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1
Abel, Mark G., Nicole Peritore, Robert Shapiro, David R. Mullineaux, Kelly Rodriguez, and James C. Hannon. "A comprehensive evaluation of motion sensor step-counting error." Applied Physiology, Nutrition, and Metabolism 36, no. 1 (January 2011): 166–70. http://dx.doi.org/10.1139/h10-095.
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The purpose of this study was to conduct a comprehensive evaluation of the effect that walking speed, gender, leg length, motion sensor tilt angle, brand, and placement have on motion sensor step-counting error. Fifty-nine participants performed treadmill walking trials at 6 speeds while wearing 5 motion sensor brands placed on the anterior (Digiwalker, DW; Walk4Life, WFL; New Lifestyles, NL; Omron, OM), midaxillary (DW; WFL; NL; ActiGraph, AG), and posterior (DW, WFL, NL) aspects of the waistline. The anterior-placed NL and midaxillary-placed AG were the most accurate motion sensors. Motion sensor step-count error tended to decrease at faster walking speeds, with lesser tilt angles, and with an anterior waistline placement. Gender and leg length had no effect on motion sensor step-count error. We conclude that the NL and AG yielded the most accurate step counts at a range of walking speeds in individuals with different physical characteristics.
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Zhou, Jinzhu, Zhiheng Cai, Pengbing Zhao, and Baofu Tang. "Efficient Sensor Placement Optimization for Shape Deformation Sensing of Antenna Structures with Fiber Bragg Grating Strain Sensors." Sensors 18, no. 8 (August 1, 2018): 2481. http://dx.doi.org/10.3390/s18082481.
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This paper investigates the problem of an optimal sensor placement for better shape deformation sensing of a new antenna structure with embedded or attached Fiber Bragg grating (FBG) strain sensors. In this paper, the deformation shape of the antenna structure is reconstructed using a strain–displacement transformation, according to the measured discrete strain data from limited FBG strain sensors. Moreover, a two-stage sensor placement method is proposed using a derived relative reconstruction error equation. In this method, the initial sensor locations are determined using the principal component analysis based on orthogonal trigonometric (i.e., QR) decomposition, and then a new location is sequentially added into the initial sensor locations one by one by minimizing the relative reconstruction error considering information redundancy. The numerical simulations are conducted, and the comparisons show that the proposed method is advantageous in terms of the sensor distribution and computational cost. Experimental validation is performed using an antenna experimental platform equipped with an optimal FBG strain sensor configuration, and the reconstruction results show good agreements with those measured directly from displacement sensors. The proposed method has a large potential for the strain sensor placement of complex structures, and the proposed antenna structure with FBG strain sensors can be applied to the future wing-skin antenna or flexible space-based antenna.
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Lin, Cheng-Wu, Shanq-Jang Ruan, Wei-Chun Hsu, Ya-Wen Tu, and Shao-Li Han. "Optimizing the Sensor Placement for Foot Plantar Center of Pressure without Prior Knowledge Using Deep Reinforcement Learning." Sensors 20, no. 19 (September 29, 2020): 5588. http://dx.doi.org/10.3390/s20195588.
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We study the foot plantar sensor placement by a deep reinforcement learning algorithm without using any prior knowledge of the foot anatomical area. To apply a reinforcement learning algorithm, we propose a sensor placement environment and reward system that aims to optimize fitting the center of pressure (COP) trajectory during the self-selected speed running task. In this environment, the agent considers placing eight sensors within a 7 × 20 grid coordinate system, and then the final pattern becomes the result of sensor placement. Our results show that this method (1) can generate a sensor placement, which has a low mean square error in fitting ground truth COP trajectory, and (2) robustly discovers the optimal sensor placement in a large number of combinations, which is more than 116 quadrillion. This method is also feasible for solving different tasks, regardless of the self-selected speed running task.
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Tian, Hongxian, Mary Weitnauer, and Gedeon Nyengele. "Optimized Gateway Placement for Interference Cancellation in Transmit-Only LPWA Networks." Sensors 18, no. 11 (November 11, 2018): 3884. http://dx.doi.org/10.3390/s18113884.
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We study the placement of gateways in a low-power wide-area sensor network, when the gateways perform interference cancellation and when the model of the residual error of interference cancellation is proportional to the power of the packet being canceled. For the case of two sensor nodes sending packets that collide, by which we mean overlap in time, we deduce a symmetric two-crescent region wherein a gateway can decode both collided packets. For a large network of many sensors and multiple gateways, we propose two greedy algorithms to optimize the locations of the gateways. Simulation results show that the gateway placements by our algorithms achieve lower average contention, which means higher packet delivery ratio in the same conditions, than when gateways are naively placed, for several area distributions of sensors.
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Oh, Dong Ho, and Shiao Hua Chen. "Robust Sensor Placement to Measurement Noise for Structural Dynamic Systems." Solid State Phenomena 120 (February 2007): 247–54. http://dx.doi.org/10.4028/www.scientific.net/ssp.120.247.
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Performance of experimental dynamic system identification depends on sensor placement especially when the number of sensor locations is relatively small and measurement noise is significant. We propose a method to select robust measurements based on the estimation error in modal analysis, which is one of the most popular system identification methods for dynamic systems, by defining a measure of the estimation. The measure is developed to deal with various types of sensors and with general damped systems. It is calculated from the eigenvector information obtained by finite element analysis or preliminary experiments and represents the weighted covariance of estimation error induced by measurement noise as well as the orthogonality of the projection matrix which is the corresponding submatrix of eigenvector-matrix by partially measured outputs. Effectiveness of the proposed measurement selection schemes is demonstrated by computer simulations and experiments.
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Tran, Chau M., and Steve C. Southward. "A Sensor Placement Strategy for the Hybrid Adaptive Feedforward Observer." Journal of Dynamic Systems, Measurement, and Control 128, no. 2 (February 20, 2005): 449–52. http://dx.doi.org/10.1115/1.2196421.
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A sensor placement technique is proposed for implementing the hybrid adaptive feedforward observer. The observer is a conventional dynamic observer augmented with an adaptive feedforward component for estimating the effect of persistent, nonstationary disturbances. The placement technique searches for the least possible number of sensors that satisfy two criteria, the observability of the plant, and the lowest condition number of the error dynamic system's state matrix. Demonstration was performed on a one-dimensional acoustic duct. The results show that the proposed technique is an effective guideline for identifying the optimal sensor locations.
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Li, Shunlong, Huiming Yin, Zhonglong Li, Wencheng Xu, Yao Jin, and Shaoyang He. "Optimal sensor placement for cable force monitoring based on multioutput support vector regression model." Advances in Structural Engineering 21, no. 15 (May 7, 2018): 2259–69. http://dx.doi.org/10.1177/1369433218772342.
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Cable force monitoring is an essential and critical part of structural health monitoring for cable-supported bridges. The quality of obtained information depends considerably on the number and location of limited sensors. The purpose of this article is to provide a method for optimal sensor placement for cable force monitoring in cable-supported bridges. Based on the spatial correlation between neighbouring or symmetrical cable forces, the structural information of non-monitored cables can be predicted by multioutput support vector regression models, established between monitored (input) and the non-monitored (output) cable forces. The number and placement of cable force sensors have significant influence on prediction performance of established multioutput support vector regression models. The proposed optimal sensor configuration is to select multioutput support vector regression models with minimum prediction error from all possible sensor locations. In this study, information entropy is employed to measure the prediction performance of different sensor configurations and formulate the objective function, optimised by three computationally effective algorithms: forward sequential sensor placement algorithm, backward sequential sensor placement algorithm and genetic algorithm. The application of proposed method to Nanjing No. 3 Yangtze River Bridge confirmed the efficiency, accuracy and effectiveness of the proposed method.
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Yu, Qinxiao, Ning Zhu, Geng Li, and Shoufeng Ma. "Simulation-Based Sensor Location Model for Arterial Street." Discrete Dynamics in Nature and Society 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/854089.
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Traffic sensors serve as an important way to a number of intelligent transportation system applications which rely heavily on real-time data. However, traffic sensors are costly. Therefore, it is necessary to optimize sensor placement to maximize various benefits. Arterial street traffic is highly dynamic and the movement of vehicles is disturbed by signals and irregular vehicle maneuver. It is challenging to estimate the arterial street travel time with limited sensors. In order to solve the problem, the paper presents travel time estimation models that rely on speed data collected by sensor. The relationship between sensor position and vehicle trajectory in single link is investigated. A sensor location model in signalized arterial is proposed to find the optimal sensor placement with the minimum estimation error of arterial travel time. Numerical experiments are conducted in 3 conditions: synchronized traffic signals, green wave traffic signals, and vehicle-actuated signals. The results indicate that the sensors should not be placed in vehicle queuing area. Intersection stop line is an ideal sensor position. There is not any fixed sensor position that can cope with all traffic conditions.
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Saleem, Muhammad Mazhar, and Hongki Jo. "Multi-objective sensor placement optimization for structural response estimation under spatially varying dynamic loading of bridges." Advances in Structural Engineering 24, no. 10 (February 19, 2021): 2255–66. http://dx.doi.org/10.1177/1369433221993574.
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Although a lot of different types of sensors are available in the market only a limited number of sensors can be installed on a structure. Proper placement of these sensors plays a vital role in effectively achieving the objectives of a monitoring system. Sensor placement becomes especially critical in the case of bridges where the applied loading keeps on changing its location. A sensor layout that provides good quality structural response estimates for a given applied loading may not yield acceptable results for a different loading arrangement. Further, usually different types of sensors are installed on a structure e.g. strain gauges and accelerometers. These sensors measure different physical quantities having different units and orders of magnitude thus cannot be easily incorporated in a sensor placement optimization (SPO) process. So, this research work proposes a multi-objective sensor placement optimization approach that can effectively deal with different types of sensor measurements and spatially varying loading such as in the case of bridges. The proposed method employs an augmented Kalman filter (AKF) for structural response estimation and a multi-objective genetic algorithm for SPO. The AKF can effectively estimate structural response using a few heterogeneous noisy measurements while incorporating the modeling error. The effectiveness of the proposed method is demonstrated using a numerical example of a 3D truss bridge structure. The results show that the proposed multi-objective optimization method yields a sensor arrangement that remains effective against spatially varying dynamic loading.
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Johnson, Marty E., Luiz P. Nascimento, Mary Kasarda, and Chris R. Fuller. "The Effect of Actuator and Sensor Placement on the Active Control of Rotor Unbalance." Journal of Vibration and Acoustics 125, no. 3 (June 18, 2003): 365–73. http://dx.doi.org/10.1115/1.1569946.
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This paper investigates both theoretically and experimentally the effect of the location and number of sensors and magnetic bearing actuators on both global and local vibration reduction along a rotor using a feedforward control scheme. Theoretical approaches developed for the active control of beams have been shown to be useful as simplified models for the rotor scenario. This paper also introduces the time-domain LMS feedforward control strategy, used widely in the active control of sound and vibration, as an alternative control methodology to the frequency-domain feedforward approaches commonly presented in the literature. Results are presented showing that for any case where the same number of actuators and error sensors are used there can be frequencies at which large increases in vibration away from the error sensors can occur. It is also shown that using a larger number of error sensors than actuators results in better global reduction of vibration but decreased local reduction. Overall, the study demonstrated that an analysis of actuator and sensor locations when feedforward control schemes are used is necessary to ensure that harmful increased vibrations do not occur at frequencies away from rotor-bearing natural frequencies or at points along the rotor not monitored by error sensors.
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Brandstein, Michael S., John E. Adcock, and Harvey F. Silverman. "Microphone‐array localization error estimation with application to sensor placement." Journal of the Acoustical Society of America 99, no. 6 (June 1996): 3807–16. http://dx.doi.org/10.1121/1.414998.
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Kalinić, Hrvoje, Zvonimir Bilokapić, and Frano Matić. "Can Local Geographically Restricted Measurements Be Used to Recover Missing Geo-Spatial Data?" Sensors 21, no. 10 (May 18, 2021): 3507. http://dx.doi.org/10.3390/s21103507.
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The experiments conducted on the wind data provided by the European Centre for Medium-range Weather Forecasts show that 1% of the data is sufficient to reconstruct the other 99% with an average amplitude error of less than 0.5 m/s and an average angular error of less than 5 degrees. In a nutshell, our method provides an approach where a portion of the data is used as a proxy to estimate the measurements over the entire domain based only on a few measurements. In our study, we compare several machine learning techniques, namely: linear regression, K-nearest neighbours, decision trees and a neural network, and investigate the impact of sensor placement on the quality of the reconstruction. While methods provide comparable results the results show that sensor placement plays an important role. Thus, we propose that intelligent location selection for sensor placement can be done using k-means, and show that this indeed leads to increase in accuracy as compared to random sensor placement.
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Darabseh, Ala’, Evangelos Bitsikas, Brice Tedongmo, and Christina Pöpper. "On ADS-B Sensor Placement for Secure Wide-Area Multilateration." Proceedings 59, no. 1 (December 1, 2020): 3. http://dx.doi.org/10.3390/proceedings2020059003.
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As automatic dependent surveillance–broadcast (ADS-B) becomes more prevalent, the placement of on-ground sensors is vital for Air Traffic Control (ATC) to control the airspace. However, the current sensors are placed in an unstructured way that keeps some areas without coverage, and others are over-densified by sensors. Therefore, areas with coverage anomalies may cause issues that inhibit accurate ADS-B verifications as well as the availability of ADS-B altogether. In this paper, we tackle the ADS-B-specific optimal sensor placement (OSP) problem. Of importance are both the optimal coverage and the secure and accurate verification of received ADS-B messages. Specifically, we take into account the following objectives. First, we determine the minimum required number of sensors in order to cover a certain area like Europe. Second, we produce a better placement of the current sensors with respect to the security and accuracy of geometric dilution of precision (GDOP). Finally, we calculate how far the current sensor setup is from our derived optimal solution as well as the cost to reach the optimality. Our experiments show that the ideal fitness score for solving the OSP is below 0.1, meaning that the mean squared error (MSE) of the required and achieved GDOPs is significantly small, thus accomplishing a near-optimal setup.
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Aydin, Boran Ekin, Hugo Hagedooren, Martine M. Rutten, Joost Delsman, Gualbert H. P. Oude Essink, Nick van de Giesen, and Edo Abraham. "A Greedy Algorithm for Optimal Sensor Placement to Estimate Salinity in Polder Networks." Water 11, no. 5 (May 27, 2019): 1101. http://dx.doi.org/10.3390/w11051101.
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We present a systematic approach for salinity sensor placement in a polder network, where the objective is to estimate the unmeasured salinity levels in the main polder channels. We formulate this problem as optimization of the estimated salinity levels using root mean square error (RMSE) as the “goodness of fit” measure. Starting from a hydrodynamic and salt transport model of the Lissertocht catchment (a low-lying polder in the Netherlands), we use principal component analysis (PCA) to produce a low-order PCA model of the salinity distribution in the catchment. This model captures most of the relevant salinity dynamics and is capable of reconstructing the spatial and temporal salinity variation of the catchment. Just using three principal components (explaining 93% of the variance of the dataset) for the low-order PCA model, three optimally placed sensors with a greedy algorithm make the placement robust for modeling and measurement errors. The performance of the sensor placement for salinity reconstruction is evaluated against the detailed hydrodynamic and salt transport model and is shown to be close to the global optimum found by an exhaustive search with a RMSE of 82.2 mg/L.
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Kirana, Vanda Catur, Dwi Herry Andayani, Andjar Pudji, and Aziza Hannouch. "Effect of Closed and Opened the Door to Temperature on PID-Based Baby Incubator with Kangaroo Mode." Indonesian Journal of electronics, electromedical engineering, and medical informatics 3, no. 3 (August 28, 2021): 121–27. http://dx.doi.org/10.35882/ijeeemi.v3i3.6.
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The uneven distribution of the baby incubator temperature can cause the temperature in the baby incubator to be different at each point. The purpose of this study was to analyze the effect of the door closed and opened to the temperature at each point of sensor placement that has been determined. The study was conducted as an experimental research design. In this experiment, an Incu Analyzer comparison was used as a calibrator unit, a baby skin temperature thermistor sensor, and four LM35 sensors for baby incubator room temperature with one LM35 sensor as a PID control system carried out by trial-and-error method. Based on the results of measurements was made with the design, when the chamber is open, it produces an average error value of T1 4.083%, T2 6.06%, T3 3.78%, T4 4.88%, and T5 1.48%, while when the chamber is closed, it produces an average error value T1 0.75. %, T2 0.88%, T3 1.15%, T4 0.74%, and T5 0.87%. Measurement of skin temperature using a thermometer has an average error value of 1.1%. The results showed that uneven heat transfer, lack of air distribution, different sensor placements at each point, and non-standard chamber sizes were factors that were uneven at each point. Based on the results of the study, it was found that the use of a working system on this device can be implemented to control the temperature of the baby incubator by knowing the temperature distribution at each point
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Wu, Hui, Zhe Liu, Jin Hu, and Weifeng Yin. "Sensor placement optimization for critical-grid coverage problem of indoor positioning." International Journal of Distributed Sensor Networks 16, no. 12 (December 2020): 155014772097992. http://dx.doi.org/10.1177/1550147720979922.
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It is more practical and efficient to deploy sensors in critical areas rather than common areas to ensure indoor positioning accuracy and reduce deployment cost. This study focused on the sensor placement optimization for critical-grid coverage problem with two objectives: accuracy and cost. After reviewing some related works, this article proposed a multi-objective optimization model for critical-grid coverage problem of indoor positioning considering k-coverage problem as well as the topological rationality of sensor distribution. Then, NSGA-II algorithm was used to solve the optimizing model of sensor placement. At last, the simulation experiment and real environment validation were conducted for proposed method. The results showed that the optimized schemes obtain a lower error (1.13, 1.21 m) and a higher reduction of sensor deployment cost than the uniform deployment scheme (1.44 m). As a conclusion, the proposed method could reduce the cost of sensor deployment while ensuring the accuracy of indoor positioning for critical areas. It also provides a new direction for improving the accuracy of indoor positioning.
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ZHANG, X. H., S. ZHU, Y. L. XU, and X. J. HOMG. "INTEGRATED OPTIMAL PLACEMENT OF DISPLACEMENT TRANSDUCERS AND STRAIN GAUGES FOR BETTER ESTIMATION OF STRUCTURAL RESPONSE." International Journal of Structural Stability and Dynamics 11, no. 03 (June 2011): 581–602. http://dx.doi.org/10.1142/s0219455411004221.
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Although a variety of sensors provide more comprehensive information and advanced features of structures, their distinct properties and limitations considerably complicate the design procedure of multi type sensor systems. This paper is focused on the optimal design of integrated sensor systems with both strain gauges and displacement transducers. Unlike traditional sensor placement approaches, in which these two types of sensors are often designed separately to monitor structural deformations and displacements respectively, the integrated design procedure presented in this study treats the sensor system as a whole. The number and locations of strain gauges and displacement transducers are optimized simultaneously, and their measurement data are fused together to better predict the unobserved structural response. The theoretical criterion for the optimization procedure is first formulated based on the strain and displacement mode shapes extracted from finite element models. Then, the initial candidate sensor locations are reduced to a smaller optimal set with minimized prediction error of structural response. A two-dimensional cantilever beam is then analyzed as a numerical example to investigate the effectiveness and accuracy of the presented optimal sensor placement approach. The results indicate that the integrated sensor system provides better estimation of structural response than single-type sensor system.
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Zhan, Jie Zi, and Ling Yu. "Optimal Sensor Placement Based on Tabu Search Algorithms." Applied Mechanics and Materials 578-579 (July 2014): 1069–72. http://dx.doi.org/10.4028/www.scientific.net/amm.578-579.1069.
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In this study, the Tabu search (TS) algorithm is introduced into the optimal sensor placement (OSP) problem in the field of the structural health monitoring and moving force identification. A TS-based OSP procedure is proposed and further evaluated by some numerical simulations on a 2D planar truss model. The mean values of off-diagonal elements in a modal assurance criterion (MAC) matrix are used as the optimization objective function. Based on the criteria of MAC, determinant of fisher matrix, matrix condition number, and the least mean square error, the TS-based OSP procedure is evaluated through comparing with ones due to both of the energy coefficient-effective independence (ECEFI) and the effective independence (EFI) algorithms. The results show that the proposed TS-based OSP procedure is feasible with a higher accuracy.
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Niswander, Wesley, Wei Wang, and Kimberly Kontson. "Optimization of IMU Sensor Placement for the Measurement of Lower Limb Joint Kinematics." Sensors 20, no. 21 (October 22, 2020): 5993. http://dx.doi.org/10.3390/s20215993.
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There is an increased interest in using wearable inertial measurement units (IMUs) in clinical contexts for the diagnosis and rehabilitation of gait pathologies. Despite this interest, there is a lack of research regarding optimal sensor placement when measuring joint kinematics and few studies which examine functionally relevant motions other than straight level walking. The goal of this clinical measurement research study was to investigate how the location of IMU sensors on the lower body impact the accuracy of IMU-based hip, knee, and ankle angular kinematics. IMUs were placed on 11 different locations on the body to measure lower limb joint angles in seven participants performing the timed-up-and-go (TUG) test. Angles were determined using different combinations of IMUs and the TUG was segmented into different functional movements. Mean bias and root mean square error values were computed using generalized estimating equations comparing IMU-derived angles to a reference optical motion capture system. Bias and RMSE values vary with the sensor position. This effect is partially dependent on the functional movement analyzed and the joint angle measured. However, certain combinations of sensors produce lower bias and RMSE more often than others. The data presented here can inform clinicians and researchers of placement of IMUs on the body that will produce lower error when measuring joint kinematics for multiple functionally relevant motions. Optimization of IMU-based kinematic measurements is important because of increased interest in the use of IMUs to inform diagnose and rehabilitation in clinical settings and at home.
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Papadopoulou, Maria, Benny Raphael, Ian Smith, and Chandra Sekhar. "Hierarchical Sensor Placement Using Joint Entropy and the Effect of Modeling Error." Entropy 16, no. 9 (September 23, 2014): 5078–101. http://dx.doi.org/10.3390/e16095078.
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Comboul, Maud, Julien Emile-Geay, Gregory J. Hakim, and Michael N. Evans. "Paleoclimate Sampling as a Sensor Placement Problem." Journal of Climate 28, no. 19 (September 29, 2015): 7717–40. http://dx.doi.org/10.1175/jcli-d-14-00802.1.
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Abstract This study formulates the design of optimal observing networks for past surface climate conditions as the solution to a data assimilation problem, given a realistic proxy system model (PSM), paleoclimate observational uncertainties, and a network of current and proposed observing sites. The method is illustrated with the design of optimal networks of coral δ18O records, chosen among candidate sites, and used to jointly infer sea surface temperature (SST) and sea surface salinity (SSS) fields from the Community Climate System Model, version 4, last millennium simulation over the 1850–2005 period. It is shown that an existing paleo-observing network accounts for approximately 20% of the SST variance, and that adding 25 to 100 optimal pseudocoral sites would boost this fraction to 35%–52%. Characterizing the SST variance alone, or jointly with the SSS, leads to similar optimal networks, which justifies using coral δ18O records for SST reconstructions. In contrast, the network design for reconstructing SSS alone is fundamentally different, emphasizing the hydroclimatic centers of action of El Niño–Southern Oscillation. In all cases, network design depends strongly on the amplitude of the observational error, so replicates may be more beneficial than the exploration of new sites; these replicates tend to be chosen where proxies are already informative of the large-scale climate field(s). Finally, extensions to other types of paleoclimatic observations are discussed, and a path to operationalization is outlined.
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Shokouhi, Seyed KS, Yong Yuan, and Hongping Zhu. "Optimal placement of sensors and piezoelectric friction dampers in the pipeline networks based on nonlinear dynamic analysis." Journal of Low Frequency Noise, Vibration and Active Control 36, no. 1 (March 2017): 56–82. http://dx.doi.org/10.1177/0263092317693504.
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Experiences of past earthquakes demonstrate that pipeline systems have no proper performance when exposed to severe earthquakes. In this study, sensor and damper placement approaches are presented for doing reliable health monitoring and seismic retrofitting of the piping networks. Since most of the available sensor placement methods are based on modal analysis results, the authors propose a new scheme that relies on the nonlinearity which utilizes nonlinear time history analysis results, and genetic algorithm is selected to act as the methodology of optimization as well. The results demonstrate that the proposed optimal sensor configuration strategy is more accurate and efficient than the extended modal assurance criterion method. To assess the number of sensors, a sensitivity analysis is undertaken in which the number of sensors computed optimally by the proposed algorithm contains the least convergence error. In addition, the number of iterations and the time consumed in the proposed approach are considerably less than the extended modal assurance criterion method. Moreover, the efficiency of the proposed sensor placement scheme was compared with a new algorithm proposed by Sun and Büyüköztürk, named discrete artificial bee colony, where the simulation result demonstrates high accuracy of the proposed sensor configuration approach. The initial time history analysis results show the vulnerable points of the system, which destroyed due to the applied seismic waves. Hence, to enhance the seismic performance of the system, piezoelectric friction dampers are optimally placed, where it can be clearly seen that the optimal arrangement of piezoelectric friction dampers in the piping system can significantly decrease the seismic response.
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Shen, Sheng, and Shao-Fei Jiang. "Distributed Deformation Monitoring for a Single-Cell Box Girder Based on Distributed Long-Gage Fiber Bragg Grating Sensors." Sensors 18, no. 8 (August 8, 2018): 2597. http://dx.doi.org/10.3390/s18082597.
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Distributed deformation based on fiber Bragg grating sensors or other kinds of strain sensors can be used to monitor bridges during operation. However, most research on distributed deformation monitoring has focused on solid rectangular beams rather than box girders—a kind of typical hollow beam widely employed in actual bridges. The deformation of a single-cell box girder contains bending deflection and also two additional deformations respectively caused by shear lag and shearing action. This paper revises the improved conjugated beam method (ICBM) based on the long-gage fiber Bragg grating (LFBG) sensors to satisfy the requirements for monitoring the two additional deformations in a single-cell box girder. This paper also proposes a suitable LFBG sensor placement in a box girder to overcome the influence of strain fluctuation on the flange caused by the shear lag effect. Results from numerical simulations show that the theoretical monitoring errors of the revised ICBM are typically 0.3–1.5%, and the maximum error is 2.4%. A loading experiment for a single-cell box gilder monitored by LFBG sensors shows that most of the practical monitoring errors are 6–8% and the maximum error is 11%.
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Peng, Yuan-Chih, Shuyang Chen, Devavrat Jivani, John Wason, William Lawler, Glenn Saunders, Richard J. Radke, Jeff Trinkle, Shridhar Nath, and John T. Wen. "Sensor-Guided Assembly of Segmented Structures with Industrial Robots." Applied Sciences 11, no. 6 (March 17, 2021): 2669. http://dx.doi.org/10.3390/app11062669.
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This paper presents a robotic assembly methodology for the manufacturing of large segmented composite structures. The approach addresses three key steps in the assembly process: panel localization and pick-up, panel transport, and panel placement. Multiple stationary and robot-mounted cameras provide information for localization and alignment. A robot wrist-mounted force/torque sensor enables gentle but secure panel pick-up and placement. Human-assisted path planning ensures reliable collision-free motion of the robot with a large load in a tight space. A finite state machine governs the process flow and user interface. It allows process interruption and return to the previous known state in case of error condition or when secondary operations are needed. For performance verification, a high resolution motion capture system provides the ground truth reference. An experimental testbed integrating an industrial robot, vision and force sensors, and representative laminated composite panels demonstrates the feasibility of the proposed assembly process. Experimental results show sub-millimeter placement accuracy with shorter cycle times, lower contact force, and reduced panel oscillation than manual operations. This work demonstrates the versatility of sensor guided robotic assembly operation in a complex end-to-end tasks using the open source Robot Operating System (ROS) software framework.
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Lofrano, Egidio, Marco Pingaro, Patrizia Trovalusci, and Achille Paolone. "Optimal Sensors Placement in Dynamic Damage Detection of Beams Using a Statistical Approach." Journal of Optimization Theory and Applications 187, no. 3 (October 16, 2020): 758–75. http://dx.doi.org/10.1007/s10957-020-01761-3.
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AbstractStructural monitoring plays a central role in civil engineering; in particular, optimal sensor positioning is essential for correct monitoring both in terms of usable data and for optimizing the cost of the setup sensors. In this context, we focus our attention on the identification of the dynamic response of beam-like structures with uncertain damages. In particular, the non-localized damage is described using a Gaussian distributed random damage parameter. Furthermore, a procedure for selecting an optimal number of sensor placements has been presented based on the comparison among the probability of damage occurrence and the probability to detect the damage, where the former can be evaluated from the known distribution of the random parameter, whereas the latter is evaluated exploiting the closed-form asymptotic solution provided by a perturbation approach. The presented case study shows the capability and reliability of the proposed procedure for detecting the minimum number of sensors such that the monitoring accuracy (estimated by an error function measuring the differences among the two probabilities) is not greater than a control small value.
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Papadimitriou, Costas, and Geert Lombaert. "The effect of prediction error correlation on optimal sensor placement in structural dynamics." Mechanical Systems and Signal Processing 28 (April 2012): 105–27. http://dx.doi.org/10.1016/j.ymssp.2011.05.019.
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Song, Lin-Ping, Leonard R. Pasion, Nicolas Lhomme, and Douglas W. Oldenburg. "Sensor Placement via Optimal Experiment Design in EMI Sensing of Metallic Objects." Mathematical Problems in Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/5856083.
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This work, under the optimal experimental design framework, investigates the sensor placement problem that aims to guide electromagnetic induction (EMI) sensing of multiple objects. We use the linearized model covariance matrix as a measure of estimation error to present a sequential experimental design (SED) technique. The technique recursively minimizes data misfit to update model parameters and maximizes an information gain function for a future survey relative to previous surveys. The fundamental process of the SED seeks to increase weighted sensitivities to targets when placing sensors. The synthetic and field experiments demonstrate that SED can be used to guide the sensing process for an effective interrogation. It also can serve as a theoretic basis to improve empirical survey operation. We further study the sensitivity of the SED to the number of objects within the sensing range. The tests suggest that an appropriately overrepresented model about expected anomalies might be a feasible choice.
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Jia, Yunsong, Xueyun Tian, Xin Chen, and Xiang Li. "An Optimization Method for the Layout of Soil Humidity Sensors Based on Compressed Sensing." Journal of Sensors 2021 (September 2, 2021): 1–10. http://dx.doi.org/10.1155/2021/9901990.
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In the farmland Internet of Things, to achieve precise control of production, it is necessary to obtain more data support, which requires the deployment of many sensors, and this will inevitably bring about high investment and high-cost problems. This paper mainly studies the optimization of sensor placement in the agricultural field. Through compressed sensing and algorithm optimization, the number of sensors used is reduced and the cost is reduced on the premise of ensuring the effect. At present, there are many mature sensor layout optimization methods, but these methods will have incomplete parameters due to experimental conditions and environmental factors. They are more suitable for structural health monitoring and lack research in agricultural applications. Considering that the sensor layout optimization can be converted into the characteristics of image compression selection and the compression effect of the compressed sensing theory is better, therefore, this paper proposes a sensor layout optimization method based on compressed sensing. Due to the structural characteristics of the existing measurement matrix in the compressed sensing theory, the specific position distribution of the optimized sensor layout cannot be obtained directly. This paper improves the existing sparse random measurement matrix to determine the number of sensors required for a given region and the function of the specific location of each sensor. The experimental results show that soil moisture can be measured with a small error of 0.91 by using 1/3 of the original sensor number. The result of data reconstruction using 1/6 of the original sensor is average, and the average error is up to 1.68, which is suitable for the environment with small data fluctuation.
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Fitz-Coy, Norman, and Anindya Chatterjee. "Actuator Placement in Multi-Degree-of-Freedom Vibration Simulators." Shock and Vibration 1, no. 3 (1994): 279–87. http://dx.doi.org/10.1155/1994/828134.
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A method for comparing candidate actuator configurations for multi-degree-of-freedom (MDOF) vibration simulators is presented. The method has its roots in the comparison of achievable subspaces and maximum error bounds; the comparison is accomplished via a QR decomposition. In instances where two configurations yield the same error bound, the ratio of the largest to smallest singular value is used to determine the “best” configuration. Both amplitude bounds at given sensor locations and relative significance of each sensor's output, if known, can be incorporated in the analysis. Through numerical examples, it is demonstrated that no simple rule of thumb criterion appears to exist for the selection of actuator placement in MDOF vibration simulators.
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Faridah, F., Sentagi Utami, Ressy Yanti, S. Sunarno, Emilya Nurjani, and Rony Wijaya. "Optimal thermal sensors placement based on indoor thermal environment characterization by using CFD model." Journal of Applied Engineering Science 19, no. 3 (2021): 628–41. http://dx.doi.org/10.5937/jaes0-28985.
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This paper discusses an analysis to obtain the optimal thermal sensor placement based on indoor thermal characteristics. The method relies on the Computational Fluid Dynamics (CFD) simulation by manipulating the outdoor climate and indoor air conditioning (AC) system. First, the alternative sensor's position is considered the optimum installation and the occupant's safety. Utilizing the Standardized Euclidean Distance (SED) analysis, these positions are then selected for the best position using the distribution of the thermal parameters' values data at the activity zones. Onsite measurement validated the CFD model results with the maximum root means square error, RMSE, between both data sets as 0.8°C for temperature, the relative humidity of 3.5%, and an air velocity of 0.08m/s, due to the significant effect of the building location. The Standardized Euclidean Distance (SED) analysis results are the optimum sensor positions that accurately, consistently, and have the optimum % coverage representing the thermal condition at 1,1m floor level. At the optimal positions, actual sensors are installed and proven to be valid results since sensors could detect thermal variables at the height of 1.1m with SED validation values of 2.5±0.3, 2.2±0.6, 2.0±1.1, for R15, R33, and R40, respectively.
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Pei, Xue-Yang, Ting-Hua Yi, and Hong-Nan Li. "Dual-type sensor placement optimization by fully utilizing structural modal information." Advances in Structural Engineering 22, no. 3 (September 17, 2018): 737–50. http://dx.doi.org/10.1177/1369433218799151.
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Strain gauges and accelerometers are widely used in bridge structural health monitoring systems. Generally, the strain gauges are placed on the key locations to obtain local structural deformation information; the accelerometers are used to obtain the structural modal information. However, the modal information contained in the measured strains is not taken into account. In this article, to fully utilize the modal information contained in strains, a mode shape estimation method is proposed that the strain mode shapes of the strain locations are used to obtain the displacement mode shapes of some positions without accelerometers. At first, to simulate the practical situation, some positions with large structural deformations are selected as the strain gauge locations. Using the proposed mode shape estimation method, the displacement mode shapes of some locations without accelerometers are estimated by the strain mode shapes using the least squares method, and the locations with the smallest estimation error are finally determined as the estimated locations. Then, accelerometers are added to the existing sensor placement. Here, the modal assurance criterion is used to evaluate the distinguishability of the displacement mode shapes obtained from the strain gauges and accelerometers. The accelerometer locations that bring the smallest modal assurance criterion values are selected. In addition, a redundancy can be set to avoid the adjacent sensors containing similar modal information. Through the proposed sensor placement method, the deformation and modal information contained in the strain gauges is fully utilized; the modal information contained in the strain gauges and accelerometers is comprehensively utilized. Numerical experiments are carried out using a bridge benchmark structure to demonstrate the sensor placement method.
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Pei, Xue-Yang, Ting-Hua Yi, Chun-Xu Qu, and Hong-Nan Li. "Conditional information entropy based sensor placement method considering separated model error and measurement noise." Journal of Sound and Vibration 449 (June 2019): 389–404. http://dx.doi.org/10.1016/j.jsv.2019.02.035.
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Andria, Gregorio, Filippo Attivissimo, Attilio Di Nisio, Anna Maria Lucia Lanzolla, and Mattia Alessandro Ragolia. "Assessment of Position Repeatability Error in an Electromagnetic Tracking System for Surgical Navigation." Sensors 20, no. 4 (February 11, 2020): 961. http://dx.doi.org/10.3390/s20040961.
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In this paper we present a study of the repeatability of an innovative electromagnetic tracking system (EMTS) for surgical navigation, developed to overcome the state of the art of current commercial systems, allowing for the placement of the magnetic field generator far from the operating table. Previous studies led to the development of a preliminary EMTS prototype. Several hardware improvements are described, which result in noise reduction in both signal generation and the measurement process, as shown by experimental tests. The analysis of experimental results has highlighted the presence of drift in voltage components, whose effect has been quantified and related to the variation of the sensor position. Repeatability in the sensor position measurement is evaluated by means of the propagation of the voltage repeatability error, and the results are compared with the performance of the Aurora system (which represents the state of the art for EMTS for surgical navigation), showing a repeatability error about ten times lower. Finally, the proposed improvements aim to overcome the limited operating distance between the field generator and electromagnetic (EM) sensors provided by commercial EM tracking systems for surgical applications and seem to provide a not negligible technological advantage.
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Chao-Shan, Yang, Cheng Hua, and Wang Zhong-Gang. "Optimal Sensor Placement for the Tower Structure Based on Key Components." Open Electrical & Electronic Engineering Journal 8, no. 1 (December 31, 2014): 348–54. http://dx.doi.org/10.2174/1874129001408010348.
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In order to improve the large-scale complex spatial structure sensor placement, this paper puts forward an optimal sensor placement method for the tower structure based on key components. According to this method, different probabilities of the structure system’s reliability degree caused by the same damage degree of components are firstly calculated; then component weight coefficients are introduced to measure the relative importance of various components in the whole structure system; the key components of the structure system are defined according to the value of weight coefficients; then modal parameters are adopted to analyze the damage sensitivity of the key components and to find out the vibration modes and measuring points sensitive to the damage of key components, thus to finish the sensor placement. Fully considering the structure characteristics, this method can solve the optimization issues, including the quantity of measurement points and the position, and avoid the complex iterative algorithm and modal expansion error, so it contributes to better controlling the structure state. Finally, through the calculation example of a communication tower, the feasibility and the validity of the method are proved.
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Cohen, Kelly, Stefan Siegel, Dave Wetlesen, Jeff Cameron, and Aaron Sick. "Effective Sensor Placements for the Estimation of Proper Orthogonal Decomposition Mode Coefficients in von Karman Vortex Street." Journal of Vibration and Control 10, no. 12 (December 2004): 1857–80. http://dx.doi.org/10.1177/1077546304046035.
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For feedback control using low-dimensional proper orthogonal decomposition (POD) models, the mode amplitudes of the POD mode coefficients need to be estimated based on sensor readings. This paper is aimed at suppressing the von Kairman vortex street in the wake of a circular cylinder using a low-dimensional approach based on POD. We compare sensor placement methods based on the spatial distribution of the POD modes to arbitrary ad hoc methods. Flow field data were obtained from Navier-Stokes simulation as well as particle image velocimetry (PIV) measurements. A low-dimensional POD was applied to the snapshot ensembles from the experiment and simulation. Linear stochastic estimation was used to map the sensor readings of the velocity field on the POD mode coefficients. We studied 53 sensor placement configurations, 32 of which were based on POD eigenfunctions and the others using ad hoc methods. The effectiveness of the sensor configurations was investigated at Re = 100 for the computational fluid dynamic data, and for a Reynolds number range of 82-99 for the water tunnel PIV data. Results show that a five-sensor configuration can keep the root mean square estimation error, for the amplitudes of the first two modes to within 4% for simulation data and within 10% for the PIV data. This level of error is acceptable for a moderately robust controller The POD-based design was found to be simpler. more effective, and robust compared to the ad hoc methods examined.
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Kapoor, Rohan, Alessandro Gardi, and Roberto Sabatini. "Network Optimisation and Performance Analysis of a Multistatic Acoustic Navigation Sensor." Sensors 20, no. 19 (October 8, 2020): 5718. http://dx.doi.org/10.3390/s20195718.
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This paper addresses some of the existing research gaps in the practical use of acoustic waves for navigation of autonomous air and surface vehicles. After providing a characterisation of ultrasonic transducers, a multistatic sensor arrangement is discussed, with multiple transmitters broadcasting their respective signals in a round-robin fashion, following a time division multiple access (TDMA) scheme. In particular, an optimisation methodology for the placement of transmitters in a given test volume is presented with the objective of minimizing the position dilution of precision (PDOP) and maximizing the sensor availability. Additionally, the contribution of platform dynamics to positioning error is also analysed in order to support future ground and flight vehicle test activities. Results are presented of both theoretical and experimental data analysis performed to determine the positioning accuracy attainable from the proposed multistatic acoustic navigation sensor. In particular, the ranging errors due to signal delays and attenuation of sound waves in air are analytically derived, and static indoor positioning tests are performed to determine the positioning accuracy attainable with different transmitter–receiver-relative geometries. Additionally, it is shown that the proposed transmitter placement optimisation methodology leads to increased accuracy and better coverage in an indoor environment, where the required position, velocity, and time (PVT) data cannot be delivered by satellite-based navigation systems.
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Zhan, Shu Lin, Fang Huang, and Jun Ying Lai. "Optimal Sensor Placement for High-Rise Building via Genetic Algorithms and Improved Information Matrix Criterion." Advanced Materials Research 368-373 (October 2011): 1653–59. http://dx.doi.org/10.4028/www.scientific.net/amr.368-373.1653.
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To improve the accuracy of parameter identification and to reduce the test cost in the high-rise structure health monitoring systems , the paper proposes an optimal placement method combines genetic algorithms with improved information matrix criterion (GA-IIM). With traditional improved effective independent method (EFI-DPR), it is easily trapped into bureau of optimum solution, and the proposed method can resolve this problem. The solutions were coded by a two-dimensional integer array, each line stored a feasible solution and compulsory mutation was adopted to avoid the solution reappeared in the same position. To improve the convergence speed, each generation of optimal group was kept to the next one to participate in the competition. With the improved information matrix criterion embedded in the genetic algorithms, the placement design was produced. This technique was used to optimize the sensor placement of a nineteenth layer frame structure. Comparing the optimized sensor placement of the proposed method with that of improved effective independent method by the modal assurance criterion and the mean square error, the proposed method performs better.
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Mazzoleni, Maurizio, Juan Chacon-Hurtado, Seong Jin Noh, Dong-Jun Seo, Leonardo Alfonso, and Dimitri Solomatine. "Data Assimilation in Hydrologic Routing: Impact of Model Error and Sensor Placement on Flood Forecasting." Journal of Hydrologic Engineering 23, no. 6 (June 2018): 04018018. http://dx.doi.org/10.1061/(asce)he.1943-5584.0001656.
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Lin, Si Yuan, Ke Wang, Yue Chen Fan, Tao Yan, and Neng He. "Error Analysis of Displacement Measurements Based on Digital Image Correlation Method." Applied Mechanics and Materials 333-335 (July 2013): 207–14. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.207.
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The error of displacement measurements by digital image correlation method is examined from a pratical perspective. Different from previous research, this study focuses on external factors influencing the accuracy of displacement measurement in the study of cooperative mark recognition and camera placement. Our major objectives of this research include indentificating the chief error sources and assessing their influences on the testing results. There are 5 parts in this paper. We start with a brief introduction of the necessity of analyzing the errors. After reviewing the principles of digital image correlation method, an detailed discussion of error soureces of this method is provided. Then we design a pratical experiment measuring the characteristics of a spring vibrator using the digital image correlation mesurement systems and laser displacement sensor. By comparing the results from two ways of measurment, we end the study with the conclusion that the accuracy of displacement measuring by digital image correlation method is tightly related to the choice of cooperative mark and camera intersection angle.
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Jarque-Bou, Néstor J., Joaquín L. Sancho-Bru, and Margarita Vergara. "Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics." Sensors 21, no. 4 (February 4, 2021): 1049. http://dx.doi.org/10.3390/s21041049.
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Simultaneous measurement of the kinematics of all hand segments is cumbersome due to sensor placement constraints, occlusions, and environmental disturbances. The aim of this study is to reduce the number of sensors required by using kinematic synergies, which are considered the basic building blocks underlying hand motions. Synergies were identified from the public KIN-MUS UJI database (22 subjects, 26 representative daily activities). Ten synergies per subject were extracted as the principal components explaining at least 95% of the total variance of the angles recorded across all tasks. The 220 resulting synergies were clustered, and candidate angles for estimating the remaining angles were obtained from these groups. Different combinations of candidates were tested and the one providing the lowest error was selected, its goodness being evaluated against kinematic data from another dataset (KINE-ADL BE-UJI). Consequently, the original 16 joint angles were reduced to eight: carpometacarpal flexion and abduction of thumb, metacarpophalangeal and interphalangeal flexion of thumb, proximal interphalangeal flexion of index and ring fingers, metacarpophalangeal flexion of ring finger, and palmar arch. Average estimation errors across joints were below 10% of the range of motion of each joint angle for all the activities. Across activities, errors ranged between 3.1% and 16.8%.
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Tulipani, Lindsey, Mark G. Boocock, Karen V. Lomond, Mahmoud El-Gohary, Duncan A. Reid, and Sharon M. Henry. "Validation of an Inertial Sensor System for Physical Therapists to Quantify Movement Coordination During Functional Tasks." Journal of Applied Biomechanics 34, no. 1 (February 1, 2018): 23–30. http://dx.doi.org/10.1123/jab.2016-0139.
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Physical therapists evaluate patients’ movement patterns during functional tasks; yet, their ability to interpret these observations consistently and accurately is unclear. Physical therapists would benefit from a clinic-friendly method for accurately quantifying movement patterns during functional tasks. Inertial sensors, which are inexpensive, portable sensors capable of monitoring multiple body segments simultaneously, are a relatively new rehabilitation technology. We sought to validate an inertial sensor system by comparing lower limb and lumbar spine kinematic data collected simultaneously with a commercial inertial sensor system and a motion camera system while 10 subjects performed functional tasks. Mean and peak segment angular displacement data were calculated and compared between systems. Mean angular displacement root mean square error between the systems across all tasks and segments was <5°. Mean differences in peak displacements were generally acceptable (<5°) for the femur, tibia, and pelvis segments for all tasks; however, the inertial system overestimated lumbar flexion compared to the motion camera system. These data suggest that the inertial system is capable of measuring angular displacements within 5° of a system widely accepted for its accuracy. Standardization of sensor placement, better attachment methods, and improvement of inertial sensor algorithms will further increase the accuracy of the system.
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Liu, Jun, Wenxue Guan, Guangjie Han, Jun-Hong Cui, Lance Fiondella, and Manal Al-Bzoor. "A Dynamic Surface Gateway Placement Scheme for Mobile Underwater Networks." Sensors 19, no. 9 (April 28, 2019): 1993. http://dx.doi.org/10.3390/s19091993.
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Deployment of surface-level gateways holds potential as an effective method to alleviate high-propagation delays and high-error probability in an underwater wireless sensor network (UWSN). This promise comes from reducing distances to underwater nodes and using radio waves to forward information to a control station. In an UWSN, a dynamic energy efficient surface-level gateway deployment is required to cope with the mobility of underwater nodes while considering the remote and three-dimensional nature of marine space. In general, deployment problems are usually modeled as an optimization problem to satisfy multiple constraints given a set of parameters. One previously published static deployment optimization framework makes assumptions about network workload, routing, medium access control performance, and node mobility. However, in real underwater environments, all these parameters are dynamic. Therefore, the accuracy of performance estimates calculated through static UWSN deployment optimization framework tends to be limited by nature. This paper presents the Prediction-Assisted Dynamic Surface Gateway Placement (PADP) algorithm to maximize the coverage and minimize the average end-to-end delay of a mobile underwater sensor network over a specified period. PADP implements the Interacting Multiple Model (IMM) tracking scheme to predict the positions of sensor nodes. The deployment is determined based on both current and predicted positions of sensor nodes, which enables better coverage and shorter end-to-end delay. PADP uses a branch-and-cut approach to solve the optimization problem efficiently, and employs a disjoint-set data structure to ensure connectivity. Simulation results illustrate that PADP significantly outperforms a static gateway deployment scheme.
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Peng, Tian, Maria Nogal, Joan R. Casas, and Jose Turmo. "Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method." Sensors 21, no. 9 (April 21, 2021): 2918. http://dx.doi.org/10.3390/s21092918.
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The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part.
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Khan, S. U., I. M. Qureshi, F. Zaman, B. Shoaib, A. Naveed, and A. Basit. "Correction of Faulty Sensors in Phased Array Radars Using Symmetrical Sensor Failure Technique and Cultural Algorithm with Differential Evolution." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/852539.
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Three issues regarding sensor failure at any position in the antenna array are discussed. We assume that sensor position is known. The issues include raise in sidelobe levels, displacement of nulls from their original positions, and diminishing of null depth. The required null depth is achieved by making the weight of symmetrical complement sensor passive. A hybrid method based on memetic computing algorithm is proposed. The hybrid method combines the cultural algorithm with differential evolution (CADE) which is used for the reduction of sidelobe levels and placement of nulls at their original positions. Fitness function is used to minimize the error between the desired and estimated beam patterns along with null constraints. Simulation results for various scenarios have been given to exhibit the validity and performance of the proposed algorithm.
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Navada, Venkata, and Rao. "A Soft Sensor for Estimation of In-Flow Rate in a Flow Process Using Pole Placement and Kalman Filter Methods." Machines 7, no. 4 (October 2, 2019): 63. http://dx.doi.org/10.3390/machines7040063.
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This article reports the design of a soft sensor for estimation of in-flow to the control valve in a flow process. The objective of the proposed work is to design and compare the performance of pole placement and Kalman filter-based observers. The observer is designed to estimate the in-flow from the measured out-flow. A mathematical model is derived for the considered physical plant using the system identification technique. An observer is designed using Pole Placement and Kalman Filter methods from the derived plant model. The obtained observer is implemented on a real-life setup for estimation of the in-flow rate. Results obtained from the designed observers are then analyzed to select the better observer. Comparison of performance based on results from Kalman Filter and Pole Placement method of observers shows that the former is more accurate, whereas the computation time is smaller in the latter. Results achieved from the designed soft sensor are verified using an electromagnetic flowmeter, and the results have a root-mean-square percentage error of 0.79%.
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Shafer, Benjamin M., Kent L. Gee, and Scott D. Sommerfeldt. "Verification of a near-field error sensor placement method in active control of compact noise sources." Journal of the Acoustical Society of America 127, no. 2 (February 2010): EL66—EL72. http://dx.doi.org/10.1121/1.3272632.
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Kammer, Daniel C. "Effect of model error on sensor placement for on-orbit modal identification of large space structures." Journal of Guidance, Control, and Dynamics 15, no. 2 (March 1992): 334–41. http://dx.doi.org/10.2514/3.20841.
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Zhan, Jie Zi, and Ling Yu. "An Effective Independence-Improved Modal Strain Energy Method for Optimal Sensor Placement of Bridge Structures." Applied Mechanics and Materials 670-671 (October 2014): 1252–55. http://dx.doi.org/10.4028/www.scientific.net/amm.670-671.1252.
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In this study, an effective independence-improved modal strain energy (EI-IMSE) method is proposed for the optimal sensor placement (OSP) problem in the field of the structural health monitoring and moving force identification. The improved modal strain energy (IMSE) is used to modify optimal sensor placement results obtained by the effective independence (EI) method. The EI-IMSE OSP method is verified by some numerical simulations on a 2D planar truss bridge model. Based on the criteria of modal assurance criterion (MAC), trace of fisher matrix, matrix condition number, and the least mean square error, the EI-IMSE OSP method is assessed through comparing with those of EI, EI-driving point residue (EI-DPR), EI-average driving DOF velocity (EI-ADDOFV), and EI-average acceleration amplitude (EI-AAA). The illustrated results show that the proposed EI-IMSE OSP method is feasible with a higher accuracy.
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Gavrilenkov, Sergey I. "A Framework for Optimal Placement of Strain Gauges on Elastic Elements of Force Sensors Using Genetic Algorithms." ITM Web of Conferences 35 (2020): 04010. http://dx.doi.org/10.1051/itmconf/20203504010.
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This paper presents a digital education tool for learning the specifics and behavior of a multi-objective genetic algorithm (MOGA) used to solve the problem of optimal placement of strain gauges on the elastic element of a force sensor. The paper formulates the problem statement and specifies how this problem can be solved using the MOGA. For the problem, the design variables are the locations of strain gauges and angles at which they are positioned. The goal functions are the output signal of the sensor and the measurement error from bending moments, which can be caused by the off-centric application of load. The solution algorithm is implemented within a framework that can be used to investigate and learn how parameters of MOGA influence its performance. The framework is used to run computational experiments for the given problem to find the optimal placement of strain gauges on the elastic element of a given force sensor. The performance of the MOGA in solving this problem is compared to that of the traditional approach.
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Adamowicz, Lukas, Reed Gurchiek, Jonathan Ferri, Anna Ursiny, Niccolo Fiorentino, and Ryan McGinnis. "Validation of Novel Relative Orientation and Inertial Sensor-to-Segment Alignment Algorithms for Estimating 3D Hip Joint Angles." Sensors 19, no. 23 (November 24, 2019): 5143. http://dx.doi.org/10.3390/s19235143.
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Wearable sensor-based algorithms for estimating joint angles have seen great improvements in recent years. While the knee joint has garnered most of the attention in this area, algorithms for estimating hip joint angles are less available. Herein, we propose and validate a novel algorithm for this purpose with innovations in sensor-to-sensor orientation and sensor-to-segment alignment. The proposed approach is robust to sensor placement and does not require specific calibration motions. The accuracy of the proposed approach is established relative to optical motion capture and compared to existing methods for estimating relative orientation, hip joint angles, and range of motion (ROM) during a task designed to exercise the full hip range of motion (ROM) and fast walking using root mean square error (RMSE) and regression analysis. The RMSE of the proposed approach was less than that for existing methods when estimating sensor orientation ( 12 . 32 ∘ and 11 . 82 ∘ vs. 24 . 61 ∘ and 23 . 76 ∘ ) and flexion/extension joint angles ( 7 . 88 ∘ and 8 . 62 ∘ vs. 14 . 14 ∘ and 15 . 64 ∘ ). Also, ROM estimation error was less than 2 . 2 ∘ during the walking trial using the proposed method. These results suggest the proposed approach presents an improvement to existing methods and provides a promising technique for remote monitoring of hip joint angles.