Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “automated alignment”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Partial Automated Alignment and Integration System

The present invention is a Partial Automated Alignment and Integration System (PAAIS) used to automate the alignment and integration of space vehicle components. A PAAIS includes ground support apparatuses, a track assembly with a plurality of energy-emitting components and an energy-receiving component containing a plurality of energy-receiving surfaces. Communication components and processors allow communication and feedback through PAAIS.

Kelley, Gary Wayne↗
NASA NTRS1993

Automated Alignment And Inspection Of Duct Welds

Machine vision system being developed for use in aligning ends of two round ducts before welding ends together and inspecting welded ducts for alignment after welding. System makes consistent, objective measurements quickly. Improves quality and reliability of welds, reduces need for rework, and reduces alignment and inspection time, thereby reducing cost of manufacture.

Cross, George S.↗
DOE OSTI2026

Robot-Alignment

Fermilab's SRF Robotics group's automated alignment program. FERMILAB-CODE-2026-03-TD

Giffen, Nickolas [Northern Illinois Univ., DeKalb,↗
NASA NTRS1992

Automation of the targeting and reflective alignment concept

The automated alignment system, described herein, employs a reflective, passive (requiring no power) target and includes a PC-based imaging system and one camera mounted on a six degree of freedom robot manipulator. The system detects and corrects for manipulator misalignment in three translational and three rotational directions by employing the Targeting and Reflective Alignment Concept (TRAC), which simplifies alignment by decoupling translational and rotational alignment control. The concept uses information on the camera and the target's relative position based on video feedback from the camera. These relative positions are converted into alignment errors and minimized by motions of the robot. The system is robust to exogenous lighting by virtue of a subtraction algorithm which enables the camera to only see the target. These capabilities are realized with relatively minimal complexity and expense.

Redfield, Robin C.↗
NASA NTRS1999

A new version of the RDP (Ribosomal Database Project)

The Ribosomal Database Project (RDP-II), previously described by Maidak et al. [ Nucleic Acids Res. (1997), 25, 109-111], is now hosted by the Center for Microbial Ecology at Michigan State University. RDP-II is a curated database that offers ribosomal RNA (rRNA) nucleotide sequence data in aligned and unaligned forms, analysis services, and associated computer programs. During the past two years, data alignments have been updated and now include >9700 small subunit rRNA sequences. The recent development of an ObjectStore database will provide more rapid updating of data, better data accuracy and increased user access. RDP-II includes phylogenetically ordered alignments of rRNA sequences, derived phylogenetic trees, rRNA secondary structure diagrams, and various software programs for handling, analyzing and displaying alignments and trees. The data are available via anonymous ftp (ftp.cme.msu. edu) and WWW (http://www.cme.msu.edu/RDP). The WWW server provides ribosomal probe checking, approximate phylogenetic placement of user-submitted sequences, screening for possible chimeric rRNA sequences, automated alignment, and a suggested placement of an unknown sequence on an existing phylogenetic tree. Additional utilities also exist at RDP-II, including distance matrix, T-RFLP, and a Java-based viewer of the phylogenetic trees that can be used to create subtrees.

Non-NASA Center↗
NASA NTRS2010

SCDU Testbed Automated In-Situ Alignment, Data Acquisition and Analysis

In the course of fulfilling its mandate, the Spectral Calibration Development Unit (SCDU) testbed for SIM-Lite produces copious amounts of raw data. To effectively spend time attempting to understand the science driving the data, the team devised computerized automations to limit the time spent bringing the testbed to a healthy state and commanding it, and instead focus on analyzing the processed results. We developed a multi-layered scripting language that emphasized the scientific experiments we conducted, which drastically shortened our experiment scripts, improved their readability, and all-but-eliminated testbed operator errors. In addition to scientific experiment functions, we also developed a set of automated alignments that bring the testbed up to a well-aligned state with little more than the push of a button. These scripts were written in the scripting language, and in Matlab via an interface library, allowing all members of the team to augment the existing scripting language with complex analysis scripts. To keep track of these results, we created an easily-parseable state log in which we logged both the state of the testbed and relevant metadata. Finally, we designed a distributed processing system that allowed us to farm lengthy analyses to a collection of client computers which reported their results in a central log. Since these logs were parseable, we wrote query scripts that gave us an effortless way to compare results collected under different conditions. This paper serves as a case-study, detailing the motivating requirements for the decisions we made and explaining the implementation process.

Automation↗
NASA NTRS2008

An Automated SVD for Alignment and Control of James Webb Space Telescope Mirrors

The James Webb Space Telescope (JWST) is a three-mirror anastigmatic telescope. The alignment of the segmented primary and secondary mirrors in the wavefront sensing and control process involves a series of actuators to control the six degrees-of-freedom motion on each surface in addition to the radius of curvature. The control matrix developed from the alignment parameters is over-determined and singular value decomposition (SVD) method is used to solve it in the least square sense. An automated SVD scheme has been developed to identify the most contributing modes in a typical alignment process and reduce the impact of error-prone modes from the control process.

Shiri, Sharam↗
NASA NTRS1991

Neural nets for aligning optical components in harsh environments: Beam smoothing spatial filter as an example

The goal is to develop an approach to automating the alignment and adjustment of optical measurement, visualization, inspection, and control systems. Classical controls, expert systems, and neural networks are three approaches to automating the alignment of an optical system. Neural networks were chosen for this project and the judgements that led to this decision are presented. Neural networks were used to automate the alignment of the ubiquitous laser-beam-smoothing spatial filter. The results and future plans of the project are presented.

Decker, Arthur J.↗
DOE OSTI2025

Cyber Knowledge Alignment

An automated workflow and introduces new approaches to curate existing cybersecurity knowledge from multiple sources. It also proposes AI/ML-based methods to infer knowledge alignments across different repositories.

Purohit, Sumit [Pacific Northwest National Laborat↗
NASA NTRS1993

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Decker, Arthur J.↗
NASA NTRS2010

Aligning Astronomical Telescopes via Identification of Stars

A proposed method of automated, precise alignment of a ground-based astronomical telescope would eliminate the need for initial manual alignment. The method, based on automated identification of known stars and other celestial objects in the telescope field of view, would also eliminate the need for an initial estimate of the aiming direction. The method does not require any equipment other than a digital imaging device such as a charge-coupled-device digital imaging camera and control computers of the telescope and camera, all of which are standard components in professional astronomical telescope systems and in high-end amateur astronomical telescope systems. The method could be implemented in software running in the telescope or camera control computer or in an external computer communicating with the telescope pointing mount and camera control computers.

Whorton, Mark↗
NASA NTRS1992

Self-Aligning Optical Measurement Systems

The paper discusses how to teach a system of neural networks to respond to the alignment clues used by a human operator in performing routine, initial alignments. A paradigm is proposed for automating the alignment of the components of optical measurement systems. The paradigm which was tested on a spatial filter has proved to be successful for optical alignment.

Decker, Arthur J.↗
NASA NTRS1972

An automated system for the alignment of large area modular solar simulators

A real-time optical alignment and diagnostic system is being assembled for installation at the Space Environment Simulation Laboratory. This system will be used to measure and analyze the performance of optical components, assemblies, and full modules. This information, in turn, is used to align assemblies and modules. The system capability includes such functions as the generation and updating of a catalog, which serves as permanent record, in addition to providing the capability to predict in-chamber performance of optics combinations before they are mounted in the chamber.

Vincent, J. P.↗
NASA NTRS2023

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗
NASA NTRS2023

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗
NASA NTRS1972

Automated cloud tracking using precisely aligned digital ATS pictures.

Discussion of the interactive man-computer system (WIMDCO) for measuring cloud motion from ATS pictures. The multipicture model of ATS navigation is used for consecutive ATS digital picture alignment to provide the required precision in cloud motion measurements by automated tracking techniques. Cloud motion is measured by tracking clouds between two digital pictures with the aid of two-dimensional cross correlation analysis. The fast Fourier transform method and other programming techniques are used for time and cost minimization. Cloud motion vectors were computed over three time intervals in July, 1969. The EW and NS components were reproducible within roughly 2 knots.

Smith, E. A.↗