Modeling and Parameter Identification of Harmonic Drive Systems

1998 ◽  
Vol 120 (4) ◽  
pp. 439-444 ◽  
Author(s):  
H. D. Taghirad ◽  
P. R. Be´langer
Keyword(s):  
Dynamic Behavior ◽  
Model Performance ◽  
Sensitivity Study ◽  
Model Parameters ◽  
Harmonic Drive ◽  
Nonlinear Regression Models ◽  
Proposed Model ◽  
Stiffness Model ◽  
Drive Systems ◽  
Compact Geometry

The unique performance features of harmonic drives, such as high gear ratios and high torque capacities in a compact geometry, justify their widespread industrial application. However, harmonic drive can exhibit surprisingly more complex dynamic behavior than conventional gear transmission. In this paper a systematic way to capture and rationalize the dynamic behavior of the harmonic drive systems is developed. Simple and accurate models for compliance, hysteresis, and friction are proposed, and the model parameters are estimated using least-squares approximation for linear and nonlinear regression models. A statistical measure of variation is defined, by which the reliability of the estimated parameter for different operating condition, as well as the accuracy and integrity of the proposed model is quantified. By these means, it is shown that a linear stiffness model best captures the behavior of the system when combined with a good model for hysteresis. Moreover, the frictional losses of harmonic drive are modeled at both low and high velocities. The model performance is assessed by comparing simulations with the experimental results on two different harmonic drives. Finally, the significance of individual components of the nonlinear model is assessed by a parameter sensitivity study using simulations.

scholarly journals Distilling Deep Structural Facial Relationships for FAU Intensity Estimation

2021 ◽  
Author(s):  
Yingruo Fan ◽  
Jacqueline CK Lam ◽  
Victor On Kwok Li
Keyword(s):  
Structural Characteristics ◽  
Model Performance ◽  
Training Model ◽  
Model Parameters ◽  
Intensity Estimation ◽  
Structural Relationships ◽  
Proposed Model ◽  
Comparable Performance ◽  
Knowledge Distillation ◽  
The Difference

<div> <div> <div> <p>Facial emotions are expressed through a combination of facial muscle movements, namely, the Facial Action Units (FAUs). FAU intensity estimation aims to estimate the intensity of a set of structurally dependent FAUs. Contrary to the existing works that focus on improving FAU intensity estimation, this study investigates how knowledge distillation (KD) incorporated into a training model can improve FAU intensity estimation efficiency while achieving the same level of performance. Given the intrinsic structural characteristics of FAU, it is desirable to distill deep structural relationships, namely, DSR-FAU, using heatmap regression. Our methodology is as follows: First, a feature map-level distillation loss was applied to ensure that the student network and the teacher network share similar feature distributions. Second, the region-wise and channel-wise relationship distillation loss functions were introduced to penalize the difference in structural relationships. Specifically, the region-wise relationship can be represented by the structural correlations across the facial features, whereas the channel-wise relationship is represented by the implicit FAU co-occurrence dependencies. Third, we compared the model performance of DSR-FAU with the state-of-the-art models, based on two benchmarking datasets. Our proposed model achieves comparable performance with other baseline models, though requiring a lower number of model parameters and lower computation complexities. </p> </div> </div> </div>

scholarly journals An Updated Analytical Structural Pounding Force Model Based on Viscoelasticity of Materials

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Qichao Xue ◽  
Chunwei Zhang ◽  
Jian He ◽  
Guangping Zou ◽  
Jingcai Zhang
Keyword(s):  
Vibration Control ◽  
Viscoelastic Model ◽  
Control Process ◽  
Model Performance ◽  
Analytical Models ◽  
Model Parameters ◽  
Force Model ◽  
Control Analysis ◽  
Proposed Model ◽  
Force Calculation

Based on the summary of existing pounding force analytical models, an updated pounding force analysis method is proposed by introducing viscoelastic constitutive model and contact mechanics method. Traditional Kelvin viscoelastic pounding force model can be expanded to 3-parameter linear viscoelastic model by separating classic pounding model parameters into geometry parameters and viscoelastic material parameters. Two existing pounding examples, the poundings of steel-to-steel and concrete-to-concrete, are recalculated by utilizing the proposed method. Afterwards, the calculation results are compared with other pounding force models. The results show certain accuracy in proposed model. The relative normalized errors of steel-to-steel and concrete-to-concrete experiments are 19.8% and 12.5%, respectively. Furthermore, a steel-to-polymer pounding example is calculated, and the application of the proposed method in vibration control analysis for pounding tuned mass damper (TMD) is simulated consequently. However, due to insufficient experiment details, the proposed model can only give a rough trend for both single pounding process and vibration control process. Regardless of the cheerful prospect, the study in this paper is only the first step of pounding force calculation. It still needs a more careful assessment of the model performance, especially in the presence of inelastic response.

scholarly journals Modelling of simple shear tests on volcanic unsaturated sands

2020 ◽  
Vol 195 ◽  
pp. 02021
Author(s):  
Mariagiovanna Moscariello ◽  
Yanni Chen ◽  
Sabatino Cuomo ◽  
Giuseppe Buscarnera
Keyword(s):  
Simple Shear ◽  
Unsaturated Soils ◽  
Model Performance ◽  
Frictional Resistance ◽  
Flow Rule ◽  
Model Parameters ◽  
Shear Tests ◽  
Soil Response ◽  
Proposed Model ◽  
Unsaturated Sands

In landslide susceptibility analysis, a relevant issue is the proper modelling of the complex mechanisms that regulate the failure and post-failure stages. In this paper, simple shear experiments replicating the kinematics of failure in landslide-prone areas are interpreted through an elastoplastic strain-hardening constitutive model for both saturated and unsaturated soils. The material tested is an air-fall volcanic (pyroclastic) soil from Southern Italy which originated from the explosive activity of the Somma-Vesuvius volcanic apparatus. Data from triaxial and shear tests performed on remoulded specimens characterized by saturated and unsaturated conditions are used to calibrate the model parameters. The evolution of shear stress, volumetric and shear strain measured during the experiments are reproduced by means of a model formulation specific for simple shear conditions. To capture the strength emerging under different states of saturation, non-associated flow rule, and a suction-dependent yield surface are used. Examination of the experimental data available for various testing conditions enabled the quantification of the variability of fundamental model constants, such as those controlling frictional resistance and water retention behaviour. To account for such scatter in the physical properties, the constitutive analyses are performed by employing varying model constants within a band of admissible values. The resulting model performance is validated by comparing the simulations with the experimental results at different saturation conditions. The results show that the combination of the proposed model with a data-driven determination of the range of variation of hydro-mechanical properties is crucial to satisfactorily simulate the essential features of the soil response under a variety of simple shear testing regimes.

scholarly journals Fuzzy Modeling of Urban Water Supply Crisis

2021 ◽  
Author(s):  
Welitom Ttatom Pereira da Silva ◽  
Marco Antonio Almeida de Souza
Keyword(s):  
Water Supply ◽  
Conceptual Model ◽  
Influencing Factors ◽  
Water Consumption ◽  
Model Performance ◽  
Real Data ◽  
Model Parameters ◽  
Urban Water ◽  
Urban Water Supply ◽  
Proposed Model

The chaotic growth of cities results in numerous problems related to public health and urban environment. One of these problems is the urban water supply system crisis. This research aims to develop a mathematical model for urban water supply crises (UWC) able to deal with the ambiguity of the real available data. The applied methodology comprises the following steps: (i) identifying the influencing factors in UWC; (ii) proposing a conceptual model for the description of UWC; (iii) collecting and simulating the necessary and available data; (iv) optimizing the conceptual model parameters; and (v) verifying the proposed model performance. The results indicate that there are many influencing factors in UWC. The model developed comprises two parts or two sub-models. The first sub-model explains water consumption, and the second sub-model explains water availability. In the first sub-model, the functions are related to the factors that influence water consumption. In the second sub-model, the functions are related to the factors that influence the availability of water. This research also aims to analyze the possibility of applying Fuzzy Logic to deal with the ambiguity of real data. It was concluded that, with the proposed model, the UWC was modeled appropriately. The model proposed can help to predict the impact of actions such as reducing losses, reducing pressure on the water supply network and intermittent supply on the intensity of water crisis cases in cities.

scholarly journals An Unstructured Model for Anaerobic Treatment of Raw Cheese Whey for Volatile Fatty Acids Production

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1850
Author(s):  
Claudio B-Arroyo ◽  
Antonio Lara-Musule ◽  
Ervin Alvarez-Sanchez ◽  
Gloria Trejo-Aguilar ◽  
Juan-Rodrigo Bastidas-Oyanedel ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Dynamic Behavior ◽  
Volatile Fatty Acids ◽  
Cheese Whey ◽  
Value Added ◽  
Anaerobic Treatment ◽  
Operating Conditions ◽  
Model Parameters ◽  
Temperature Conditions ◽  
Proposed Model

The whey is a byproduct of the dairy industry that, if not treated properly, can cause serious environmental pollution problems. Anaerobic treatment is an alternative for its recovery, since, in addition to reducing the organic load. it allows the generation of value-added products such as volatile fatty acids (VFA) and biogas. However, the process is very complex and requires specific operating conditions that guarantee its stability and favor the production of value-added compounds. In this work, an unstructured mathematical model is proposed to evaluate the dynamic behavior of the stages of the anaerobic degradation process of the whey (i.e., hydrolysis, acidogenesis, acetogenesis and methanogenesis). The proposed model considers the dynamic variation in pH during the experiment. To validate the model, an experimental set was carried out at pH and temperature conditions that favor the production of VFAs. Experimental results show that the anaerobic treatment of the raw cheese whey favors pH = 5.5; for T = 40 °C, the maximum VFA production is obtained (30.71 gCOD L−1), and for T = 35 °C, a 45.81% COD degradation is reached. The proposed model considers the effect of pH and temperature and it is validated in the region where the experimental tests were carried out. The model parameters were estimated using the Levenberg–Marquardt method, obtaining coefficients of determination R2 > 0.94. The proposed model can describe the dynamic behavior of the key variables in the anaerobic treatment of raw cheese whey at different pH and temperature conditions, finding that VFA production is favored at pH ≥ 7, while the highest COD removal results in acidic conditions

scholarly journals Distilling Deep Structural Facial Relationships for FAU Intensity Estimation

2021 ◽  
Author(s):  
Yingruo Fan ◽  
Jacqueline CK Lam ◽  
Victor On Kwok Li
Keyword(s):  
Structural Characteristics ◽  
Model Performance ◽  
Training Model ◽  
Model Parameters ◽  
Intensity Estimation ◽  
Structural Relationships ◽  
Proposed Model ◽  
Comparable Performance ◽  
Knowledge Distillation ◽  
The Difference

<div> <div> <div> <p>Facial emotions are expressed through a combination of facial muscle movements, namely, the Facial Action Units (FAUs). FAU intensity estimation aims to estimate the intensity of a set of structurally dependent FAUs. Contrary to the existing works that focus on improving FAU intensity estimation, this study investigates how knowledge distillation (KD) incorporated into a training model can improve FAU intensity estimation efficiency while achieving the same level of performance. Given the intrinsic structural characteristics of FAU, it is desirable to distill deep structural relationships, namely, DSR-FAU, using heatmap regression. Our methodology is as follows: First, a feature map-level distillation loss was applied to ensure that the student network and the teacher network share similar feature distributions. Second, the region-wise and channel-wise relationship distillation loss functions were introduced to penalize the difference in structural relationships. Specifically, the region-wise relationship can be represented by the structural correlations across the facial features, whereas the channel-wise relationship is represented by the implicit FAU co-occurrence dependencies. Third, we compared the model performance of DSR-FAU with the state-of-the-art models, based on two benchmarking datasets. Our proposed model achieves comparable performance with other baseline models, though requiring a lower number of model parameters and lower computation complexities. </p> </div> </div> </div>

In-Plane Flexible Ring Tire Model—Part 1: Modeling and Parameter Identification

2018 ◽  
Vol 46 (3) ◽  
pp. 174-219 ◽  
Author(s):  
Bin Li ◽  
Xiaobo Yang ◽  
James Yang ◽  
Yunqing Zhang ◽  
Zeyu Ma
Keyword(s):  
Static Load ◽  
Model Parameters ◽  
Tire Model ◽  
Test Results ◽  
Lumped Mass ◽  
Virtual Test ◽  
Proposed Model ◽  
Particle Swarm Method ◽  
Vehicle Dynamic Simulation ◽  
Flexible Ring

ABSTRACT The tire model is essential for accurate and efficient vehicle dynamic simulation. In this article, an in-plane flexible ring tire model is proposed, in which the tire is composed of a rigid rim, a number of discretized lumped mass belt points, and numerous massless tread blocks attached on the belt. One set of tire model parameters is identified by approaching the predicted results with ADAMS® FTire virtual test results for one particular cleat test through the particle swarm method using MATLAB®. Based on the identified parameters, the tire model is further validated by comparing the predicted results with FTire for the static load-deflection tests and other cleat tests. Finally, several important aspects regarding the proposed model are discussed.

EXPONENTIATED HALF-LOGISTIC LOMAX DISTRIBUTION WITH PROPERTIES AND APPLICATION

2019 ◽  
Vol XVI (2) ◽  
pp. 1-11
Author(s):  
Farrukh Jamal ◽  
Hesham Mohammed Reyad ◽  
Soha Othman Ahmed ◽  
Muhammad Akbar Ali Shah ◽  
Emrah Altun
Keyword(s):  
Real Data ◽  
Continuous Model ◽  
Model Parameters ◽  
Data Set ◽  
Lomax Distribution ◽  
Mathematical Properties ◽  
Proposed Model ◽  
Probability Weighted Moment ◽  
Record Statistics ◽  
Maximum Likelihood Criterion

A new three-parameter continuous model called the exponentiated half-logistic Lomax distribution is introduced in this paper. Basic mathematical properties for the proposed model were investigated which include raw and incomplete moments, skewness, kurtosis, generating functions, Rényi entropy, Lorenz, Bonferroni and Zenga curves, probability weighted moment, stress strength model, order statistics, and record statistics. The model parameters were estimated by using the maximum likelihood criterion and the behaviours of these estimates were examined by conducting a simulation study. The applicability of the new model is illustrated by applying it on a real data set.

scholarly journals Nodule Detection with Convolutional Neural Network Using Apache Spark and GPU Frameworks

2021 ◽  
Vol 11 (6) ◽  
pp. 2838
Author(s):  
Nikitha Johnsirani Venkatesan ◽  
Dong Ryeol Shin ◽  
Choon Sung Nam
Keyword(s):  
Neural Network ◽  
Radiation Dose ◽  
Convolutional Neural Network ◽  
Model Performance ◽  
Performance Comparison ◽  
Apache Spark ◽  
Training Time ◽  
Learning Framework ◽  
Proposed Model

In the pharmaceutical field, early detection of lung nodules is indispensable for increasing patient survival. We can enhance the quality of the medical images by intensifying the radiation dose. High radiation dose provokes cancer, which forces experts to use limited radiation. Using abrupt radiation generates noise in CT scans. We propose an optimal Convolutional Neural Network model in which Gaussian noise is removed for better classification and increased training accuracy. Experimental demonstration on the LUNA16 dataset of size 160 GB shows that our proposed method exhibit superior results. Classification accuracy, specificity, sensitivity, Precision, Recall, F1 measurement, and area under the ROC curve (AUC) of the model performance are taken as evaluation metrics. We conducted a performance comparison of our proposed model on numerous platforms, like Apache Spark, GPU, and CPU, to depreciate the training time without compromising the accuracy percentage. Our results show that Apache Spark, integrated with a deep learning framework, is suitable for parallel training computation with high accuracy.

scholarly journals A General Temperature-Dependent Stress–Strain Constitutive Model for Polymer-Bonded Composite Materials

Polymers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1393
Author(s):  
Xiaochang Duan ◽  
Hongwei Yuan ◽  
Wei Tang ◽  
Jingjing He ◽  
Xuefei Guan
Keyword(s):  
Composite Materials ◽  
Constitutive Model ◽  
Model Parameters ◽  
Temperature Dependent ◽  
Stress Strain ◽  
Proposed Model ◽  
Single Temperature ◽  
Testing Data ◽  
Bonded Composite ◽  
Tension And Compression

This study develops a general temperature-dependent stress–strain constitutive model for polymer-bonded composite materials, allowing for the prediction of deformation behaviors under tension and compression in the testing temperature range. Laboratory testing of the material specimens in uniaxial tension and compression at multiple temperatures ranging from −40 ∘C to 75 ∘C is performed. The testing data reveal that the stress–strain response can be divided into two general regimes, namely, a short elastic part followed by the plastic part; therefore, the Ramberg–Osgood relationship is proposed to build the stress–strain constitutive model at a single temperature. By correlating the model parameters with the corresponding temperature using a response surface, a general temperature-dependent stress–strain constitutive model is established. The effectiveness and accuracy of the proposed model are validated using several independent sets of testing data and third-party data. The performance of the proposed model is compared with an existing reference model. The validation and comparison results show that the proposed model has a lower number of parameters and yields smaller relative errors. The proposed constitutive model is further implemented as a user material routine in a finite element package. A simple structural example using the developed user material is presented and its accuracy is verified.

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