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At least 37 records · Page 2

Formulations and applications of large structure actuator and sensor placements

A new approach based on the steady-state solutions of the optimal control and estimation problems is presented to study respectively the actuator and sensor locations for large flexible structures. A simple and computer-implementable formulation for minimizing the steady state optimal cost function and the state estimation error inherent in the estimation process is given. In conjunction with the new approach, two criteria are established relating the actuator and the sensor placement optimalities respectively to the minimums of the optimal cost function and the state estimation error. To illustrate the concepts of this paper, we present the results of some numerical and analytical studies on the actuator and the sensor locations of several simple flexible beam modes.

Juang, J.-N.↗

Evaluation of sensor placement algorithms for on-orbit identification of space platforms

Anticipating the construction of the international space station, on-orbit modal identification of space platforms through optimally placed accelerometers is an area of recent activity. Unwanted vibrations in the platform could affect the results of experiments which are planned. Therefore, it is important that sensors (accelerometers) be strategically placed to identify the amount and extent of these unwanted vibrations, and to validate the mathematical models used to predict the loads and dynamic response. Due to cost, installation, and data management issues, only a limited number of sensors will be available for placement. This work evaluates and compares four representative sensor placement algorithms for modal identification. Most of the sensor placement work to date has employed only numerical simulations for comparison. This work uses experimental data from a fully-instrumented truss structure which was one of a series of structures designed for research in dynamic scale model ground testing of large space structures at NASA Langley Research Center. Results from this comparison show that for this cantilevered structure, the algorithm based on Guyan reduction is rated slightly better than that based on Effective Independence.

Glassburn, Robin S.↗

Sensor Placement Optimization Study for the Built Environment: Operational Use Cases

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear and radiological incidents. State, local, tribal, and territorial (SLTT) government agencies that implement systems of fixed-position sensors are faced with numerous decisions regarding sensor selection, quantity, and placement. To develop guidance on implementation of radiation detection systems, we simulated the release of radioactive material in an urban environment using a combination of three models: the Weather Research Forecasting (WRF), Quick Urban and Industrial Complex (QUIC), and Monte Carlo N-Particle (MCNP) models. We then evaluated the performance of several hypothetical sensor systems. The small number of simulations we conducted are not sufficient to generate definitive design guidance for radiation sensor systems, but we did identify trends that would be of interest to emergency planners. For a scenario that releases 1000 curies of Cs-137, radiation detectors were needed at 500-meter intervals to have a high likelihood of event detection and to estimate source location and plume detection. We also noted that optimal detector altitude varied with distance to the source. We recommend additional research in this area be conducted to support developing sensor placement guidelines that expand on a range of locations, isotopes, activity levels, and different weather conditions. Original simulation strategies included a range of environments, additional radioisotopes (Am241 and AmBe), and a larger selection of sensor types. These types of expansions would support SLTT guidance on sensor system recommendations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing

Deciding how to optimally deploy sensors in a large, complex, and spatially extended structure is critical to ensure that the surface pressure field is accurately captured for subsequent analysis and design. In some cases, reconstruction of missing data is required in downstream tasks such as the development of digital twins. Here, this paper presents a data-driven sparse sensor selection algorithm, aiming to provide the most information contents for reconstructing aerodynamic characteristics of wind pressures over tall building structures parsimoniously. The algorithm first fits a set of basis functions to the training data, then applies a computationally efficient QR algorithm that ranks existing pressure sensors in order of importance based on the state reconstruction to this tailored basis. The findings of this study show that the proposed algorithm successfully re- constructs the aerodynamic characteristics of tall buildings from sparse measurement locations, generating stable and optimal solutions across a range of conditions. As a result, this study serves as a promising first step toward leveraging the success of data-driven and machine learning algorithms to supplement traditional genetic algorithms currently used in wind engineering.

42 ENGINEERING↗

Sensor Placement Optimization Study for the Built Environment: Next Steps Report

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear incidents. First responder organizations that implement systems of fixed-position sensors face numerous decisions regarding sensor selection, quantity, and placement. Researchers at Pacific Northwest National Laboratory (PNNL) have evaluated the performance of several hypothetical sensor systems during a simulated activation of a radiological dispersal device. Due to technical limitations, PNNL’s analysis was limited to a single location and number of scenarios. This document describes additional research and analysis that would result in improved guidance to first responder organizations considering installation of radiation monitoring systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimization of actuator and sensor placement for on-orbit identification in large flexible spacecraft

There has been considerable research on choosing actuator and sensor locations in large flexible spacecraft in order to optimize the controllability and observability of the system, or to maximize some objective function of control system performance. Future large flexible spacecraft may require on-orbit identification of the structure to tune the control system, because such tests cannot be performed in a one-g environment before launch. This indicates that the choice of actuator and sensor locations must serve a dual purpose, for control and for identification. This paper develops concepts for a degree of identifiability and studies placement of actuators and sensors on a free-free beam to optimize such objective functions. The results in this simple situation suggest that in free-free spacecraft structures in orbit, placement for control and placement for identification may often be consistent objectives rather than conflicting objectives.

Bergmann, Martin↗

A method for optimal actuator and sensor placement for large flexible structures

A method of finding the optimal sensor and actuator locations for the control of flexible structures has been developed. The method is based on the orthogonal projection of structural modes into the intersection subspace of the controllable and observable subspaces. The controllability and observability grammians are then used to weight the projections to reflect the degrees of controllability and observability. This method produces a three-dimensional design space wherein sets of optimal actuator and sensors may be selected.

Lim, K. B.↗

The Alpha-Proton-X-ray Spectrometer deployment mechanism: An anthropomorphic approach to sensor placement on Martian rocks and soil

On July 4,1997, the Mars Pathfinder spacecraft lands on Mars and starts conducting technological and scientific experiments. One experiment, the Alpha-Proton-X-ray Spectrometer, uses a sensor head placed against rocks and soil to determine their composition. To guarantee proper placement, a deployment mechanism mounted on the Mars Rover aligns the sensor head to within 20 deg of the rock and soil surfaces. In carrying out its task, the mechanism mimics the action of a human hand and arm. Consisting of a flexible wrist, a parallel link arm, a brush dc motor actuator, and a revolutionary non-pyrotechnic fail-safe release device, the mechanism correctly positions the sensor head on rocks as high as 0.29 m and on targets whose surfaces are tilted as much as 45 deg from the nominal orientation of the sensor head face. The mechanism weighs less than 0.5 kg, can withstand 100 g's, and requires less than 2.8 N x m of actuation torque. The fail-safe coupler utilizes Cerrobend, a metal alloy that melts at 60 C, to fuse the actuator and the rest of the mechanism together. A film heater wrapped around the coupler melts the metal, and Negator springs drive the mechanism into its stowed position. The fail-safe actuates using 6.75 Watts for 5 minutes in the event of an actuator failure.

Blomquist, Richard S.↗

Journey over Destination: Dynamic Sensor Placement Enhances Generalization

Reconstructing complex, high-dimensional global fields from limited data points is a challenge across various scientific and industrial domains. This is particularly important for recovering spatio-temporal fields using sensor data from, for example, laboratory-based scientific experiments, weather forecasting, or drone surveys. Given the prohibitive costs of specialized sensors and the inaccessibility of
certain regions of the domain, achieving full field coverage is typically not feasible. Therefore, the development of machine learning algorithms trained to reconstruct fields given a limited dataset is of critical importance. In this study, we introduce a general
approach that employs moving sensors to enhance data exploitation during the training of an attention based neural network, thereby improving field reconstruction. The training of sensor locations is accomplished using an end-to-end workflow, ensuring
differentiability in the interpolation of field values associated to the sensors, and is simple to implement using differentiable programming. Additionally, we have incorporated a correction mechanism to prevent sensors from entering invalid regions within the domain. We evaluated our method using two distinct datasets; the results show that our approach enhances learning, as evidenced by improved test scores.

54 ENVIRONMENTAL SCIENCES↗

Sensor placement for on-orbit modal testing

A systematic procedure of placing accelerometers for the on-orbit modal identification of large flexible space structures is addressed. Target modes for modal testing are selected by examining the modal cost of each mode. Assuming that a time-domain modal identification algorithm such as Eigensystem Realization Algorithm is employed to identify the modes from measured time response data, the sensors are placed to ensure the recovery of the target modes. As an application example of the procedure, an accelerometer placement study for the Space Station Freedom On-Orbit Modal Identification Experiment is presented.

Lim, Tae W.↗

(abstract) The Alpha-Proton-X-ray Spectrometer Deployment Mechanism -- An Anthropomorphic Approach to Sensor Placement on Martian Rocks and Soil

The Mars Pathfinder mission promises to reap a harvest of geological information about Mars. One of the nearly half dozen instruments making this science data possible is the alpha proton X ray spectrometer (APXS). Using a curium source and backscattering techniques, the APXS will determine the elemental composition of rocks and the soil around the landing site. To ensure information of high fidelity, the APXS sensor face must be aligned to within 20° to the surface of each rock and soil sampling location and be held there for up to 10 hours. This is accomplished through the anthropomorphic deployment mechanism (ADM). The ADM mounts on the back of the Mars rover. Working with the rover, the ADM both actively and passively positions the APXS sensor head against a chosen target. The ADM is an amalgamation of unique solutions to some very challenging design problems. The resulting design is light, flexible, and nearly autonomous. Its straightforward operation rivals that of the human arm in simplicity and elegance.

Mars↗