Optimal Design of the Modular Joint Drive Train for Enhancing Cobot Load Capacity and Dynamic Performance

Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.

Effective way of alleviating poverty against poverty control: Based on the model of "Three Drives, Four Joints" in Zhen'an County

Based on the survey research of poverty controlling model of "Three Drives, Four Joints" in Zhen'an County, its forming motives, implementing mechanism, and constraint factors have been explored to testify its enlightenment and applicability, establishing a promotable, applicable, and effective poverty alleviation model. "Three Drives, Four Joints" model is linked to the poor who lacks ability of self-development. Relying on the drives from key leading companies, the capable and the rich, a community with shared interests by the poor and the subjects of the "three drives" could be formed through "Joint Production, Joint Resources, Joint Community of Stock, and Joint Operation". The linked poverty alleviation development model of "the influential and the rich bring along the poor" and "A rich household would help the others" come into being. It is found out that the model of "Three Drives, Four Joints" is in essence a poverty alleviation method focusing on the increase of the income and diversified ways of increasing the earnings. Problems of poverty alleviation carrier and joint mechanism have been solved in the poverty alleviation process. The model is innovative in activating the resource elements, helping to move the poor out of poverty. A referential, copyable, and applicable model is offered to advance the poverty alleviation in mountainous areas in China.

Research on Angular Output Velocity of a Drive Shaft with Double Cross Universal Joints

The study object is the angular output velocity of the drive shaft which is made up of two series-wound cross universal joints. We have deduced the function relation between the angular output velocity and initiative input angle of the drive shaft with double cross universal joints that is based on the calculation formula of the angular output velocity of a single cross universal joint, and by analyzing the relation between the two input angles. By using this function relation, the constant velocity condition of the drive shaft with double cross universal joints＂ is verified. The step-by-step searching algorithm is adopted to obtain the optimal phase angle that leads to the minimum fluctuate index of the angular output velocity in the vary velocity condition. At the same time, we worked out the maximal and minimum value of the angular output velocity, and their initiative input angle. The correctness of the function of the angular output velocity and the step-by-step search algorithm are verified by an ADAMS simulation example.

Effect of Spine Motion on Mobility in Quadruped Running

Most of current running quadruped robots have similar construction： a stiff body and four compliant legs. Many researches have indicated that the stiff body without spine motion is a main factor in limitation of robots’ mobility. Therefore, investigating spine motion is very important to build robots with better mobility. A planar quadruped robot is designed based on cheetahs’ morphology. There is a spinal driving joint in the body of the robot. When the spinal driving joint acts, the robot has spine motion; otherwise, the robot has not spine motion. Six group prototype experiments with the robot are carried out to study the effect of spine motion on mobility. In each group, there are two comparative experiments： the spinal driving joint acts in one experiment but does not in the other experiment. The results of the prototype experiments indicate that the average speeds of the robot with spine motion are 8.7%–15.9% larger than those of the robot without spine motion. Furthermore, a simplified sagittal plane model of quadruped mammals is introduced. The simplified model also has a spinal driving joint. Using a similar process as the prototype experiments, six group simulation experiments with the simplified model are conducted. The results of the simulation experiments show that the maximum rear leg horizontal thrusts of the simplified mode with spine motion are 68.2%–71.3% larger than those of the simplified mode without spine motion. Hence, it is found that spine motion can increase the average running speed and the intrinsic reason of speed increase is the improvement of the maximum rear leg horizontal thrust.

Knowledge and data jointly driven aeroengine gas path performance assessment method

Aeroengines,as the sole power source for aircraft,play a vital role in ensuring flight safety.The gas path,which represents the fundamental pathway for airflow within an aeroengine,directly impacts the aeroengine's performance,fuel efficiency,and safety.Therefore,timely and accurate evaluation of gas path performance is of paramount importance.This paper proposes a knowledge and data jointly driven aeroengine gas path performance assessment method,combining Fingerprint and gas path parameter deviation values.Firstly,Fingerprint is used to correct gas path parameter deviation values,eliminating parameter shifts caused by non-component performance degradation.Secondly,coarse errors are removed using the Romanovsky criterion for short-term data divided by an equal-length overlapping sliding window.Thirdly,an Ensemble Empirical Mode Decomposition and Non-Local Means(EEMD-NLM)filtering method is designed to“clean”data noise,completing the preprocessing for gas path parameter deviation values.Afterward,based on the characteristics of gas path parameter deviation values,a Dynamic Temporary Blended Network(DTBN)model is built to extract its temporal features,cascaded with Multi-Layer Perceptron(MLP),and combined with Fingerprint to construct a Dynamic Temporary Blended AutoEncoder(DTB-AutoEncoder).Eventually,by training this improved autoencoder,the aeroengine gas path multi-component performance assessment model is formed,which can sufficiently decouple the nonlinear mapping relationship between aeroengine gas path multi-component performance degradation and gas path parameter deviation values,thereby achieving the performance assessment of engine gas path components.Through practical application cases,the effectiveness of this model in assessing the aeroengine gas path multi-component performance is verified.