Journal articles: 'Dynamic Error'

1

Bickhard, Mark H. "Error dynamics: the dynamic emergence of error avoidance and error vicariants." Journal of Experimental & Theoretical Artificial Intelligence 13, no. 3 (2001): 199–209. http://dx.doi.org/10.1080/09528130110067133.

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Lei, Dun Cai, Jin Yuan Tang, and Jian Jie Tang. "Gear Dynamic Transmission Error Testing." Advanced Materials Research 871 (December 2013): 352–57. http://dx.doi.org/10.4028/www.scientific.net/amr.871.352.

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A measuring device for gear dynamic transmission error test is developed based on NI Labview software, and a new type eccentric bushing structure that can simulate a variety of installation errors is presented. The hardware and software design of the gear dynamic transmission error measuring device is given, and the gear dynamic transmission errors for low-speed and high-speed in different loads are gotten based on the device and the measured data. Experimental dynamic transmission error results show that the gear dynamic transmission error measuring device is a stable and friendly interface with easy operation and high accuracy, able to do real-time detection and data acquisition for gearing.

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Wang, Jianhong, Teik C. Lim, and Liding Yuan. "Spur gear multi-tooth contact dynamics under the influence of bearing elasticity and assembly errors." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 227, no. 11 (2013): 2440–55. http://dx.doi.org/10.1177/0954406213477816.

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A numerical model is formulated to analyze the tooth contact dynamic load distribution and dynamic transmission error of a pair of spur gears under the influence of bearing elasticity and gearbox assembly errors. In the proposed model, the deformation of the tooth is computed by applying a combination of finite elements and contact mechanics. The elasticity of the bearings is represented with infinitesimal linear spring elements, while the shafts and gears except the teeth that are in engagement are assumed to be rigid bodies. Applying those assumptions, three sets of highly coupled governing equations representing the meshing teeth flexible behavior, gear-bearing assembly translation dynamics and gear rotation dynamics are derived. The resultant model is then used to predict the dynamical behaviors of the geared rotor system, tooth contact dynamic load, and dynamic transmission error. A set of parametric studies is also performed to analyze the gear dynamic response.

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Hou, Guo An, and Tao Sun. "Influence of FTS's Dynamic Character on the Machining Error." Key Engineering Materials 579-580 (September 2013): 580–83. http://dx.doi.org/10.4028/www.scientific.net/kem.579-580.580.

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Fast tool servo (FTS) is widely utilized to fabricate optical freeform surfaces with nanometric surface roughness and with sub-micrometric form errors. FTSs dynamics character plays the major part in many factors that influence machining error. In this paper, a dynamic model for FTS is built up to describe its dynamic and to analyze the effects on machining error under different work frequencies. It was found that FTS dynamic mainly affect the Y direction machining accuracy of the workpiece surface, with the increase of the working frequency of FTS, the error caused by FTS dynamic also increases rapidly.

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P, Woodburne, Zhao Y, Raehsler R, and Sohng S. "The Dynamic Phillips Curve Revisited: An Error Correction Model." International Journal of Advances in Management and Economics 1, no. 5 (2012): 01–04. http://dx.doi.org/10.31270/ijame/01/05/2012/01.

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Shestakov, A. L. "Dynamic error correction method." IEEE Transactions on Instrumentation and Measurement 45, no. 1 (1996): 250–55. http://dx.doi.org/10.1109/19.481342.

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Back, Juhoon, Kyung T. Yu, and Jin H. Seo. "Dynamic observer error linearization." Automatica 42, no. 12 (2006): 2195–200. http://dx.doi.org/10.1016/j.automatica.2006.07.009.

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Zhang, Yong Chao, Song Lin Wu, and Jun Feng Zhang. "Modeling of Dynamic Errors for a Table-Tilting Type 5-Axis Machine Tools." Advanced Materials Research 655-657 (January 2013): 1277–81. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.1277.

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The precision of its processes is affected by static error and dynamic error. This paper focuses on modeling about dynamic errors and proposed an algorithm of the dynamic error for Table-tilting 5-axis machine tool, which is using Homogeneous Transformation Matrix to establish the dynamic errors formula, so as to structure a model of its dynamic error. Dynamic errors about rotary and linear axis of a 5-axis machining center with tilting rotary table type are defined. At last, we performed the operation and measurement of Table-tilting 5-axis machine, in order to compare and verify the dynamic errors, and to use as adjusting the Table-tilting 5-axis machine tool, and improve the precision of its machining. The result of a synthesis example verifies the effectiveness of the proposed modeling.

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Nikolic, Mark I., and Nadine B. Sarter. "Modeling Error Recovery in Dynamic Collaborative Domains." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 3 (2002): 372–76. http://dx.doi.org/10.1177/154193120204600333.

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For many years, the focus of research in the area of human error was the prevention of erroneous actions and assessments through training and design. However, errors can never be eliminated completely. Therefore, the goal of more recent efforts is to minimize their negative consequences through support for error management, i.e., the detection, explanation, and recovery from erroneous actions. For the most part, these efforts have examined the first step in this sequence - error detection. In contrast, little is known about how operators explain and recover from errors. This is true especially for dynamic collaborative environments such as aviation. In this paper, we present findings from a survey and an incident report analysis that suggest the need for adapting the current model of error recovery. Specifically, we emphasize the importance of considering constraints imposed by specific domains in order to predict and explain the predominance and success of certain recovery strategies.

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Beck, Alexander, and Martin Ehrendorfer. "Singular-Vector-Based Covariance Propagation in a Quasigeostrophic Assimilation System." Monthly Weather Review 133, no. 5 (2005): 1295–310. http://dx.doi.org/10.1175/mwr2909.1.

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Abstract Variational data assimilation systems require the specification of the covariances of background and observation errors. Although the specification of the background-error covariances has been the subject of intense research, current operational data assimilation systems still rely on essentially static and thus flow-independent background-error covariances. At least theoretically, it is possible to use flow-dependent background-error covariances in four-dimensional variational data assimilation (4DVAR) through exploiting the connection between variational data assimilation and estimation theory. This paper reports on investigations concerning the impact of flow-dependent background-error covariances in an idealized 4DVAR system that, based on quasigeostrophic dynamics, assimilates artificial observations. The main emphasis is placed on quantifying the improvement in analysis quality that is achievable in 4DVAR through the use of flow-dependent background-error covariances. Flow dependence is achieved through dynamical error-covariance evolution based on singular vectors in a reduced-rank approach, referred to as reduced-rank Kalman filter (RRKF). The RRKF yields partly dynamic background-error covariances through blending static and dynamic information, where the dynamic information is obtained from error evolution in a subspace of dimension k (defined here through the singular vectors) that may be small compared to the dimension of the model’s phase space n, which is equal to 1449 in the system investigated here. The results show that the use of flow-dependent background-error covariances based on the RRKF leads to improved analyses compared to a system using static background-error statistics. That latter system uses static background-error covariances that are carefully tuned given the model dynamics and the observational information available. It is also shown that the performance of the RRKF approaches the performance of the extended Kalman filter, as k approaches n. Results therefore support the hypothesis that significant analysis improvement is possible through the use of flow-dependent background-error covariances given that a sufficiently large number (here on the order of n/10) of singular vectors is used.

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Wan, Ziping, Xin Xie, Aihua He, and Dapeng Fan. "Analysis on Influence Degree of Static and Dynamic Kinematics Error of EMA Pitch Servo Mechanism." Journal of Physics: Conference Series 2203, no. 1 (2022): 012006. http://dx.doi.org/10.1088/1742-6596/2203/1/012006.

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Abstract Aiming at the problem that the influence degree of static and dynamic accuracy of EMA pitch servo mechanism is not clear, this paper analyzes the influence degree of static and dynamic error of EMA pitch servo mechanism based on high-precision pointing system. In terms of static error, based on the static error kinematics model, by establishing the static error probability model and solving the static error model, it is pointed out that the geometric error is the largest factor affecting the static kinematics error. In terms of the influence degree of dynamic error, based on the dynamic error kinematics model, through the establishment of the dynamic error separation process, and based on the test and mechanical experiment platform, it is pointed out that the general trend error is the largest factor affecting the dynamic kinematics error. Through the analysis of the influence degree of static and dynamic kinematic errors, the accuracy improvement direction of the EMA pitch servo mechanism is defined.

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Lee, Hong-Gi, Kyung-Duk Kim, and Hong-Tae Jeon. "Restricted dynamic observer error linearizability." Automatica 53 (March 2015): 171–78. http://dx.doi.org/10.1016/j.automatica.2014.12.037.

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Епифанов, Сергей Валерьевич, та Ли Цицзе. "АНАЛИЗ ПОГРЕШНОСТЕЙ ЭКСПЕРИМЕНТАЛЬНОГО ОПРЕДЕЛЕНИЯ ДИНАМИЧЕСКИХ ХАРАКТЕРИСТИК ТЕРМОПАРЫ В УСЛОВИЯХ ДВИГАТЕЛЯ С ИСПОЛЬЗОВАНИЕМ СКАЧКООБРАЗНОГО ВОЗДЕЙСТВИЯ". Aerospace technic and technology, № 7 (31 серпня 2020): 31–40. http://dx.doi.org/10.32620/aktt.2020.7.05.

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The turbine inlet temperature is one of the major thermodynamic parameters that determine specific thrust and specific fuel consumption of the turbine engine. The gas temperature also influences the temperature of the engine parts, hence thermal stresses and the ability of materials to support static and cyclic loads. Therefore, the temperature limitation is one of the main tasks of the engine automatic control system. Because of a significant influence of the gas temperature on parameters of the working process, strength, and life-time of parts, the temperature must be limited with high precision.The paper is focused on dynamic parameters of the temperature measurement channel, which contains consequently linked engine, thermocouple, and the dynamic corrector. Errors of the corrector tuning, which mainly depend on the error of thermocouple time constant setting, cause dynamic errors in the temperature determining and the corresponding errors of automatic control. The paper considers the influence of the corrector tuning error on a dynamic error of the temperature determination. The equations are derived that relate the dynamic error with dynamic parameters of the engine and dynamic parameters of the temperature measurement channel. These equations can be used in the synthesis of this channel, which satisfies the set requirements to the temperature determining precision. The simplest case is considered when the thermocouple is represented as an inertial dynamic link, which single dynamic parameter is the time constant. Then the above-mentioned equations relate the thermocouple time constant with the error of temperature measurement and allow formulating requirements to a precision of its experimental determination.The final part of the paper considers the error of thermocouple time constant experimental determining. The relations are derived that allow analyzing this error under influence of such parameters as the measuring error, interval of observations, measuring frequency and dynamic properties of the engine and the thermocouple.

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Gibo, Tricia L., Sarah E. Criscimagna-Hemminger, Allison M. Okamura, and Amy J. Bastian. "Cerebellar motor learning: are environment dynamics more important than error size?" Journal of Neurophysiology 110, no. 2 (2013): 322–33. http://dx.doi.org/10.1152/jn.00745.2012.

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Cerebellar damage impairs the control of complex dynamics during reaching movements. It also impairs learning of predictable dynamic perturbations through an error-based process. Prior work suggests that there are distinct neural mechanisms involved in error-based learning that depend on the size of error experienced. This is based, in part, on the observation that people with cerebellar degeneration may have an intact ability to learn from small errors. Here we studied the relative effect of specific dynamic perturbations and error size on motor learning of a reaching movement in patients with cerebellar damage. We also studied generalization of learning within different coordinate systems (hand vs. joint space). Contrary to our expectation, we found that error size did not alter cerebellar patients' ability to learn the force field. Instead, the direction of the force field affected patients' ability to learn, regardless of whether the force perturbations were introduced gradually (small error) or abruptly (large error). Patients performed best in fields that helped them compensate for movement dynamics associated with reaching. However, they showed much more limited generalization patterns than control subjects, indicating that patients rely on a different learning mechanism. We suggest that patients typically use a compensatory strategy to counteract movement dynamics. They may learn to relax this compensatory strategy when the external perturbation is favorable to counteracting their movement dynamics, and improve reaching performance. Altogether, these findings show that dynamics affect learning in cerebellar patients more than error size.

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Kono, Daisuke, Sascha Weikert, Atsushi Matsubara, and Kazuo Yamazaki. "Estimation of Dynamic Mechanical Error for Evaluation of Machine Tool Structures." International Journal of Automation Technology 6, no. 2 (2012): 147–53. http://dx.doi.org/10.20965/ijat.2012.p0147.

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Dynamic motion errors of machine tools consist of errors in the mechanical system and the servo system. In this study, a simple method to estimate the dynamic mechanical error is proposed to evaluate machine tool structures. The dynamic mechanical error in the low frequency range is estimated from the static deformation due to the driving force, the counter force, and the inertial force. The error in a high-precision machine tool is estimated for comparison with measurements. Two calculation tools, finite element analysis and rigid multi-body simulation, are used for the estimation. Measured dynamic mechanical errors can be correctly estimated by the proposed method using finite element analysis. The tilt of driven bodies is the major reason for dynamic mechanical errors. When the reduction factor representing the structural deformation is properly determined, the rigid multi-body simulation is also an effective tool. Use of the proposed method for modification planning is demonstrated. Stiffness enhancement of the saddle was an effective modification candidate to reduce the dynamic mechanical error. If the error should be reduced to sub-micrometer level, the location of components should be modified because the Abbe offset and the offset of the driving force from the inertial force must be shortened.

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Baker, Dale A., and David A. Gough. "Dynamic Delay and Maximal Dynamic Error in Continuous Biosensors." Analytical Chemistry 68, no. 8 (1996): 1292–97. http://dx.doi.org/10.1021/ac960030d.

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Stewart, Chris, Mina Shokr, Gokhan Ibal, and Terry Caelli. "Circular Error Probables for Moving Targets: The Dynamic Error Probable." Journal of Guidance, Control, and Dynamics 39, no. 7 (2016): 1690–93. http://dx.doi.org/10.2514/1.g001706.

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PALANI, G. S., NAGESH R. IYER, and T. V. S. R. APPA RAO. "A POSTERIORI ERROR ESTIMATION AND H-ADAPTIVE REFINEMENT TECHNIQUES FOR TRANSIENT DYNAMIC ANALYSIS OF STIFFENED PLATE/SHELL PANELS." International Journal of Structural Stability and Dynamics 04, no. 02 (2004): 259–77. http://dx.doi.org/10.1142/s0219455404001227.

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This paper presents a posteriori error estimation and h-adaptive refinement techniques for transient dynamic analysis of stiffened plates/shells using the finite element method (FEM). We furnish the formulation of stiffness and mass matrices for finite element (FE) models, QL9S2 and QUAD4S2 for dynamic analysis of plates/shells with arbitrarily-located concentric/eccentric stiffeners. Procedures for computing a posteriori errors for spatial and temporal errors have been presented for transient dynamic problems. An h-adaptive refinement strategy for stiffened plate/shell panels by employing QL9S2 and QUAD4S2 FE models has been discussed. An adaptive time stepping scheme, which is to be used with the time errors for quality control of the time steps, has also been presented. Numerical studies have been conducted to evaluate the efficacy of the error estimators and the adaptive mesh refinement and time stepping algorithm. The spatial error estimator for transient dynamic analysis is found to exhibit monotonic convergence at all time steps. The temporal error estimator for transient dynamic analysis in association with the adaptive time stepping is able to compute more accurate and reliable time steps to keep the time errors within the specified tolerance limits.

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Callaghan, Jack P., Kiera Keown, and David M. Andrews. "Influence of dynamic factors on calculating cumulative low back loads." Occupational Ergonomics 5, no. 2 (2005): 89–97. http://dx.doi.org/10.3233/oer-2005-5202.

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This study examined the error induced in estimating cumulative low back loading for exposure to dynamic manual materials handling tasks by using either static or quasi-dynamic biomechanical models when compared to a dynamic model. Ten male subjects performed three sagittal plane lifting tasks at three different lifting speeds and using three different hand loads. Digitized video recordings and measured hand forces were collected in order to calculate cumulative L4/L5 spinal loading (compression, moment, joint shear, and reaction shear) using rigid link and single muscle equivalent biomechanical models. Cumulative loading was calculated using three modeling approaches: static, quasi-dynamic, and dynamic. The calculation of cumulative loading using the dynamic model was set as the "gold standard" and error in the static and quasi-dynamic approaches was determined by comparison with the dynamic model. The use of a quasi-dynamic model resulted in an average error of −2.76% across all 10 subjects, 3 tasks, 3 lifting speeds and 3 masses. The static model had an average error of −12.55%. The error in both modeling approaches was significantly effected by the type of task performed, mass lifted, speed of lift, and model variable examined indicating that neither model produced consistent errors across the lifting parameters. The small errors associated with the quasi-dynamic model indicates that it holds promise as a method to reduce the amount of data required to estimate cumulative loading yet still preserve the dynamic loading exposure of a manual materials handling task.

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Frías-Paredes, Laura, Fermin Mallor, Martín Gastón-Romeo, and Teresa León. "Dynamic mean absolute error as new measure for assessing forecasting errors." Energy Conversion and Management 162 (April 2018): 176–88. http://dx.doi.org/10.1016/j.enconman.2018.02.030.

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Wang, Hong Ying, and Xue Me Hu. "Based on the Nc Machining System Error Aspheric Analysis and Research." Advanced Materials Research 383-390 (November 2011): 7649–53. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.7649.

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From the machining errors and static dynamic error influence two aspects are discussed in this paper, the analysis of machining process on the processing precision influence of error, puts forward process design. Long-term since, improving precision machine tool is through the two methods: error and avoid error compensation. Avoid error is a "hard", focusing on design and processing in the error may eliminate all stages. And error compensation in existing machine, can work environment to further improve the machining precision, it is a kind of economic effectively improve the machining precision of the method. For error analysis and calculation, the ultimate goal is to eliminate and reduce processing error, the improvement of the machining errors of classification in many ways. According to the machining process of the factors causing error to occur any regularity, processing error into system error and the random error, According to the nature of the changes with time, and can be divided into static error and dynamic error.

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Xu, Rui, Yaoyao Wang, Xianle Shi, Ningning Wang, and Dong Ming. "The Effect of Static and Dynamic Visual Stimulations on Error Detection Based on Error-Evoked Brain Responses." Sensors 20, no. 16 (2020): 4475. http://dx.doi.org/10.3390/s20164475.

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Error-related potentials (ErrPs) have provided technical support for the brain-computer interface. However, different visual stimulations may affect the ErrPs, and furthermore, affect the error recognition based on ErrPs. Therefore, the study aimed to investigate how people respond to different visual stimulations (static and dynamic) and find the best time window for different stimulation. Nineteen participants were recruited in the ErrPs-based tasks with static and dynamic visual stimulations. Five ErrPs were statistically compared, and the classification accuracies were obtained through linear discriminant analysis (LDA) with nine different time windows. The results showed that the P3, N6, and P8 with correctness were significantly different from those with error in both stimulations, while N1 only existed in static. The differences between dynamic and static errors existed in N1 and P2. The highest accuracy was obtained in the time window related to N1, P3, N6, and P8 for the static condition, and in the time window related to P3, N6, and P8 for the dynamic. In conclusion, the early components of ErrPs may be affected by stimulation modes, and the late components are more sensitive to errors. The error recognition with static stimulation requires information from the entire epoch, while the late windows should be focused more within the dynamic case.

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Krupanek, Beata. "Dynamic Error Correction of Methane Sensor." International Journal of Electronics and Telecommunications 60, no. 4 (2014): 287–89. http://dx.doi.org/10.2478/eletel-2014-0037.

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Abstract Coal mine methane is a term given to the methane gas produced or emitted in association with coal mining activities either from the coal seam itself or from other gassy formations underground. The primary reason for measuring methane is to improve the safety of the mines. In recent years, there have been many fatalities in underground coal mine explosions in which methane was a contributing factor. The rapid detection of methane is very important from the point of view of safety of mine workers. This paper presents a concept of fast methane detection by reconstituting its concentration in dynamic states.

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Yang, Jongwook, Juhoon Back, Jin H. Seo, and Hyungbo Shim. "Reduced-order Dynamic Observer Error Linearization." IFAC Proceedings Volumes 43, no. 14 (2010): 915–20. http://dx.doi.org/10.3182/20100901-3-it-2016.00285.

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CHE, Hong Bo, Jin Wook KIM, Tae Il BAE, and Young Hwan KIM. "Accelerating Relaxation Using Dynamic Error Prediction." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E92-A, no. 2 (2009): 648–51. http://dx.doi.org/10.1587/transfun.e92.a.648.

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Van Dijk, N. M., and K. Sladký. "Error Bounds for Nonnegative Dynamic Models." Journal of Optimization Theory and Applications 101, no. 2 (1999): 449–74. http://dx.doi.org/10.1023/a:1021749829267.

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Kong, Mingfang, Bingzhen Chen, Xiaorong He, and Shanying Hu. "Gross error identification for dynamic system." Computers & Chemical Engineering 29, no. 1 (2004): 191–97. http://dx.doi.org/10.1016/j.compchemeng.2004.07.008.

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Bodnar, Taras, and Nikolaus Hautsch. "Dynamic conditional correlation multiplicative error processes." Journal of Empirical Finance 36 (March 2016): 41–67. http://dx.doi.org/10.1016/j.jempfin.2015.12.002.

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Song, Ki-Young, Madan M. Gupta, and Noriyasu Homma. "Design of an Error-Based Adaptive Controller for a Flexible Robot Arm Using Dynamic Pole Motion Approach." Journal of Robotics 2011 (2011): 1–9. http://dx.doi.org/10.1155/2011/726807.

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Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we introduce a novel concept ofdynamic pole motion(DPM) for the design of an error-based adaptive controller (E-BAC). The purpose of this novel design approach is to make the system response reasonably fast with no overshoot, where the system may be time varying and nonlinear with only partially known dynamics. The E-BAC is implanted in a system as a nonlinear controller with two dominant dynamic parameters: the dynamic position feedback and the dynamic velocity feedback. For illustrating the strength of this new approach, in this paper we give an example of a flexible robot with nonlinear dynamics. In the design of this feedback adaptive controller, parameters of the controller are designed as a function of the system error. The position feedbackKp(e,t)and the velocity feedbackKv(e,t)are continuously varying and formulated as a function of the system errore(t). This approach for formulating the adaptive controller yields a very fast response with no overshoot.

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Chen, Guo Da, Ying Chun Liang, He Ran Wang, Ya Zhou Sun, and Jia Xuan Chen. "Frequency Domain Error Analysis in Ultra-Precision Flycutting." Key Engineering Materials 620 (August 2014): 96–103. http://dx.doi.org/10.4028/www.scientific.net/kem.620.96.

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In some special fields such as precision optics, the part surface has strict requirements on the frequency domain errors, besides the conventional spatial domain errors such as surface roughness error. In light of the available works lacking of the frequency domain error analysis in ultra-precision flycutting, this paper therefore presents its frequency domain error analysis. A case study of KDP crystal flycutting is carried out to show its detailed processes, where the processing parameters, tool geometry, motion dynamic error of the machine guideway and tool-work vibration induced dynamic error are considered. A surface profile generation method is put forward. Two cases with different tool-work vibration frequencies are carried out. The spatial frequency spectrum is obtained based on the FFT analysis of the generated profile in the specified direction. After the in-depth analysis, the inherent correlation of the generated spatial frequency components with feed spatial frequency and machine dynamic errors induced spatial frequency under certain machining conditions are found, which is very meaningful for the frequency domain error prediction in the real application. The proposed analysis method can also be applied into other types of surface machining.

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Piprek, Patrick, Michael M. Marb, Pranav Bhardwaj, and Florian Holzapfel. "Trajectory/Path-Following Controller Based on Nonlinear Jerk-Level Error Dynamics." Applied Sciences 10, no. 23 (2020): 8760. http://dx.doi.org/10.3390/app10238760.

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This study proposes a novel, nonlinear trajectory/path-following controller based on jerk-level error dynamics. Therefore, at first the nonlinear acceleration-based kinematic equations of motion of a dynamic system are differentiated with respect to time to obtain a representation connecting the translation jerk with the (specific) force derivative. Furthermore, the path deviation, i.e., the difference between the planned and the actual path, is formulated as nonlinear error dynamics based on the jerk error. Combining the derived equations of motion with the nonlinear error dynamics as well as employing nonlinear dynamic inversion, a control law can be derived that provides force derivative commands, which may be commanded to an inner loop for trajectory control. This command ensures an increased smoothness and faster reaction time compared to traditional approaches based on a force directly. Furthermore, the nonlinear parts in the error dynamic are feedforward components that improve the general performance due to their physical connection with the real dynamics. The validity and performance of the proposed trajectory/path-following controller are shown in an aircraft-related application example.

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Lorimer, Tom, Rachel Goodridge, Antonia K. Bock, et al. "Tracking changes in behavioural dynamics using prediction error." PLOS ONE 16, no. 5 (2021): e0251053. http://dx.doi.org/10.1371/journal.pone.0251053.

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Automated analysis of video can now generate extensive time series of pose and motion in freely-moving organisms. This requires new quantitative tools to characterise behavioural dynamics. For the model roundworm Caenorhabditis elegans, body pose can be accurately quantified from video as coordinates in a single low-dimensional space. We focus on this well-established case as an illustrative example and propose a method to reveal subtle variations in behaviour at high time resolution. Our data-driven method, based on empirical dynamic modeling, quantifies behavioural change as prediction error with respect to a time-delay-embedded ‘attractor’ of behavioural dynamics. Because this attractor is constructed from a user-specified reference data set, the approach can be tailored to specific behaviours of interest at the individual or group level. We validate the approach by detecting small changes in the movement dynamics of C. elegans at the initiation and completion of delta turns. We then examine an escape response initiated by an aversive stimulus and find that the method can track return to baseline behaviour in individual worms and reveal variations in the escape response between worms. We suggest that this general approach—defining dynamic behaviours using reference attractors and quantifying dynamic changes using prediction error—may be of broad interest and relevance to behavioural researchers working with video-derived time series.

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Rezaiamin, Abdoolkarim, Marzieh Pazokian, Mansoureh Zagheri Tafreshi, and Malihe Nasiri. "The Relationship Between Work Commitment, Dynamic, and Medication Error." Clinical Nursing Research 27, no. 6 (2017): 660–74. http://dx.doi.org/10.1177/1054773817707290.

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Incidence of medication errors in intensive care unit (ICU) can cause irreparable damage for ICU patients. Therefore, it seems necessary to find the causes of medication errors in this section. Work commitment and dynamic might affect the incidence of medication errors in ICU. To assess the mentioned hypothesis, we performed a descriptive-analytical study which was carried out on 117 nurses working in ICU of educational hospitals in Tehran. Minick et al., Salyer et al., and Wakefield et al. scales were used for data gathering on work commitment, dynamic, and medication errors, respectively. Findings of the current study revealed that high work commitment in ICU nurses caused low number of medication errors, including intravenous and nonintravenous. We controlled the effects of confounding variables in detection of this relationship. In contrast, no significant association was found between work dynamic and different types of medication errors. Although the study did not observe any relationship between the dynamics and rate of medication errors, the training of nurses or nursing students to create a dynamic environment in hospitals can increase their interest in the profession and increase job satisfaction in them. Also they must have enough ability in work dynamic so that they don’t confused and distracted result in frequent changes of orders, care plans, and procedures.

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Chen, Yao, Mo Huang, Yuanyuan Zhang, Changyuan Wang, and Tao Duan. "An Analytical Method for Dynamic Wave-Related Errors of Interferometric SAR Ocean Altimetry under Multiple Sea States." Remote Sensing 13, no. 5 (2021): 986. http://dx.doi.org/10.3390/rs13050986.

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The spaceborne interferometric synthetic aperture radar (InSAR) is expected to measure the sea surface height (SSH) with high accuracy over a wide swath. Since centimeter-level accuracy is required to monitor the ocean sub-mesoscale dynamics, the high accuracy implies that the altimetric errors should be totally understood and strictly controlled. However, for the dynamic waves, they move randomly all the time, and this will lead to significant altimetric errors. This study proposes an analytical method for the dynamic wave-related errors of InSAR SSH measurement based on the wave spectrum and electromagnetic scattering model. Additionally, the mechanisms of the dynamic wave-related errors of InSAR altimetry are analyzed, and the detailed numerical model is derived. The proposed analytical method is validated with NASA’s Surface Water and Ocean Topography (SWOT) project error budget, and the Root-Mean-Square Errors (RMSEs) are in good agreement (0.2486 and 0.2470 cm on a 0.5 km2 grid, respectively). Instead of analysis for a typical project, the proposed method can be applied to different radar parameters under multiple sea states. The RMSEs of Ka-band under low sea state, moderate sea state, and high sea state are 0.2670, 1.3154, and 6.6361 cm, respectively. Moreover, the RMSEs of X-band and Ku-band are also simulated and presented. The experimental results demonstrate that the dynamic wave-related errors of InSAR altimetry are not sensitive to the frequencies but are sensitive to the sea states. The error compensation method is necessary for moderate and higher sea states for centimetric accuracy requirements. This can provide feasible suggestions on system design and error budget for the future interferometric wide-swath altimeter.

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Qiu, Jian. "Study on Spindle Dynamic Errors of Domestic NC Machine Tools." Advanced Materials Research 690-693 (May 2013): 3279–83. http://dx.doi.org/10.4028/www.scientific.net/amr.690-693.3279.

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This paper explains a set of tests necessary for ensuring spindle performance focus on the rotating sensitive direction of spindle. It is found that the original signals of spindle dynamic rotation could be separated and reconstructed to spindle dynamic signal and random signal according to their different frequency components. The asynchronous error and synchronization error of spindle dynamic rotation in radial direction and axial direction could be computed from spindle dynamic signal. The distribution trend of spindle dynamic errors is studied, it is found without considering the shift speed of machine tool spindle and the natural frequency of machine tool, the distribution of spindle dynamic errors presented a trend of rising with the rotation speed increasing.

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Zeng, Huang Lin, Yong Sun, Xiao Hong Ren, and Li Xin Liu. "Error Compensation of a NC Machining System Based on a Dynamic Feedback Neural Network." Applied Mechanics and Materials 52-54 (March 2011): 1890–94. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.1890.

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Machining error of a NC machining system is a kind of comprehensive error in dynamically machining process; especially it is of errors with non-linear characteristics. In this paper, we will set up a kind of model of comprehensive errors analysis for a NC machining system and present an error compensation for high-precision a NC machining system by a dynamic feedback neural network embedded in a NC machine tool. The results obtained shows that this approach can effectively improve compensation precision and real time of error compensation on machine tools.

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Punt, Andre E. "Extending production models to include process error in the population dynamics." Canadian Journal of Fisheries and Aquatic Sciences 60, no. 10 (2003): 1217–28. http://dx.doi.org/10.1139/f03-105.

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Four methods for fitting production models, including three that account for the effects of error in the population dynamics equation (process error) and when indexing the population (observation error), are evaluated by means of Monte Carlo simulation. An estimator that represents the distributions of biomass explicitly and integrates over the unknown process errors numerically (the NISS estimator) performs best of the four estimators considered, never being the worst estimator and often being the best in terms of the medians of the absolute values of the relative errors. The total-error approach outperforms the observation-error estimator conventionally used to fit dynamic production models, and the performance of a Kalman filter based estimator is particularly poor. Although the NISS estimator is the best-performing estimator considered, its estimates of quantities of management interest are severely biased and highly imprecise for some of the scenarios considered.

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Guo, Fang, and Zongde Fang. "Experimental and Theoretical Study of Gear Dynamical Transmission Characteristic Considering Measured Manufacturing Errors." Shock and Vibration 2018 (November 4, 2018): 1–20. http://dx.doi.org/10.1155/2018/9645453.

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In the research of gear transmission, the vibration and noise problem has received many concerns all the times. Scholars use tooth modification technique to improve the meshing state of gearings in order to reduce the vibration and noise. However, few of researchers consider the influence of measured manufacturing errors when they do the study of tooth modification. In order to investigate the efficiency of the tooth modification in the actual project, this paper proposes a dynamic model of a helical gear pair including tooth modification and measured manufacturing errors to do a deterministic analysis on the dynamical transmission performance. In this analysis, based on the measured tooth deviation, a real tooth surface (including modification and measured tooth profile error) is fitted by a bicubic B-spline. With the tooth contact analysis (TCA) and loaded tooth contact analysis (LTCA) on the real tooth surface, the loaded transmission error, tooth surface elastic deformation, and load distribution can be determined. Based on the results, the time-varying mesh stiffness and gear mesh impact are computed. Taking the loaded transmission error, measured cumulative pitch error, eccentricity error, time-varying mesh stiffness, and gear mesh impact as the internal excitations, this paper establishes a 12-degree-of-freedom (DOF) dynamic model of a helical gear pair and uses the Fourier series method to solve it. In two situations of low speed and high speed, the gear system dynamic response is analyzed in the time and frequency domains. In addition, an experiment is performed to validate the simulation results. The study shows that the proposed technique is useful and reliable for predicting the dynamic response of a gear system.

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Atanasiu, Virgil, Cezar Oprişan, and Dumitru Leohchi. "The Effect of Tooth Wear on the Dynamic Transmission Error of Helical Gears with Smaller Number of Pinion Teeth." Applied Mechanics and Materials 657 (October 2014): 649–53. http://dx.doi.org/10.4028/www.scientific.net/amm.657.649.

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The paper presents an analytical investigation of the effect of the tooth wear on the dynamic transmission error of helical gear pairs with small number of pinion teeth. Firstly, the dynamic analysis is conducted to investigate only the effect of the time-varying mesh stiffness on the variation of dynamic transmission error along the line of action. Then, the tooth wear effect on the dynamics of helical gear with small number of pinion teeth is being researched. In the analysis, instantaneous dynamic contact analysis is used in wear depth calculations. A comparative study was performed to investigate the relation between total contact ratio, mesh stiffness and dynamic transmission error of helical gear pairs with small number of teeth.

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Spindler, A., and P. A. Vanrolleghem. "Dynamic mass balancing for wastewater treatment data quality control using CUSUM charts." Water Science and Technology 65, no. 12 (2012): 2148–53. http://dx.doi.org/10.2166/wst.2012.125.

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Mass balancing is a widely used tool for data quality control in wastewater treatment. It can effectively detect systematic errors in data. To overcome the limitations of the mean balancing error as a measure of data quality, a well established method for statistical process control (the CUSUM chart) is adopted for application on the error vector of balancing data. Two examples show how time periods with stable low mass balancing errors can be detected by the method. The detectability of such time periods depends on the variability of the balancing error which is an important measure for the precision of the data.

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Zhang, Jing Mei, Lei Xue, Rui Min Zhang, and Chang Yin Sun. "Robust Tracking Control for 3 DOF Helicopter Based on Least Squares Support Vector Machine." Applied Mechanics and Materials 313-314 (March 2013): 370–73. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.370.

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A robust tracking control method for 3 DOF helicopter via least squares support vector machine with considering uncertainty and bounded disturbance is proposed in this paper. The inversion errors which is brought due to modeling errors and uncertainty can be compensated by least squares support vector machine, and the optimal regulator guaranteed dynamic characteristics of approximate linearization system and response quality of tracking error dynamic. Finally, the stability and convergence analysis of error dynamic system is proven by Lyapunov stability theory and numerical simulations have demonstrated the effectiveness of the proposed approach.

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Shan, Li Jun, Yu Ting Liu, and Wei Dong He. "Analysis of Nonlinear Dynamic Accuracy on RV Transmission System ." Advanced Materials Research 510 (April 2012): 529–35. http://dx.doi.org/10.4028/www.scientific.net/amr.510.529.

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RV (Rotate Vector) transmission is a new precision transmission system. In order to improve its accuracy, we study the RV transmission system. It is researched in comprehensive factors including displacement errors, elastic deformation (static transmission error, design transmission error), gear meshing errors, backlash of gear, time-varying mesh stiffness, mesh damping, bearing stiffness, torsional stiffness of input shaft, etc. The mathematical and mechanical model of dynamic transmission accuracy is established by the concentrated mass method and the dynamic substructure method. Then, the meshing force of each part is analyzed in RV reducer. The motion differential equation of RV drive system is obtained, which lays the foundation for the calculation and analysis of the transmission error.

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Zhang, Yanshun, Chuang Peng, Dong Mou, Ming Li, and Wei Quan. "An Adaptive Filtering Approach Based on the Dynamic Variance Model for Reducing MEMS Gyroscope Random Error." Sensors 18, no. 11 (2018): 3943. http://dx.doi.org/10.3390/s18113943.

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To improve the dynamic random error compensation accuracy of the Micro Electro Mechanical System (MEMS) gyroscope at different angular rates, an adaptive filtering approach based on the dynamic variance model was proposed. In this paper, experimental data were utilized to fit the dynamic variance model which describes the nonlinear mapping relations between the MEMS gyroscope output data variance and the input angular rate. After that, the dynamic variance model was applied to online adjustment of the Kalman Filter measurement noise coefficients. The proposed approach suppressed the interference from the angular rate in the filtering results. Dynamic random errors were better estimated and reduced. Turntable experiment results indicated that the adaptive filtering approach compensated for the MEMS gyroscope dynamic random error effectively both in the constant angular rate condition and the continuous changing angular rate condition, thus achieving adaptive dynamic random error compensation.

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Zhao, Zewei, and Houfeng Wang. "MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (2020): 1226–33. http://dx.doi.org/10.1609/aaai.v34i01.5476.

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Grammatical error correction (GEC) is a promising natural language processing (NLP) application, whose goal is to change the sentences with grammatical errors into the correct ones. Neural machine translation (NMT) approaches have been widely applied to this translation-like task. However, such methods need a fairly large parallel corpus of error-annotated sentence pairs, which is not easy to get especially in the field of Chinese grammatical error correction. In this paper, we propose a simple yet effective method to improve the NMT-based GEC models by dynamic masking. By adding random masks to the original source sentences dynamically in the training procedure, more diverse instances of error-corrected sentence pairs are generated to enhance the generalization ability of the grammatical error correction model without additional data. The experiments on NLPCC 2018 Task 2 show that our MaskGEC model improves the performance of the neural GEC models. Besides, our single model for Chinese GEC outperforms the current state-of-the-art ensemble system in NLPCC 2018 Task 2 without any extra knowledge.

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Smallwood, David. "Validation of Measured Dynamic Data Using Rigid Body Response." Journal of the IEST 55, no. 1 (2012): 25–39. http://dx.doi.org/10.17764/jiet.55.1.2171387035102w27.

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As multiple axis vibration testing has become more widespread, it has become increasingly important to ensure the instrumentation is accurately portrayed in the instrumentation table. However, errors do occur. The method used in this paper to help uncover these errors is based on the condition that at low frequencies (below any resonant frequencies of the object being studied) the response is essentially rigid body. The spectral density matrix (SDM) at a low frequency, of many more than six response measurements, is decomposed using singular value decomposition (SVD). Under the assumption of rigid body response, it is assumed that the first six singular vectors are linear combinations of the six rigid body modes. The best linear fit is then calculated for this fit. The measurements are then removed one at a time, and the reduction in the fit error is calculated. It is assumed that if the removal of a measurement reduces the error significantly, that measurement is likely in error.

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Muhammad, Wazir, Lee Hoon, Khan Alam, Muhammad Maqbool, and Gulzar Khan. "Dose non-linearity of the dosimetry system and possible monitor unit errors on medical linear accelerators used in conventional and intensity-modulated radiation therapy." Nuclear Technology and Radiation Protection 27, no. 4 (2012): 368–73. http://dx.doi.org/10.2298/ntrp1204368m.

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The purpose of this work is to study dose non-linearity in medical linear accelerators used in conventional radiotherapy and intensity-modulated radiation therapy. Open fields, as well as the enhanced dynamic wedge ones, were used to collect data for 6 MV and 15 MV photon beams obtained from the VARIAN linear accelerator. Beam stability was checked and confirmed for different dose rates, energies, and application of enhanced dynamic wedge by calculating the charge per monitor unit. Monitor unit error was calculated by the two-exposure method for open and enhanced dynamic wedge beams of 6 MV and 15 MV photons. A significant monitor unit error with maximum values of ?2.05931 monitor unit and ?2.44787 monitor unit for open and enhanced dynamic wedge beams, respectively, both energy and dose rate dependent, was observed both in the open photon beam and enhanced dynamic wedge fields. However, it exhibited certain irregular patterns at enhanced dynamic wedge angles. Dose monitor unit error exists only because of the overshoot phenomena and electronic delay in dose coincident and integrated circuits with a dependency on the dose rate and photon energy. Monitor unit errors are independent of the application of enhanced dynamic wedge. The existence of monitor unit error demands that the dose non-linearity of the linear accelerator dosimetry system be periodically tested, so as to avoid significant dosimetric errors.

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Jin, Shou-Song, Xiao-Tao Tong, and Ya-Liang Wang. "Influencing Factors on Rotate Vector Reducer Dynamic Transmission Error." International Journal of Automation Technology 13, no. 4 (2019): 545–56. http://dx.doi.org/10.20965/ijat.2019.p0545.

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The factors influencing rotate vector (RV) reducer dynamic transmission error were studied using virtual prototyping technology, which contained the elastic deformation, working load, part manufacturing error, and assembly clearance. According to the error transmission relationship of the RV reducer, 15 influencing factors were selected to design an orthogonal simulation test. The virtual prototype of the RV reducer was built using CREO and ANSYS, and imported into ADAMS for multi-body dynamics simulation. The simulation method reliability was verified via experiments. The results show that the circle center radius error of the pin gear, the amount of equidistant modification of the cycloid gear, the amount of radial-moving modification of the cycloid gear, the clearance between the support bushing and planet carrier, and the clearance between the crankshaft and the support bushing were positively correlated with the RV reducer dynamic transmission error. Among these, the circle center radius error of the pin gear has the greatest influence on the dynamic transmission error of the RV reducer followed by the amount of equidistant modification of the cycloid gear. The elastic deformation of the part and the load fluctuation show a certain gain effect on the transmission error, the elastic deformation of the cycloid gear has a great influence, and the elastic deformation of the pin gear has the least.

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Agarwal, Arpita, Nikhil Rastogi, KJ Maria Das, et al. "Evaluating the dosimetric consequences of MLC leaf positioning errors in dynamic IMRT treatments." Journal of Radiotherapy in Practice 18, no. 03 (2019): 225–31. http://dx.doi.org/10.1017/s1460396918000705.

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AbstractPurposeThe purpose of this study was to evaluate the dosimetric impact of multileaf collimator (MLC) positional errors on dynamic intensity-modulated radiotherapy (IMRT) treatments through planning simulation. Secondly the sensitivity of IMRT MatriXX device for detecting the MLC leaf positional errors was also evaluated.Materials and methodsIn this study five dynamic IMRT plans, each for brain and head–neck (HN), were retrospectively included. An in-house software was used to introduce random errors (uniform distribution between −2·0 and +2·0 mm) and systematic errors [±0·5, ±0·75, ±1·0 and ±2·0 mm (+: open MLC error and −: close MLC error)]. The error-introduced MLC files were imported into the treatment planning system and new dose distributions were calculated. Furthermore, the dose–volume histogram files of all plans were exported to in-house software for equivalent uniform dose (EUD), tumour control probability and normal tissue complication probability calculations. The error-introduced plans were also delivered on LINAC, and the planar fluences were measured by IMRT MatriXX. Further, 3%/3 mm and 2%/2 mm γ-criteria were used for analysis.ResultsIn planning simulation study, the impact of random errors was negligible and ΔEUD was &lt;0·5±0·7%, for both brain and HN. The impact of systematic errors was substantial, and on average, the maximum change in EUD for systematic errors (close 2 mm) was −10·7±3·1% for brain and −15·5±2·6% for HN.ConclusionsIt can be concluded that the acceptable systematic error was 0·4 mm for brain and 0·3 mm for HN. Furthermore, IMRT MatriXX device was able to detect the MLC errors ≥2 mm in HN and &gt;3 mm errors in brain with 2%/2 mm γ-criteria.

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Chen, Zaigang, and Yimin Shao. "Dynamic features of planetary gear train with tooth errors." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229, no. 10 (2014): 1769–81. http://dx.doi.org/10.1177/0954406214549503.

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As one of the inherited displacement excitation sources which are related to the gear vibration and noise problems, gear transmission error always consists of two parts: gear tooth geometric error and tooth elastic deformation under transmitted load. The gear tooth geometric errors were directly employed as the displacement excitations in previous papers, which are not accurate. In this paper, a new method is developed to transform the gear tooth errors (TEs) to be the appropriate dynamic excitations through the mesh stiffness and the unloaded static transmission error (USTE), where the obtained displacement excitation curves, namely the USTE curves, are very different from the TE curves. Incorporation of the proposed model into the dynamic model of a planetary gear train enables the investigation of the TE effect on the dynamic excitations and vibrations. Two groups of TEs with different amplitudes are employed in the case studies. The results verify that the micro-scale TEs influence not only the dynamic displacement excitation, but also the total mesh stiffness and the planetary gear vibrations greatly.

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Shan, Li Jun, Wei Dong He, and Tian Min Guan. "Analysis of Nonlinear Characteristics of Double-Crank Ring-Plate-Typed Pin-Cycloid Gear Planetary Drive." Advanced Materials Research 44-46 (June 2008): 711–16. http://dx.doi.org/10.4028/www.scientific.net/amr.44-46.711.

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Double-crank ring-plate-typed pin-cycloid gear planetary drive conquers shortcomings of a traditional pin-cycloid gear planetary drive, whose load-capacity is restricted by rotation-arm bearing dimension. The load-capacity of this kind of new drive is improved greatly and the efficiency of whole machine is 94%. In order to know dynamics reliability of this drive , nonlinear characteristics of double-crank ring-plate-typed pin-cycloid gear planetary drive are analyzed from two sides of transmission error and dynamic meshing process in this paper. A sensitive analytic mathematic model of rod dimension error is set up by kinematics theory. Based on ring-plate-type cycloid drive dynamic meshing characteristics, a rigidity-flexibility combined model of pin-cycloid planetary drive is set up by ANSYS/LS-DYNA module. Meshing process between pin-cycloid gear is simulated by FEM. Instantaneous stress, distortion and dynamic meshing rigidity are computed. Analytical results show that nonlinear meshing rigidity and transmission errors are two main dynamic exciters which cause prototype to vibrate. So, rod dimension error should be reduced in order to increase meshing accuracy, and meshing rigidity of new prototype should be increased in order to reduce vibration. Nonlinear characteristics of the drive can offer some theoretical bases for design of new prototype.

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Journal articles on the topic 'Dynamic Error'

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