scholarly journals Kineto-elastic analysis of modular robot systems with component model updating

Author(s):  
Richard P. Mohamed

This dissertation describes the kineto-elastic analysis and component structural dynamic model updating of serial modular reconfigurable robots (MRRs). In general, kineto-elastic analysis is concerned with the structural vibrations, elastic deflections, and torque transmissions of robots which undergo motion from one pose (position and orientation) to another. This work focuses on the kineto-elastic analysis of MRRs undergoing low-speed quasi-static motion. When determining an MRR's payload capacity, or designing MRR modules, the main difficulty is the large number of module configurations and the infinite number of poses within each configuration. Also, the kineto-elastic models of MRRs can become quite large with an increasing number of modules, thereby increasing the numerical complexity. Furthermore, the analytical models of individual MRR components may contain uncertainties, such as unknown stiffness and material parameters, which may lead to large errors for assembled MRR models. To alleviate these issues, a new framework was developed for the kineto-elastic analysis of MRR modules with an emphasis on assessing the worst-case poses. First, a combinatory search method was presented to reduce the computational burdens associated with determining the maximum payload capacity, and performing the module stiffness designs. This involved identifying the worst-case configuration and pose amongst a large number of configurations and infinite number of poses. Afterwards, it was demonstrated that the determination of an MRR's payload capacity, as well as the module stiffness designs, can be performed at the worst-case pose and configuration to satisfy a global set of kineto-elastic performance requirements for all remaining configurations. Next, a new component mode synthesis (CMS) model with fixed-free component boundaries was developed to reduce the sizes of kineto-elastic models, mimic natural link-joint connectivity, and allow experimental tests of joint modules in multiple poses to enable test-analysis model correlation. Finally, a novel method was created to update the uncertain model parameters of joint and link modules using frequency response data from component vibration tests in multiple poses (including the worst cases), with boundary conditions matching those from the CMS models. This procedure can completely avoid testing an entire assembly to perform model updating, and can provide accurate updated model results in any assembly pose.

2021 ◽  
Author(s):  
Richard P. Mohamed

This dissertation describes the kineto-elastic analysis and component structural dynamic model updating of serial modular reconfigurable robots (MRRs). In general, kineto-elastic analysis is concerned with the structural vibrations, elastic deflections, and torque transmissions of robots which undergo motion from one pose (position and orientation) to another. This work focuses on the kineto-elastic analysis of MRRs undergoing low-speed quasi-static motion. When determining an MRR's payload capacity, or designing MRR modules, the main difficulty is the large number of module configurations and the infinite number of poses within each configuration. Also, the kineto-elastic models of MRRs can become quite large with an increasing number of modules, thereby increasing the numerical complexity. Furthermore, the analytical models of individual MRR components may contain uncertainties, such as unknown stiffness and material parameters, which may lead to large errors for assembled MRR models. To alleviate these issues, a new framework was developed for the kineto-elastic analysis of MRR modules with an emphasis on assessing the worst-case poses. First, a combinatory search method was presented to reduce the computational burdens associated with determining the maximum payload capacity, and performing the module stiffness designs. This involved identifying the worst-case configuration and pose amongst a large number of configurations and infinite number of poses. Afterwards, it was demonstrated that the determination of an MRR's payload capacity, as well as the module stiffness designs, can be performed at the worst-case pose and configuration to satisfy a global set of kineto-elastic performance requirements for all remaining configurations. Next, a new component mode synthesis (CMS) model with fixed-free component boundaries was developed to reduce the sizes of kineto-elastic models, mimic natural link-joint connectivity, and allow experimental tests of joint modules in multiple poses to enable test-analysis model correlation. Finally, a novel method was created to update the uncertain model parameters of joint and link modules using frequency response data from component vibration tests in multiple poses (including the worst cases), with boundary conditions matching those from the CMS models. This procedure can completely avoid testing an entire assembly to perform model updating, and can provide accurate updated model results in any assembly pose.


2010 ◽  
Vol 17 (4-5) ◽  
pp. 445-459 ◽  
Author(s):  
Marcin Luczak ◽  
Antonio Vecchio ◽  
Bart Peeters ◽  
Ludo Gielen ◽  
Herman Van der Auweraer

This paper presents a novel approach in the field of experimental and numerical investigation of mechanical properties of composite structures. It takes into account test data variability resulting from structural dynamic properties measurement and uses them to quantify uncertainties in model parameters updating. The main goal of the conducted research is to investigate the dynamic properties of fibre reinforced composite structures. Non-destructive experimental and numerical simulation methods are used hereto. In the experimental part, different test configurations were taken into account. The excitation was performed by means of random and harmonic, single and multi point stimuli while the response measurement was done through contact and non-contact acceleration, velocity and dynamic strain sensing. The test results are applied in two ways: for the structural identification of the object and for non-deterministic updating of the numerical model according to a range of experimental models obtained from test. The sources of the test data variabilities were related to the excitation and measurement technique applied for the investigated object. Non – deterministic model updating and verification & validation included uncertainties of its parameters by means of interval and stochastic methods. A number of variable test modal models were statistically assessed to investigate impact of variability source onto modal model parameters. The presented research was conducted in the context of the FP6 Marie Curie project UNVICO-2.


2011 ◽  
Vol 378-379 ◽  
pp. 98-101
Author(s):  
Yu Xin Zhang ◽  
Zeng Zhong Wang ◽  
Ye Yan Liu

Analytical models of the actual structure often differ greatly from their as-built counterparts. Model updating techniques improve the predictions of the behavior of the actual structure by identifying and correcting the uncertain parameters of the analytical model. This paper presents a new model updating technique to improve the finite element analysis model by updating design parameters using strain measurement based on affine scaling interior Algorithm. Static strain measurements are more reliable and realistic than acceleration data in practice. Numerical examples are presented to study the application of the method.


2020 ◽  
Vol 14 (3) ◽  
pp. 7141-7151 ◽  
Author(s):  
R. Omar ◽  
M. N. Abdul Rani ◽  
M. A. Yunus

Efficient and accurate finite element (FE) modelling of bolted joints is essential for increasing confidence in the investigation of structural vibrations. However, modelling of bolted joints for the investigation is often found to be very challenging. This paper proposes an appropriate FE representation of bolted joints for the prediction of the dynamic behaviour of a bolted joint structure. Two different FE models of the bolted joint structure with two different FE element connectors, which are CBEAM and CBUSH, representing the bolted joints are developed. Modal updating is used to correlate the two FE models with the experimental model. The dynamic behaviour of the two FE models is compared with experimental modal analysis to evaluate and determine the most appropriate FE model of the bolted joint structure. The comparison reveals that the CBUSH element connectors based FE model has a greater capability in representing the bolted joints with 86 percent accuracy and greater efficiency in updating the model parameters. The proposed modelling technique will be useful in the modelling of a complex structure with a large number of bolted joints.


Coatings ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Saisai Wang ◽  
Jian Chen ◽  
Xiaodong Wen

Most of the existing models of structural life prediction in early carbonized environment are based on accelerated erosion after standard 28 days of cement-based materials, while cement-based materials in actual engineering are often exposed to air too early. These result in large predictions of the life expectancy of mineral-admixture cement-based materials under early CO2-erosion and affecting the safe use of structures. To this end, different types of mineral doped cement-based material test pieces are formed, and early CO2-erosion experimental tests are carried out. On the basis of the analysis of the existing model, the influence coefficient of CO2-erosion of the mineral admixture Km is introduced, the relevant function is given, and the life prediction model of the mineral admixture cement-based material under the early CO2-erosion is established and the model parameters are determined by using the particle group algorithm (PSO). It has good engineering applicability and guiding significance.


Author(s):  
Paul J. Pearson ◽  
David M. Bevly

This paper develops two analytical models that describe the yaw dynamics of a farm tractor and can be used to design or improve steering control algorithms for the tractor. These models are verified against empirical data. The particular dynamics described are the motions from steering angle to yaw rate. A John Deere 8420 tractor, outfitted with inertial sensors and controlled through a PC-104 form factor computer, was used for experimental validation. Conditions including different implements at varying depths, as would normally be found on a farm, were tested. This paper presents the development of the analytical models, validates them against empirical data, and gives trends on how the model parameters change for different configurations.


Author(s):  
R. Chander ◽  
M. Meyyappa ◽  
S. Hanagud

Abstract A frequency domain identification technique applicable to damped distributed structural dynamic systems is presented. The technique is developed for beams whose behavior can be modeled using the Euler-Bernoulli beam theory. External damping of the system is included by means of a linear viscous damping model. Parameters to be identified, mass, stiffness and damping distributions are assumed to be continuous functions over the beam. The response at a discrete number of points along the length of the beam for a given forcing function is used as the data for identification. The identification scheme involves approximating the infinite dimensional response and parameter spaces by using quintic B-splines and cubic cardinal splines, respectively. A Galerkin type weighted residual procedure, in conjunction with the least squares technique, is employed to determine the unknown parameters. Numerically simulated response data for an applied impulse load are utilized to validate the developed technique. Estimated values for the mass, stiffness and damping distributions are discussed.


Author(s):  
Francesco Braghin ◽  
Federico Cheli ◽  
Edoardo Sabbioni

Individual tire model parameters are traditionally derived from expensive component indoor laboratory tests as a result of an identification procedure minimizing the error with respect to force and slip measurements. These parameters are then transferred to vehicle models used at a design stage to simulate the vehicle handling behavior. A methodology aimed at identifying the Magic Formula-Tyre (MF-Tyre) model coefficients of each individual tire for pure cornering conditions based only on the measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed and steer angle) during standard handling maneuvers (step-steers) is instead presented in this paper. The resulting tire model thus includes vertical load dependency and implicitly compensates for suspension geometry and compliance (i.e., scaling factors are included into the identified MF coefficients). The global number of tests (indoor and outdoor) needed for characterizing a tire for handling simulation purposes can thus be reduced. The proposed methodology is made in three subsequent steps. During the first phase, the average MF coefficients of the tires of an axle and the relaxation lengths are identified through an extended Kalman filter. Then the vertical loads and the slip angles at each tire are estimated. The results of these two steps are used as inputs to the last phase, where, the MF-Tyre model coefficients for each individual tire are identified through a constrained minimization approach. Results of the identification procedure have been compared with experimental data collected on a sport vehicle equipped with different tires for the front and the rear axles and instrumented with dynamometric hubs for tire contact forces measurement. Thus, a direct matching between the measured and the estimated contact forces could be performed, showing a successful tire model identification. As a further verification of the obtained results, the identified tire model has also been compared with laboratory tests on the same tire. A good agreement has been observed for the rear tire where suspension compliance is negligible, while front tire data are comparable only after including a suspension compliance compensation term into the identification procedure.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Dario Lunni ◽  
Goffredo Giordano ◽  
Francesca Pignatelli ◽  
Carlo Filippeschi ◽  
Stefano Linari ◽  
...  

Abstract A real-time tool to monitor the electrospinning process is fundamental to improve the reproducibility and quality of the resulting nanofibers. Hereby, a novel optical system integrated through coaxial needle is proposed as monitoring tool for electrospinning process. An optical fiber (OF) is inserted in the inner needle, while the external needle is used to feed the polymeric solution (PEO/water) drawn by the process. The light exiting the OF passes through the solution drop at the needle tip and gets coupled to the electrospun fiber (EF) while travelling towards the nanofibers collector. Numerical and analytical models were developed to assess the feasibility and robustness of the light coupling. Experimental tests demonstrated the influence of the process parameters on the EF waveguide properties, in terms of waveguide length (L), and on the nanofibers diameter distribution, in terms of mean $$\widehat{D}$$ D ^ and normalized standard deviation $$\chi$$ χ . Data analysis reveals good correlation between L and $$\widehat{D}, \chi$$ D ^ , χ (respectively maximum correlation coefficients of $${\rho }_{L,\widehat{D}}$$ ρ L , D ^ = 0.88 and $${\rho }_{L,\chi }$$ ρ L , χ = 0.84), demonstrating the potential for effectively using the proposed light-assisted technology as real-time visual feedback on the process. The developed system can provide an interesting option for monitoring industrial electrospinning systems using multi- or moving needles with impact in the scaling-up of innovative nanofibers for soft systems.


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