Legged robots have an advantage when moving on uneven ground and have become a significant focus of extensive studies. The essence of developing a legged robot lies in the selection of effective leg mechanisms. Among the various approaches, leg mechanisms using one-degree-of-freedom link mechanisms stand out for their simpler control. Despite this advantage, the design of link mechanisms presents challenges because of their nonlinear nature. Although various methods have been proposed to surmount this problem, they are unsuitable for link leg mechanism design in terms of their design purpose. In this study, we propose a novel design method using a genetic algorithm to design link leg mechanisms without predefined shapes, topologies and trajectories. Link mechanisms design without predetermined trajectories was implemented by evaluating the movement of mechanisms in a 2D rigid body simulation. In order to accomplish the design of link mechanisms without predetermining the number of links or topology, a decoding technique was devised to create a link mechanism from chromosomes. Our proposed method successfully designed link mechanisms with various shapes, topologies and link numbers. A fabricated link mechanism based on a design demonstrated adequate performance in a real environment. On the other hand, we found a bias in the link number of the design results, which indicates the need for further refinement of our method.

This study delves into the automatic analog circuit design, focusing primarily on topology optimization. Many real-world calculations and evaluations often involve complex and nonlinear problems, posing significant challenges in optimization. Obtaining characteristic values using a simulator can require significant computational resources, adding to the complexity of these issues. In this paper, we employ an innovative optimization method that employs a factorization machine with a digital annealer (FM-DA) and a genetic algorithm (GA). The result is a global optimization method that integrates local optimization structures into its framework. FM-DA&GA represents a black-box optimization technique, where the input variables are expressed as binary variables. The optimization process is then performed using factorization machines that predict characteristic data. This method has been proven to be highly effective for topology optimization in the design of analog circuits. Furthermore, this method can produce a structure with excellent optimization performance at a less computational cost owing to the use of global optimization.

Affective and aesthetic qualities of textures largely depend on their visual and tactile features. However, to date, no systematic methods have been established for the design of such textures. This study confirms the feasibility of the Taguchi method for the multi-objective optimization of texture appearance and tactile pleasantness. To this end, texture stimuli are created using a medium-density fiberboard and laser cutting with several design parameters, including the dimensions and number of engraved figures. Each texture is evaluated based on its appearance and tactile pleasantness. In the multi-objective optimization process using the Taguchi method, a single-objective optimization is performed on iteratively updated sample sets. After several iterations of single-objective process, three non-dominated solutions, namely the Pareto set, are identified with respect to visual and tactile pleasantness. This study demonstrates the effectiveness of the multi-objective Taguchi method to optimize multimodal textured stimulations.

The double enveloping toroidal worm gear pair is a type of basic worm transmission with multi-tooth and double-line contacts. Tooth surfaces of the worm gear are hobbed by a toroidal worm gear hob which is produced based on the toroidal worm. The tooth surface of the hobbed worm gear is macroscopic non-smooth surface and have wave edges, and it is different with the theoretical worm gear tooth surface. In order to obtain the actual forming law of the hobbed worm gear tooth surface with wave edges, this article explores the hobbing principle based on hobbing processes. The actual hobbing mathematical model of the worm gear tooth surface are established, and the wave edges height is defined to evaluate the quality of the worm gear tooth surface. To preliminary obtain the characteristics of the hobbed worm gear tooth surface, the wave edges height distribution of left and right tooth surfaces are analyzed firstly. And then, the hob teeth of the hob are divided into different units to study the influence on the hobbed worm gear tooth surfaces, such as different spirals and different teeth. Further the influence of changing the total number of hob’s chip grooves on the forming characteristics of worm gear tooth surfaces is studied. The results show that the wave edges on the left and right tooth surfaces of the toroidal worm gear are symmetrically distributed. And only some hob teeth have an effect on the final shape of the hobbed worm gear tooth surface, so these cutting teeth are key hob teeth of the toroidal worm gear hob. The total number of hob’s grooves is mostly effect the wave height of the root circle position of the hobbed worm gear. The results provide important references for the design of a toroidal worm gear hob, which are helpful to obtain the high performance double enveloping toroidal worm gearing.

This article proposes a multi-objective optimization method for product service configuration based on customer demand constraint mechanism, targeting the diverse customer needs of product service systems (PSS). This method first forms a utility matrix based on the response of product service instances to customer needs and establishes constraints based on product attributes and enterprise resources. The PSS configuration module is divided into product basic modules and optional modules based on customer demand constraint mechanisms, aiming to express the combination of product and service attributes. Through the utility matrix, multiple optional objectives such as safety, energy efficiency, and economy of PSS configuration are established to fully express the multi-dimensional needs of customer satisfaction. Then a new MOEA/D algorithm was developed for multi-objective optimization of PSS configuration. The improved MOEA/D algorithm adopts a weight vector adjustment strategy based on correlation sparsity, which improves the convergence and diversity of optimization results in high-dimensional objective space and solves the problem of exponential growth in solution space caused by the increase in customer demand types. This method was applied to practical cases of home appliance PSS configuration and compared with the performance of five advanced methods. The experimental results showed that the model established in this paper and the improved algorithm obtained configuration schemes had significant advantages in convergence and diversity.

The aim of this study is to develop a vision-based 3D-dynamic motion errors measurement method. In this report, a measurement method is proposed, and its resolution and measurement error in plane motion measurement are discussed. Moreover, the influence of the defocus condition on the detection resolution is analyzed. The displacement of the marker installed on the spindle of the machine tool is obtained through the video captured by the high-speed camera. In order to obtain the displacement of the marker, the center position of the marker is identified by fitting a mathematical function to obtain the position of the intensity peak of the marker. The measurement resolution and accuracy of the proposed method are investigated experimentally. In addition to the model fitting method, the edge detection and threshold detection methods with different functions for model fitting method are also used for marker position detection for comparison. The deviation of model fitting in the results is less than 42 μm compared with the grid encoder as the reference. The standard deviation of the measured static position is less than 0.1 pixel with a defocus length less than 80 mm.

Under the intensely competitive global economy, the new product development (NPD) has gradually changed from production-oriented to market-oriented. Therefore, it is an important factor to transform specific customers’ needs into shape appeal in products’ sale. The main purpose of this study is to analyze products’ Kansei knowledge by combining rough set theory (RST) and fuzzy association rule mining (FARM), thus providing decision support for NPD. The core Kansei needs that have a great impact on customers’ satisfaction is extracted in RST. FARM can identify the potential relationship between key Kansei attributes and product design attributes. The upright exercise bike is taken as the target case. It is found that the core customer needs of the exercise bike are “vitality”, “speed”, “luxury” and “stable”; while the “modern” which has no impact on emotional properties is deleted. Finally, the mapping relationship between the “vitality” Kansei image and the shape element is given priority. The result shows that the systematic design method combining RST and FARM has good predictive ability and significantly improves the efficiency of research and customers’ satisfaction.

The change in lubrication status often leads to changes in the internal force and vibration status of rolling bearings, which is the reason for the change in the character frequency of rolling bearing defects. This thesis simulated the lubrication state of starved lubrication and adequate lubrication by quantifying the amount of lubricant, and explored the mechanism of characteristic frequency changes under different lubrication states through dynamic modeling techniques. The results showed that as the lubrication state changed from starved lubrication to adequate lubrication, although the friction between rolling body(RB) and the raceways decreased, it could not overcome the influence of increased lubricating oil viscosity resistance. The sliding effect inside the bearing intensified, and the frequency of outer ring(OR) and inner ring(IR) defects decreased, with change rates of 6.3% and 5.3%, respectively; This phenomenon had also been observed in experiments. The research results provide practical reference for bearing fault monitoring technology based on frequency comparison method in practice, which should consider the frequency change rate of defect characteristics caused by lubrication status in different periods for accurate diagnosis.

The electrocautery is an essential device in surgical operations, capable of performing both incisions and hemostasis. Hemostasis can be achieved by charring the blood, but issues such as re-bleeding due to adhesion on the electrode surface and the generation of surgical smoke have been noted. In this study, we aimed to suppress the adhesion of charred blood and the generation of surgical smoke by using silicone-coated electrodes to prevent blood adhesion. To investigate the causes of surgical smoke, we used simulations to clarify the Joule heating and convection of blood associated with discharge using axisymmetric models with flat and spherical cylinder tips. Furthermore, the impact of the presence or absence of silicone coating on the generation of surgical smoke and the movement of heat in the blood during discharge experiments using commercially available electrode shapes was clarified through high-speed infrared camera imaging. As a result, it was confirmed that, compared to commercial electrodes without silicone coating, in the case of side-exposed electrodes, unidirectional heat transfer on the blood surface was observed. Additionally, it was revealed that the amount of surgical smoke decreased when small bubbles were generated in the presence of silicone coating and suppressing spark generation around the electrode. From these results, it was found that side-exposed electrodes, which generate small bubbles and directional convection such as jet-type flow within the blood during discharge, are effective in suppressing surgical smoke.