix for the test balance. Since the accuracy of the test calibration is determined by the accuracy of the reference balance and current technology allows for reference balances to be calibrated to within +/-0.05% the entire system has an accuracy of +/-0.2%. The entire apparatus is relatively small and can be mounted on a movable base for easy transport between test locations. The system can also accept a wide variety of reference balances, thus allowing calibration under diverse load and size requirements.
A system for automatically calibrating force balances is provided. The invention uses a reference balance aligned with the balance being calibrated to provide superior accuracy while minimizing the time required to complete the calibration. The reference balance and the test balance are rigidly attached together with closely aligned moment centers. Loads placed on the system equally effect each balance, and the differences in the readings of the two balances can be used to generate the calibration matrix for the test balance. Since the accuracy of the test calibration is determined by the accuracy of the reference balance and current technology allows for reference balances to be calibrated to within .+-.0.05%, the entire system has an accuracy of a .+-.0.2%. The entire apparatus is relatively small and can be mounted on a movable base for easy transport between test locations. The system can also accept a wide variety of reference balances, thus allowing calibration under diverse load and size requirements.
A method is described for calibrating cameras including radial lens distortion, by using known points such as those measured from a calibration fixture. The distortion terms are relative to the optical axis, which is included in the model so that it does not have to be orthogonal to the image sensor plane.
Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance of traditional computer vision techniques developed for electro-optical imagery does not directly translate to the thermal domain due to two major reasons: these algorithms require photometric assumptions to hold, and methods for photometric calibration of RGB cameras cannot be applied to thermal-infrared cameras due to difference in data acquisition and sensor phenomenology. In this paper, we take a step in this direction, and introduce a novel algorithm for online photometric calibration of thermalinfrared cameras. Our proposed method does not require any specific driver/hardware support and hence can be applied to any commercial off-the-shelf thermal IR camera. We present this in the context of visual odometry and SLAM algorithms, and demonstrate the efficacy of our proposed system through extensive experiments for both standard benchmark datasets, and real-world field tests with a thermal-infrared camera in natural outdoor environments.
Illustrations in this view-graph presentation are presented on a Bayesian approach to 3D surface reconstruction and camera calibration.Existing methods, surface analysis and modeling,preliminary surface reconstruction results, and potential applications are addressed.
An automatic calibration system was designed for use in the vacuum facility at the Space Science Laboratory of the Marshall Space Flight Center. That system was developed and used in the intervening winter to calibrate the ion spectrometer that eventually flew in May 1986 aboard the NASA project, CRIT 1. During this summer, it is planned to implement the calibration of both an ion and electron spectrometer of a new design whose basic elements were conceived during the winter of 1985 to 1986. This spectrometer was completed in the summer and successfully mounted in the vacuum tank for calibration. However, the source gate valve malfunctioned, and, at the end of the summer, it still needed a replacement. During the inevitable delays in the experimental research, the numerical model of the Critical Velocity effect was completed and these results were presented.
The work reported here demonstrates how to automatically compute the position and attitude of a targeting reflective alignment concept (TRAC) camera relative to the robot end effector. In the robotics literature this is known as the sensor registration problem. The registration problem is important to solve if TRAC images need to be related to robot position. Previously, when TRAC operated on the end of a robot arm, the camera had to be precisely located at the correct orientation and position. If this location is in error, then the robot may not be able to grapple an object even though the TRAC sensor indicates it should. In addition, if the camera is significantly far from the alignment it is expected to be at, TRAC may give incorrect feedback for the control of the robot. A simple example is if the robot operator thinks the camera is right side up but the camera is actually upside down, the camera feedback will tell the operator to move in an incorrect direction. The automatic calibration algorithm requires the operator to translate and rotate the robot arbitrary amounts along (about) two coordinate directions. After the motion, the algorithm determines the transformation matrix from the robot end effector to the camera image plane. This report discusses the TRAC sensor registration problem.
Systems and reliability engineering for automatic pressure transducer calibration system
A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.
A self-calibrating, remote programmable signal conditioning amplifier system employs information read from a memory attached to a measurement transducer for automatic calibration. The signal conditioning amplifier is self-calibrated on a continuous basis through use of a dual input path arrangement, with each path containing a multiplexer and a programmable amplifier. A digital signal processor controls operation of the system such that a transducer signal is applied to one of the input paths, while one or more calibration signals are applied to the second input path. Once the second path is calibrated, the digital signal processor switches the transducer signal to the second path. and then calibrates the first path. This process is continually repeated so that each path is calibrated on an essentially continuous basis. Dual output paths are also employed which are calibrated in the same manner. The digital signal processor also allows the implementation of a variety of digital filters which are either programmed into the system or downloaded by an operator, and performs up to eighth order linearization.
Qualification and certification of safety critical parts is a hurdle to the adoption of metallic additively manufactured components for aerospace vehicle applications. Challenges include variability in part properties due to inconsistent defect distribution and microstructure. Understanding of the process through finite element modeling (FEM), and process control through in-situ monitoring, may result in significant improvements; however, solutions useful to manufacturers will require large volumes of data and automated data utilization. Toward this end, a generalizable automated FEM calibration paradigm is developed. This paradigm leverages existing and novel tools from machine learning and uncertainty quantification to enable the automatic calibration of FEMs without requiring prior knowledge of the model performance across input parameter space, including meshing and solver settings, which can require time consuming manual model probing or cause noisy and inconsistent predictions. The result is a probabilistic distribution of calibrated and validated FEM input parameters targeting measured data.
In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.
A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least-squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 Goddard Earth Model-T1 (GEM-T1) were employed toward application of this technique for gravity field parameters. Also GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized. The method employs subset solutions of the data associated with the complete solution to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.
A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 (Goddard Earth Model, 36x36 spherical harmonic field) were employed toward application of this technique for gravity field parameters. Also, GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized here. The method employs subset solutions of the data associated with the complete solution and uses an algorithm to adjust the data weights by requiring the differences of parameters between solutions to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting as compared to the nominal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.