Search results

This paper aims to design an active shock absorber scheme for use in conjunction with a passive shock absorber to suppress the horizontal vibration of elevator cars in a smaller range and shorter time. The developed active shock absorber will also improve the safety and comfort of passengers driving in ultra-high-speed elevators.

A six-degree of freedom dynamic model is established according to the position and condition of the car. Then the active shock absorber and disturbance compensation-based adaptive control scheme are designed and simulated in MATLAB/Simulink. The results are analysed and compared with the traditional shock absorber.

The results show that, compared with traditional spring-based passive damping systems, the designed active shock absorber can reduce vibration displacement by 60%, peak acceleration by 50% and oscillation time by 2/3 and is more robust to different spring stiffness, damping coefficient and load.

The developed active shock absorber and its control algorithm can significantly reduce vibration amplitude and converged time. It can also adjust the damping strength according to the actual load of the elevator car, which is more suitable for high-speed elevators.

The purpose of the paper is to propose an efficient and accurate force/torque (F/T) sensing method for the robotic wrist-mounted six-dimensional F/T sensor based on an excitation trajectory.

This paper presents an efficient and accurate F/T sensing method based on an excitation trajectory. First, the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity. Therefore, the sensing accuracy is improved. Then, the excitation trajectory with optimized poses is used for robot following and data acquisition. The data acquisition is not limited by poses and its time can be significantly shortened. Finally, the least squares method is used to identify parameters and sense contact forces/torques.

Experiments have been carried out on the self-developed robot manipulator. The results strongly demonstrate that the proposed approach is more efficient and accurate than the existing widely-adopted method. Furthermore, the data acquisition time can be shortened from more than 60 s to 3 s/20 s. Thus, the proposed approach is effective and suitable for fast-paced industrial applications.

The main contributions of this paper are as follows: the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity; and the excitation trajectory with optimized poses is used for robot following and data acquisition.

To prevent the coil from burning or getting damaged, it is necessary to estimate the duration of its operation as long as its temperature does not exceed the permissible limit. This paper aims to investigate the effect of switching on the thermal behavior of impregnated and nonimpregnated windings. Also, the safe operating time for each winding is determined.

The power loss of the winding is expressed as a function of the winding specifications. Using homogenization techniques, the equivalent thermal properties for the homogenized winding are calculated and used in a proposed thermal equivalent circuit for winding modeling and analysis. The validity and accuracy of the proposed model are determined by comparing its analysis results and simulation and measurement results.

The results show that copper windings have better thermal behavior and lower temperature compared to aluminum windings. On the other hand, by impregnating or increasing the packing factor of the winding, the thermal behavior is improved. Also, by choosing the right duty cycle for the winding current source, it is possible to prevent the burning or damage of the winding and increase its lifespan. Comparing the measurement results with the analysis results shows that the proposed equivalent circuit has an error of less than 4% in the calculation of the winding center temperature.

In this paper, the effect of temperature on the electrical resistance of the coil is ignored. Also, rectangular wires were not investigated. Research in these topics are considered as future work.

By calculating the thermal time constant of the winding, its safe operation time can be calculated so that its temperature does not exceed the tolerable value (150 °C). The proposed method analyzes both impregnated and nonimpregnated windings with various schemes. It investigates the effects of switching on their thermal behavior. Additionally, it determines the safe operating time for each type of winding.

The purpose of this paper is the dynamic analysis and seismic damage assessment of steel sheet pile quay wall with inelastic behavior underground motions using several accelerograms.

Finite element analysis is conducted using the Plaxis 2D software to generate the numerical model of quay wall. The extension of berth 25 at the port of Bejaia, located in northeastern Algeria, represents a case study. Incremental dynamic analyses are carried out to examine variation of the main response parameters under seismic excitations with increasing Peak ground acceleration (PGA) levels. Two global damage indices based on the safety factor and bending moment are introduced to assess the relationship between PGA and the damage levels.

The results obtained indicate that the sheet pile quay wall can safely withstand seismic loads up to PGAs of 0.35 g and that above 0.45 g, care should be taken with the risk of reaching the ultimate moment capacity of the steel sheet pile. However, for PGAs greater than 0.5 g, it was clearly demonstrated that the excessive deformations with material are likely to occur in the soil layers and in the structural elements.

The main contribution of the present work is a new double seismic damage index for a steel sheet pile supported quay wharf. The numerical modeling is first validated in the static case. Then, the results obtained by performing several incremental dynamic analyses are exploited to evaluate the degradation of the soil safety factor and the seismic capacity of the pile sheet wall. Computed values of the proposed damage indices of the considered quay wharf are a practical helping tool for decision-making regarding the seismic safety of the structure.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

The aim of this paper is to provide a simple yet accurate and efficient geometric method for thermal homogenization of impregnated and non-impregnated coil winding technologies based on the concept of thermal resistance.

For regular windings, the periodic microscopic cell in the winding space is identified. Also, for irregular windings, the average microscopic cell of the winding is determined. An approximation is used to calculate the thermal resistance of the winding cell. Based on this approximation, the winding insulation is considered as a circular ring around the wire. Mathematical equations are obtained to calculate the equivalent thermal resistance of the cell. The equivalent thermal conductivity of the winding is calculated using equivalent thermal resistance of the cell. Winding thermal homogenization is completed by determining the equivalent thermal properties of the cell.

The thermal pattern of different windings is simulated and compared with the results of different homogenization methods. The results show that the proposed method is applicable for a wide range of windings in terms of winding scheme, packing factor and winding insulation. Also, the results show that the proposed method is more accurate than other winding homogenization methods in calculating the equivalent thermal conductivity of the winding.

In this paper, the change of electrical resistance of the winding with temperature and thermal contact between the sub-components are ignored. Also, liquid insulators, such as oils, and rectangular wires were not investigated. Research in these topics is considered as future work.

Unlike other homogenization methods, the proposed method can be applied to non-impregnated and irregular windings. Also, compared to other homogenization methods, the proposed method has a simpler formulation that makes it easier to program and implement. All of these indicate the efficiency of the proposed method in the thermal analysis of the winding.

The electromechanical planetary transmission system has the advantages of high transmission power and fast running speed, which is one of the important development directions in the future. However, during the operation of the electromechanical planetary transmission system, friction and other factors will lead to an increase in gear temperature and thermal deformation, which will affect the transmission performance of the system, and it is of great significance to study the influence of the temperature effect on the nonlinear dynamics of the electromechanical planetary system.

The effects of temperature change, motor speed, time-varying meshing stiffness, meshing damping ratio and error amplitude on the nonlinear dynamic characteristics of electromechanical planetary systems are studied by using bifurcation diagrams, time-domain diagrams, phase diagrams, Poincaré cross-sectional diagrams, spectra, etc.

The results show that when the temperature rise is less than 70 °C, the system will exhibit chaotic motion. When the motor speed is greater than 900r/min, the system enters a chaotic state. The changes in time-varying meshing stiffness, meshing damping ratio, and error amplitude will also make the system exhibit abundant bifurcation characteristics.

Based on the principle of thermal deformation, taking into account the temperature effect and nonlinear parameters, including time-varying meshing stiffness and tooth side clearance as well as comprehensive errors, a dynamic model of the electromechanical planetary gear system was established.

Because of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this paper is to propose a deep learning torque prediction method based on long short-term memory (LSTM) recurrent neural networks optimized by particle swarm optimization (PSO), which can accurately predict the the joint torque.

The proposed model optimized the LSTM with PSO algorithm to accurately predict the IRs joint torque. The authors design an excitation trajectory for ABB 1600–10/145 experimental robot and collect its relative dynamic data. The LSTM model was trained with the experimental data, and PSO was used to find optimal number of LSTM nodes and learning rate, then a torque prediction model is established based on PSO-LSTM deep learning method. The novel model is used to predict the robot’s six joint torque and the root mean error squares of the predicted data together with least squares (LS) method were comparably studied.

The predicted joint torque value by PSO-LSTM deep learning approach is highly overlapped with those from real experiment robot, and the error is quite small. The average square error between the predicted joint torque data and experiment data is 2.31 N.m smaller than that with the LS method. The accuracy of the novel PSO-LSTM learning method for joint torque prediction of IR is proved.

PSO and LSTM model are deeply integrated for the first time to predict the joint torque of IR and the prediction accuracy is verified.

The purpose of this paper is to realize the lightweight of connecting rod and meet the requirements of low energy consumption and vibration. Based on the structural design of the original connecting rod, the finite element analysis was conducted to reduce the weight and increase the natural frequencies, so as to reduce materials consumption and improve the energy efficiency of internal combustion engine.

The finite element analysis, structural optimization design and topology optimization of the connecting rod are applied. Efficient hybrid method is deployed: static and modal analysis; and structure re-design of the connecting rod based on topology optimization.

After the optimization of the connecting rod, the weight is reduced from 1.7907 to 1.4875 kg, with a reduction of 16.93%. The maximum equivalent stress of the optimized connecting rod is 183.97 MPa and that of the original structure is 217.18 MPa, with the reduction of 15.62%. The first, second and third natural frequencies of the optimized connecting rod are increased by 8.89%, 8.85% and 11.09%, respectively. Through the finite element analysis and based on the lightweight, the maximum equivalent stress is reduced and the low-order natural frequency is increased.

This paper presents an optimization method on the connecting rod structure. Based on the statics and modal analysis of the connecting rod and combined with the topology optimization, the size of the connecting rod is improved, and the static and dynamic characteristics of the optimized connecting rod are improved.