Structural Parameters Of System Research Articles

Control Strategy of PMSG Generator in Small Wind Turbine System

This paper presents a control strategy of turbine directly driven permanent magnet synchronous generator (PMSG) for a small wind generation system. The mathematical models of a wind turbine system, the PMSG generator and converters have been described. The control algorithms of the converter systems based on the methods of vector control have been applied. The study methodology is based on defining various study cases combining structural and operational parameters of the wind energy systems. The models of the PMSG, the force commutated rectifier, the DC bus, the buck converter and the inverter are developed and used in the control scheme. The objective of this paper is to compare between tow controls with simulation, and with more description of all the system by developing the technique needed to control the converter. The simulation results will show that the proposed control can operate with a good performance in a stand-alone wind energy conversion system for low power generation applications.

Quasi-LPV system modeling and identification of a variable speed electro-mechanical and hydraulic MISO system

An accurate digital model is of great significance to system operation inversion and behavior prediction. The multi-energy domain coupling mechanism of the Electro-mechanical and Hydraulic (EMH) system is complex and has strong nonlinear characteristics. At present, the research mainly focuses on the mechanical-hydraulic coupling characteristics, while the research on the large operating range and the influence of electric motor and load characteristics on the nonlinear dynamics of the EMH system are less. Based on the first principle description, the nonlinear characteristics of the system components are described in this paper. Furthermore, the nonlinear dynamic model of the EMH system described in multi-state space is established based on the Quasi-LPV system. Combined with the experimental data, the structural and non-structural uncertain parameters of system are identified. Finally, the influence of the mechanical characteristics of electric motor, load on the nonlinear dynamics of the EMH system are discussed. Experiments show that the Quasi-LPV models proposed in this paper can accurately reproduce and predict system behavior. It provides technical support for rapid design, selection, and scheme optimization of hydraulic systems in general scenarios.

RESEARCH OF THE WORKING PROCESS OF THE CLEANING SYSTEM OF MACHINES FOR HARVESTING ROOT CROPS

Conducted the theoretical and experimental studies of the combined cleaning system functioning process by analyzing the motion of fodder beet through the working surfaces of feeding conveyor and auger installed above it. We have got analytical and empirical process model of fodder beet oblique sub-hiton the augerturn that characterize the dependence of the total rate of sub-hit coefficient of technological interaction of roots and depth of root damage on the main parameters of combined cleaning system. We found out the rational limits of basic structural and kinematic parameters of combined cleaning system by providedminimum offodder beet damage. Particular importance for improving the design and technological level and individual working bodies of the combined cleaning system should be given to issues of general engineering problems of machine design: improvement of working bodies and other structural elements of the combined cleaning system based on a deeper analysis of physical and mechanical properties of roots. Characteristics of fodder beets, as an element of the system "machine-working body-root crop", must be considered as a set of different mechanical qualities and parameters that are decisive in the total mechanical action on the object, their allowable level and range of structural and kinematic parameters of workers bodies. When optimizing the parameters of transport and technological systems of the root of the harvesting machine, which have working bodies of screw mechanisms, at the stage of their design it is advisable to first build a mathematical model of the technological process of root cleaning system parameters.

Uncertain Parameters Estimation using Multi-Dimensional Analysis and Stochastic Model Updating

Stochastic model updating based on perturbation theory has been widely applied to quantify uncertain parameters in structural systems due to its simplicity and straightforward approach. Nevertheless, the significant requirements for establishing a good correlation in the initial prediction of structural responses and small perturbations in uncertain parameters have become influential in stochastic model updating. The initial assumptions of structural parameters are often unavailable to quantify the input properties due to insufficient information about the structural system. These problems contribute to large errors in initial prediction, causing ill-posedness in sensitivity matrices and convergence difficulties caused by the local minima function in the stochastic model updating approach. In these circumstances, this study attempts to propose a novel scheme to overcome the ill-posed and converging problems in the stochastic model updating by quantifying structural parameters of the assembled structure encompassing high uncertainties such as the stiffness term of the contact joint interface by using a combination of the lattice-based exploration approach and the perturbation-based stochastic model updating method. The lattice-based exploration approach is adopted for generating samples of predicted responses from the assumed initial distribution of random parameters in the interest of improving the initial correlation of the predicted responses for producing well-condition sensitivity. Responses from each sample are evaluated in light of their experimental counterparts to estimate the optimum initial distribution of the random parameters. Then, the initial statistical properties of the parameters can be estimated by rerunning the sampling approach using the optimum distribution. As a result, stochastic model updating using the perturbation approach can be applied efficiently with the new initial distribution. The proposed scheme has been demonstrated on an assembled bolted joint structure, focusing on the contact interfaces. It is found that the proposed scheme managed to produce satisfactory predictions on the distribution of natural frequencies with only 12.5 % of total errors are recorded in comparison with the experimental data.

40× zoom optical system design based on stable imaging principle of four groups.

Based on stable imaging principle of four groups and combined with optical design software, a method for initial structure calculation of zoom optical system and optical system optimization design is proposed to solve the problems of difficult initial structure calculation, large volume, and inflection point of zoom curves of a high zoom ratio optical system. First, this paper theoretically derives the four-group stable imaging principle of the zoom optical system. Then, using the derived equations and optical design software, the initial structural parameters of the four-group zoom optical system are solved to ensure that there is no inflection point in the zoom curves. Finally, a lightweight and small 40× continuous zoom optical system is designed to verify the feasibility and effectiveness of the design method proposed in this paper. The zoom optical system has the advantages of good imaging quality, lightweight, small size, smooth zoom, and no inflection point.

Correction to: Decision-making for structural parameters of injection mold gating system based on agent model and intelligent algorithm

Correction to: Decision-making for structural parameters of injection mold gating system based on agent model and intelligent algorithm

Decision-making for structural parameters of injection mold gating system based on agent model and intelligent algorithm

Decision-making for structural parameters of injection mold gating system based on agent model and intelligent algorithm

Constrained unscented Kalman filter for parameter identification of structural systems

The unscented Kalman filter (UKF) can be used to identify model parameters of structural systems from the measurement data. However, the standard UKF may provide unreliable and nonphysical estimates, since no parameter constraints are incorporated in the identification process. This paper discusses and compares several constrained UKF (CUKF) methods for parameter identification of structural systems. The effectiveness and robustness of the methods are evaluated through numerical simulation on a Bouc–Wen hysteretic system. The results demonstrate that with properly handling of the constraints, the identification accuracy can be improved. The proposed CUKF method is further validated using experimental data collected from a full-scale reinforced concrete structure. Based on the identified model parameters, the updated models can achieve more accurate simulation responses than the initial model.

A long short-term memory based deep learning algorithm for seismic response uncertainty quantification

The application of metamodeling technique to overcome computational challenge of Monte Carlo simulation (MCS) technique for response uncertainty quantification under stochastic earthquake load is a difficult task due to the high-dimensional nature of stochastic load. Recent developments in the sequential models for forecasting and prediction have opened a new avenue in this regard. Various deep learning algorithms, particularly the convolutional neural network and recurrent neural network are quite suitable for response uncertainty quantification of nonlinear stochastic dynamic system. However, most of the existing studies consider stochastic load as the only source of uncertainty assuming the parameters characterizing a structure as deterministic. The present study proposes a long short-term memory (LSTM) based deep learning algorithm for seismic response uncertainty quantification by duly addressing both the stochastic nature of dynamic load and structural system parameter uncertainty. The functional application program interface feature of Keras that allows layers sharing to form more complex model is explored to form a response approximation model. It incorporates more than one input source i.e., stochastic dynamic excitation sequence as well as structural system parameter uncertainty. The proposed algorithm is elucidated through two numerical examples i.e., a proof-of-concept example and one realistic structural engineering problem by considering the direct MCS based results as the benchmark. The results of accuracy matrices, regression analysis results, comparison of seismic response statistics and reliability results with the results of direct MCS technique clearly revealed the enhanced prediction capability of the proposed LSTM model.

Bayesian parameter updating in linear structural dynamics with frequency transformed data using rational surrogate models

The identification of parameters of structural models through measurements of the system’s response is of interest in many contexts. In Bayesian system identification the underlying inverse problem is formulated in a probabilistic setting, and Bayes’ rule is applied to update a prior conjecture on the parameters. We apply the Bayesian framework to identify the parameters of structural systems using dynamic measurement data. The likelihood function is formulated in terms of the misfit of the frequency transformed data and the model frequency response function. We introduce a novel formulation that accounts for the correlation of the model error in both spatial and frequency domain. The proposed formulation is able to handle dense data sets in the frequency domain without need to manually select data points. Due to the high computational demands of sampling-based approaches for solving the Bayesian updating problem with expensive structural dynamics models, we resort to surrogate models. We apply a recently introduced rational surrogate model that approximates the complex frequency response as a rational of two polynomials with complex coefficients. Samples of the posterior distribution of the model parameters are then obtained through an adaptive sequential sampling approach using the surrogate instead of the original dynamic model. The proposed method is successfully applied to identify the orthotropic stiffness and damping parameters of a finite element model of a cross laminated timber plate.

Quadratic Stabilization of Linear Uncertain Positive Discrete-Time Systems

The paper provides extended methods for control linear positive discrete-time systems that are subject to parameter uncertainties, reflecting structural system parameter constraints and positive system properties when solving the problem of system quadratic stability. By using an extension of the Lyapunov approach, system quadratic stability is presented to become apparent in pre-existing positivity constraints in the design of feedback control. The approach prefers constraints representation in the form of linear matrix inequalities, reflects the diagonal stabilization principle in order to apply to positive systems the idea of matrix parameter positivity, applies observer-based linear state control to assert closed-loop system quadratic stability and projects design conditions, allowing minimization of an undesirable impact on matching parameter uncertainties. The method is utilised in numerical examples to illustrate the technique when applying the above strategy.

Modified Strong Tracking System Identification Method Based on Square Root Center Difference Kalman Filter for Civil Structures

Civil engineering structures will exhibit hysteretic behavior due to damage caused by dynamic loads. Identifying the hysteretic behavior of structures is a practical and challenging problem that involves observing vibration data to determine strength and stiffness degradation. This paper proposes a modified square root central difference Kalman filter (MSRCD-KF) method to track this behavior. By combining the QR decomposition and strong tracking filtering technology, the proposed method makes the recursive calculation process unconditionally stable, while enabling the tracking of abrupt changes in structural parameters. A three degree-of-freedom (3-DOF) Duffing system is used in the simulation to verify the effectiveness of the proposed method. Numerical results show that the proposed method can converge to the true value quickly and accurately. Then, the proposed method is used to identify the structural parameters of a two-story concrete frame structure under different seismic loading sequences. In the first example, the structure is simplified as a 2-DOF linear system for which the equivalent stiffness and damping under different damage levels are identified. This information is then used to obtain the stiffness variation trend, damping ratio, and frequency. The second example uses the Bouc–Wen model to consider the stiffness and strength degradation of the structure. Finally, the experimental results demonstrate that the proposed method can accurately identify the structural parameters of nonlinear systems, and the identified hysteresis curves are in good agreement with the experimental ones.

Multi-Objective Optimization of Structural Parameters of Air-Cooled System for Lithium Battery Pack Based on Surrogate Model

Abstract The new energy electric vehicle, which takes clean electric energy as the main driving force, has no pollutants and exhaust emissions during its operation and has a higher energy utilization ratio than the fuel locomotive. Therefore, electric vehicles have been widely developed in recent years. The maximum temperature and temperature consistency of the battery pack in the electric vehicle have a great influence on the life and safety of the battery. In this paper, the thermal management system of the lithium battery pack was taken as the research object. The temperature distribution and uniformity of the battery pack under different heat dissipation conditions were analyzed based on computational fluid dynamics (CFD). The multi-objective optimization method of the battery pack thermal management system was carried out by combining the surrogate model with fast non-dominated sorting genetic algorithm (NSGA-II). The maximum temperature of the battery pack obtained from candidate point 1 is 310.72 K, which is 4.99 K lower than the initial model temperature, and the temperature standard deviation is 0.76 K, with a reduction rate of 51.9%. Experiment results showed that maximum difference between the optimized and experimental value of the maximum temperature is 0.8 K, and the error was within 1 K. Therefore, the multi-objective optimization method proposed in this paper has high accuracy.

Output-Only Modal Estimation Using Eigensystem Realization Algorithm with Nonstationary Data Correlation

The conventional eigensystem realization algorithm with data correlation (ERA/DC) combines the impulse response or free response data of a structural system with the concept of correlation function to identify the modal parameter of the structural system. Previous studies have shown that the modal parameters of structural systems subjected to stationary white noise excitation can be estimated by ERA/DC from the ambient response without excitation data. This concept is extended in this paper for output-only modal identification for the structural system with complex modes under ambient excitation as a nonstationary process in the form of a product model. Numerical simulations and experimental verification are used to validate the effectiveness of the proposed method for response-only modal estimation, and the stabilization diagram is used with modal assurance criterion (MAC) to distinguish structural modes from fictitious modes.

Dynamic modelling and stability analysis of the articulated tracked vehicle considering transient track-terrain interaction

Articulated tracked vehicles (ATVs) exhibit enhanced steerability but reduced yaw stability. Apart from the track-terrain contact, the dynamics of the articulated frame steering (AFS) system strongly influences the stability of ATVs. We developed a detailed hydraulic steering system and a yaw-plane ATVs model for vehicle stability research. The transient characteristic of track-ground contact was considered. The multibody dynamics model by Recurdyn/Track software was compared with the established model to verify the model correctness at time-domain and frequency-domain. The result suggests that the vehicle yaw stability can be evaluated in terms of the oscillation frequency, damping ratio, overshoot, and steady-state deviation of articulation angle response. A multi-objective optimization is proposed to obtain the optimized structural parameters of AFS system by employing response surface method (RSM) and non-dominated sorting genetic algorithm II (NSGA-II). The optimal solutions revealed that more compact mechanism design of AFS system contributes to a compromise stability performance with 4.44 % decrease in the oscillation frequency and 10.3 % decrease in the damping ratio.

An efficient procedure to predict the dynamic loads for piston liner systems in marine engines

The piston ring-cylinder liner (PRCL) is one of the most important parts of marine diesel engines and contributes 25% to 50% of total friction loss. The lubrication simulation analysis of the PRCL system is a challenging task. Complete understanding and precise prediction of lubrication loads is a key to understanding the friction behavior of PRCL systems as the accuracy of the friction prediction depends upon precise prediction of lubrication loads. Therefore, this paper focuses on the gas pressure calculation which is the primary source of lubrication loads. The procedure presented combines the advantages of two mainstream methods to predict loads in the PRCL system. The result is a significant reduction in the computation time without compromising on accuracy. Firstly, a comparison of both approaches is presented which suggests that each technique has its limitations (one is time-bound, and one is accuracy-bound). Then, the results from both calculation methods are verified against literature and a parametric study is performed to identify the key structural parameters of PRCL system that affect the calculation efficiency. Finally, a correlation coefficient is introduced into the analysis to combine the two approaches which then identifies the conditions under which the use of the faster method becomes invalid and replaces it with the more accurate approach. This ensures optimum performance of the calculation procedure by switching between the fast and the accurate method depending upon the accuracy requirement under given conditions, thereby, simplifying the dynamic and lubrication model of PRCL systems. The study has direct implications for the tribological design of the PRCL interface.

The Influence of the Negative Properties of Heaving Soil on the Stability of Frame-Rod Structural Systems

This article discusses the influence of the negative properties of heaving soil on the stability of frame-rod structural systems during the operation of buildings and structures. It is known that the loads and influences arising during the operation of buildings and structures can lead to loss of stability of both an individual element and the entire structural system as a whole. It is extremely difficult to accident-free work operation of buildings and structures, the foundation layer of which are heaving soils. Therefore, it is necessary to develop a methodology for determining the critical stability parameters of frame-rod structural systems that takes into account the heaving properties of base soils. In the process of loss of stability, elements of frame-rod structural systems under the influence of force factors due to the influence of constrained conditions can experience both passive and active bifurcation. With the manifestation of the negative properties of heaving soils, vertical deformations of the base occur, which can lead to a change in the type of bifurcation of both an individual element and the entire structural system as a whole. Based on the assumption that the element will pass from passive bifurcation to active at the moment when the work performed by internal forces is compensated by the work of the heaving forces, an expression is obtained to determine the critical deformation of the base soil. A statically indefinable single-span frame is considered, the right strut of which is loaded with force P and the left one with force αP. Using the displacement method, the critical stability parameters of the specified rod system were determined before and after the manifestation of the negative properties of the base soil. Based on the numerical analysis, it was concluded that the right pillar of the frame loses stability actively, involving the left one in the general bifurcation. After manifestation of the negative properties of the base soil, the type of bifurcation of the frame elements changes, leading to significant changes in the stability parameters. In this case, the critical deformation of the heaving linearly increases with an increase in the geometric dimensions of the frame and decreases with an increase in the load application coefficient α at 0,6<α<0,8 and 1,0<α<1,1. In the range 0,8>α> 1,0, these parameters are directly proportional.

Multiple-image encryption based on light-field imaging and gravity model

A new multiple-image encryption method based on a light-field imaging system and the gravity model is presented in this paper. An inverse process of light-field imaging was used for multiple-image encryption. The method first combined multiple images into one light-field image. It was then encrypted using the gravity model, which further improved the security. The structural parameters of the light-field imaging system and the different objective distances of each original image could be used as part of the secret keys. A refocusing reconstruction algorithm for the light-field image was used in the decryption process. Experiments and analyses have shown that the proposed scheme could easily be accessed and provides a large key space and high sensitivity in the key space. Furthermore, it is robust against occlusion attacks. Compared with the repeated use of gravity model alone, the proposed method offers enhanced statistical properties and efficiency benefits. The proposed encryption can be achieved by a computational way, which can eliminate the negative effects of hardware limitations and aberrations.

Seismic modal identification using a new approach based on weighted transmissibility

AbstractIn recent years, the transmissibility‐based operational modal analysis has attracted the attention of many researchers due to its effective applications in output‐only modal identification. However, the present research indicates that the application of this approach is not so appropriate for the ambient vibration records with short length and high spectral leakage, such as seismic records. The existence of nonperiodic frequency components in the records leads to an increase in the spectral leakage and dispersion. In this paper, an effective approach called weighted transmissibility‐based operational modal analysis is proposed to properly identify the structural modal parameters using the seismic records. The proposed method identifies the natural frequencies and mode shapes based on weighed transmissibility, so that it combines the single‐reference weighted transmissibility functions associated with different transferring outputs obtained from single or multiple loading conditions in a unique matrix formulation. Then, it extracts the vibration modes using the efficient spectra obtained from the singular value decomposition of weighted transmissibility matrices. In this paper, a theoretical example (5DOF system) is provided to indicate the capabilities of the proposed approach for identifying the modal parameters of structural systems.

Cantilever-based micro thrust measurement and pressure field distribution of biomimetic robot fish actuated by macro fiber composites (MFCs) actuators

Underwater autonomous vehicles (UAVs) actuated by smart actuators have attracted increasing attention. A miniature macro fiber composite (MFC)-actuated robot fish inspired by koi fish is developed. A cantilever mechanism is designed to transfer the dynamic micro thrust of the robot fish. Three design indexes, namely the bending stiffness, the ratio of the bending stiffness to the torsional stiffness, and the natural frequency of the cantilever transducer are proposed. Thus, a simple and effective method to determine the structural parameters of the cantilever-based micro thrust force measurement system is presented. Calibration results demonstrated that the parameters of the proposed cantilever transducer match well with the designed indexes. Dynamic variation mechanisms of the micro thrust force associated with the swimming behaviors of the robot fish are well captured using the proposed measurement system. Experimental results show that the MFC-actuated robot fish obtains the biggest mean thrust of 1.73 mN in the case of the largest oscillating velocity. The maximum instant thrust grows with the increment of the oscillating frequency, and achieves its maximum of 7.35 mN in the case of 10 Hz. While the maximum instant drag first decreases then increases as the actuation frequency increases, and obtains its minimum of −2.62 mN in the case of the maximum oscillating velocity. On the contrary, variations of the thrust pattern/oscillating period are reversed to those of the maximum instant drag. Computational fluid dynamics results demonstrate that variations of the instant thrust are fully determined by the distribution and intensity of the concentrated pressure regions induced by the oscillating caudal fin. The cycle-averaged velocity fields are closely related to the mean thrust generated by the MFC-actuated robot fish. As a result, the fluid–structure interaction mechanisms associated with the thrust variations of the MFC-actuated robot fish are revealed. This study may be useful for the design and realization of UAVs actuated by smart actuators.