Academic literature on the topic 'Error sensor placement'
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Journal articles on the topic "Error sensor placement"
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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.
Dissertations / Theses on the topic "Error sensor placement"
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Shafer, Benjamin Michael. "Error sensor placement for active control of an axial cooling fan /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2119.pdf.
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Shafer, Benjamin M. "Error Sensor Placement for Active Control of an Axial Cooling Fan." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/1205.
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Recent experimental achievements in active noise control (ANC) for cooling fans have used near-field error sensors whose locations are determined according to a theoretical condition of minimized sound power. A theoretical point source model, based on the condition previously stated, reveals the location of near-field pressure nulls that may be used to optimize error sensor placement. The actual locations of these near-field pressure nulls for both an axial cooling fan and a monopole loudspeaker were measured over a two-dimensional grid with a linear array of microphones. The achieved global attenuation for each case is measured over a hemisphere located in the acoustic far field of the ANC system. The experimental results are compared to the theoretical pressure null locations in order to determine the efficacy of the point source model. The results closely matched the point source model with a loudspeaker as the primary source, and the sound power reduction was greatly reduced when error sensors were placed in non-ideal locations. A weakness of the current near-field modeling process is that a point monopole source is used to characterize the acoustic noise from an axial cooling fan, which may have multipole characteristics. A more complete characterization of fan noise may be obtained using a procedure based on the work of Martin and Roure [J. Sound Vib. 201 (5), 577--593 (1997)]. Pressure values are obtained over a hemisphere in the far field of a primary source and the contributions from point source distributions up to the second order, centered at the primary source, may be calculated using a multipole expansion. The source information is then used in the aforementioned theoretical near-field calculation of pressure. The error sensors are positioned using the complete fan characterization. The global far-field attenuation for the multipole expansion model of fan noise is compared to that of previous experiments. Results show that the multipole expansion model yields a more accurate representation the near field, but is not successful in achieving greater sound power reductions in the far field.
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Anderson, Monty J. "Active Control of the Human Voice from a Sphere." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5295.
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This work investigates the application of active noise control (ANC) to speech. ANC has had success reducing tonal noise. In this work, that success was extended to noise that is not completely tonal but has some tonal elements such as speech. Limitations such as causality were established on the active control of human speech. An optimal configuration for control actuators was developed for a sphere using a genetic algorithm. The optimal error sensor location was found from exploring the nulls associated with the magnitude of the radiated pressure with reference to the primary pressure field. Both numerically predicted and experimentally validated results for the attenuation of single frequency tones were shown. The differences between the numerically predicted results for attenuation with a sphere present in the pressure field and monopoles in the free-field are also discussed.The attenuation from ANC of both monotone and natural speech is shown and a discussion about the effect of causality on the results is given. The sentence “Joe took father’s shoe bench out” was used for both monotone and natural speech. Over this entire monotone speech sentence, the average attenuation was 8.6 dB with a peak attenuation of 10.6 dB for the syllable “Joe”. Natural speech attenuation was 1.1 dB for the sentence average with a peak attenuation on the syllable “bench” of 2.4 dB. In addition to the lower attenuation values for natural speech, the pressure level for the word “took” was increased by 2.3 dB. Also, the harmonic at 420 Hz in the word “father’s” of monotone speech was reduced globally up to 20 dB. Based on the results of the attenuation of monotone and natural speech, it was concluded that a reasonable amount of attenuation could be achieved on natural speech if its correlation could approach that of monotone speech.
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PUREKAR, DHANESH MADHUKAR. "A STUDY OF MODAL TESTING MEASUREMENT ERRORS, SENSOR PLACEMENT AND MODAL COMPLEXITY ON THE PROCESS OF FINITE ELEMENT CORRELATION." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1132015246.
Full textConference papers on the topic "Error sensor placement"
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Brewer, William V. "Error Model for Rotating Reference Frame Sensors Employed in the Space Station Module, Rack-Insertion End-Effector." In ASME 1998 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/detc98/mech-5992.
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Abstract Flight dynamics projections depend on estimates of the mass and its location for everything launched. It has been decided that these estimates will be made with the assistance of measurements taken by sensors installed on the Rack Insertion End Effector (RIEE). This error model is used to estimate accuracy that might be expected from the titled sensor placement scheme, taken as a whole, given the errors of component sensors and their placement.
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Flynn, Eric, and Michael Todd. "Optimal Sensor Placement for Active Sensing." In ASME 2008 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2008. http://dx.doi.org/10.1115/smasis2008-439.
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We present a novel approach for optimal actuator and sensor placement for active sensing-based structural health monitoring (SHM). Of particular interest is the optimization of actuator-sensor arrays making use of Lamb wave propagation for detecting damage in thin plate-like structures. Using a detection theory framework, we establish the optimum configuration as the minimization of the expected percentage of the structure to show type I or type II error during the damage detection process. The detector incorporates a statistical model of the active sensing process which implements both pulse-echo and pitch-catch actuation schemes and takes into account line of site and non-uniform damage probabilities. The optimization space was searched using a genetic algorithm with a time varying mutation rate. We provide four example actuator/sensor placement scenarios and the optimal solutions as generated by the algorithm.
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Khalil, Mohamed, Ioannis Kouroudis, Roland Wüchner, and Kai-Uwe Bletzinger. "Optimal Sensor Configuration for Fatigue Life Prediction in Structural Applications." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-8909.
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Abstract Structural health monitoring is spreading widely across engineering domains. Its added value is not restricted to observing structural behavior, but crosses over to enabling the assessment of structural integrity under varying operating conditions. Damage prognosis is one vital demand from structural health monitoring solutions. Many methods have been developed to update damage predictions based on sensor data, nonetheless the selection and positioning of sensors to alleviate the prediction errors remains a question under investigation. In this work, an optimal sensor placement method is proposed for fatigue damage prediction in structures. An optimization problem is formulated to minimize the a-posteriori damage estimation error based on a Kalman filter. The derivation of the objective function is presented, along with a discussion of algorithm-related issues. Finally, the mentioned damage prediction approach is applied to two structures to verify the adequacy of the sensor configurations proposed by the method.
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Kohara, Akira, Kunihisa Okano, Kentaro Hirata, and Yukinori Nakamura. "Sensor placement minimizing the state estimation mean square error: Performance guarantees of greedy solutions." In 2020 59th IEEE Conference on Decision and Control (CDC). IEEE, 2020. http://dx.doi.org/10.1109/cdc42340.2020.9304166.
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Xu, Jian, Kean Chen, and Yunhe Li. "Wave-Domain Optimization of Secondary Source Placement Free From Information of Error Sensor Positions." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9414622.
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KAMMER, DANIEL. "Effect of model error on sensor placement for on-orbit modal identification of Large Space Structures." In 32nd Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-1180.
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Owens, Patrick D., and A. Galip Ulsoy. "Self-Reproducing Machines: Preventing Degeneracy." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14201.
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Machines produced by humans exhibit insufficient complexity to produce similar machines. As John von Neumann originally postulated, if biological systems are able to successfully reproduce, then there must be some characteristic that we can embed in machines to give them the ability to reproduce. Such a self-reproductive machine, also imbued with the ability to do constructive work, could prove enormously useful to the human race. This paper considers a simple self-reproducing machine, which consists of a 2-DOF, planar robot arm capable of picking up and placing the components of another arm. If the robot places the components within the allowable tolerance, then the original arm has successfully reproduced. An assembly line is constructed, so that a self-reproduction process can proceed along a track. If this process eventually fails because one robot is not capable of assembling another, then the system is said to be degenerate. Otherwise, the system is sustainable. A kinematic model that maps component placement errors from one generation of the robot arm to the next was derived. The system exhibited exponential growth in component placement errors. Thus, this self-reproduction system is degenerate. This system is then augmented to provide error-correction during the assembly process. With the application of error-correction the self-reproduction process is made sustainable. The minimal amount of error-correction required to achieve sustainable self-reproduction was investigated through sensor quantization, and it was shown that the amount of fidelity in the error-correction signal determines the success of the self-reproduction process. This self-reproduction system was also analyzed in the context of Kabamba's Generation Theory, which could predict the results obtained through simulation regarding degeneracy or sustainability.
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Gutierrez, David, Nate Anderson, Chad Hanak, Tim Paton, Julia Vallejos, and Nick Brown. "Real-Time Wellbore Placement Improvement with High-Fidelity Trajectory Estimation and Dual-Sensor MWD Packages." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206253-ms.
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Abstract High-fidelity trajectory estimation combined with dual-probe Measurement-While-Drilling (MWD) directional instrumentation provides a solution to minimum curvature’s known inefficiencies in modeling the true wellbore position and definition (Stockhausen & Lesso, 2003). While it may not be cost efficient to increase survey frequency from the industry standard of 30ft-200ft, it is possible using the techniques defined in this research to maintain current survey intervals and increase wellbore placement accuracy while reducing positional uncertainty by up to 45% over the most advanced commercially available magnetic survey correction algorithms. Taking advantage of modern MWD tool platforms enables the installation of an additional (30-inch) survey measurement probe in the existing tool string with a fixed and known offset to the primary survey probe. Directional surveys from both survey probes are telemetered to surface at traditional course length survey intervals in real-time. The two surveys along with the known steering and non-steering intervals are processed through a high-fidelity trajectory estimation algorithm to quantify the wellbore behavior between survey stations. The result is a highly accurate and dense survey listing with modeled trajectory waypoints between traditional surveys to reduce the course length between directional measurement datapoints and better capture the true well path. Through extensive lab modeling, it was determined that the use of the dual-probe MWD package in combination with the high-fidelity trajectory estimation algorithm could result in a reduction in the Ellipse of Uncertainty (EOU) by 20% in the horizontal (semi-major) plane and 45% in the vertical (semi-minor) plane when compared to Multi-Station Analysis (MSA) and BHA Sag survey correction techniques. In addition to proof-of-concept modeling, the system has been deployed and used in real-time application on three separate pads, totaling nine wells. The results were able to validate and exceed baseline goals by exhibiting, on average, a reduction of the EOU by 21% in the horizontal plane and 58% in the vertical plane. Further, True Vertical Depth (TVD) error at well Total Depth (TD) in excess of 10ft was observed on three out of nine wells (33%) in this limited real-time application study. This difference was relative to separate, concurrent processing of the surveys via Multi-Station Analysis (MSA) and BHA sag corrections. This level of increased TVD accuracy is significant in many applications, depending on zone thickness and difficulty of geological interpretation. Increased accuracy and reduced uncertainty result from a better understanding of the true well path between traditional course length surveys. The trajectory estimation algorithm quantifies the rotational build/drop and walk rates in real-time and is reinforced by the dual-probe directional survey measurements. These tendencies can be used to better project forward to the bit as the well is drilled. Improved projection to the bit allows for enhanced recognition of deviation from the well plan and better-informed steering decisions.
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Augustine, Paul, Anoop K. Dhingra, and Deepak K. Gupta. "Dynamic Moving Load Identification Using Optimal Sensor Placement." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50701.
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A structure in service can be subjected to static, dynamic or moving loads. Several situations in practice involve estimation of moving loads which induce vibrations in the structure on which they are applied. An accurate estimation of these loads will ensure product quality and reliability of the final design, and mitigate the cost of structural health monitoring systems. The moving nature of dynamic loads increases the computational difficulty of the problem. One of the types of Inverse Problems involves estimation of the applied load from measured structural response such as strain or accelerations. Measuring response at a limited number of locations causes the unavailability of full set of structural response which can lead to inaccurate results. The unavailability of full structural response is mainly due to three reasons — (i) financial constraints limiting the number of sensors that can be used, (ii) inaccessibility of loading locations to place sensors, and (iii) sensor influence on structural response. The load recovered from such insufficient structural response data will be prone to errors. Ill-conditioning of the inverse problem can be eliminated by choosing optimum sensor locations on the structure, which leads to precise load estimate. No studies could be found which consider optimum sensor placement while recovering dynamic moving loads acting on a structure. In this paper, the recovery of the dynamic moving loads through measurement of structural response at a finite number of optimally selected locations is investigated. The developed algorithm is implemented using ANSYS APDL and MATLAB programming environment. Optimum sensor locations are identified using the D-optimal design algorithm and strain gages are placed at those locations. An algorithm is developed to utilize the strain data measured at optimum locations to estimate the moving load. The developed algorithm is applied to three example problems. The first example deals with the case where two orthogonal dynamic moving loads are applied at the same location. The second example involves a specific vehicle-bridge interaction problem. The vehicle is approximated as a half model consisting of two axles, where the dynamic loads from axles are modeled as point loads which move together. In both the cases, the estimated dynamic moving loads matched closely with the applied loads. In third example, the algorithm is also tested by adding 5% noise to the input response data. Even with random noise present in input strain data, the load estimates are obtained with a high degree of accuracy. Compared to conventional algorithms for estimating moving loads, the developed method makes the dynamic moving load recovery procedure accurate and relatively easy to implement.
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Pettys-Baker, Robert, Crystal Compton, Sophia Utset-Ward, Marc Tompkins, Brad Holschuh, and Lucy E. Dunne. "Design and Development of Valgus-Sensing Leggings." In 2017 Design of Medical Devices Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dmd2017-3526.
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Performing exercises, especially cutting and pivoting activities, with poor lower extremity mechanics can lead to severe damage of the knee, such as anterior cruciate ligament (ACL) tears [1]. A common movement pattern observed in at-risk athletes is knee valgus. This term refers to the medial collapse of the knee (when the knees falls inward towards the center of the body). Intervention to prevent knee valgus could reduce the chance of injury for at-risk athletes, or re-injury for those recovering from a knee injury. Currently, in patients with knee injuries, knee valgus is monitored by physical therapists, who observe a patient’s movements visually during exercise. The therapists instruct patients on how to identify valgus and how they might correct it. Visual diagnosis of valgus can be difficult and subjective, thereby allowing the unavoidable presence of human error. In addition, monitoring in real time is only possible when the patient is with a therapist. Several studies have focused on the issue of accurate detection of knee valgus by using a variety of systems such as 2D and 3D motion capture systems to track knee and hip movements, dynamometers, and electromyography [2][3][4]. Although these systems are able to determine knee valgus, they are difficult to use, require expensive equipment, and do not provide real-time feedback outside of the clinic setting. The purpose of this study was to inform the design of a valgus-sensing legging by exploring sensor placement options to maximize the magnitude of the sensor response difference between valgus and non-valgus knee bends.