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In order to improve the design efficiency of different types of rollers globoidal cam deceleration mechanism and standardize the design system, a parametric design method based on NX secondary development is proposed, and the design system is developed. According to the theory of space geometry and the principle of conjugate surface, the working profile equations of five typical types of rollers, including cylindrical roller, conical roller, ball-cone roller, drum roller and ball roller, and globoidal cam are deduced. The key design parameters are extracted, and the human-machine interaction design menus and dialogs are developed by using the NX secondary development tool. Combined with NX Open C/C++ API and Visual Studio compilation environment, the parametric design system of different types of rollers globoidal cam deceleration mechanism is developed. And according to the assembly constraint relationship between the components in the mechanism, the automatic assembly function is developed. The application shows that the whole system developed can meet the user's personalized design requirements, help to realize the normalization and standardization of the design process of different types of rollers globoidal cam deceleration mechanism, achieve the rapid design and modification, and shorten the design cycle.

In order to design the globoidal cam deceleration mechanism with good performance and improve the transmission performance, the working surface equation and conjugate contact equation are deduced based on the space conjugate contact principle. The constant parameters of globoid cam are preprocessed by using Creo software, and the parametric design of globoid cam deceleration mechanism is completed. According to the finite element method, the first six modes of the reducer mechanism are analyzed. The orthogonal experiment method is used to design the experimental scheme. The influence of pressure angle, rotary pitch radius, roller radius and roller width on the sensitivity of the constraint mode of the reducer mechanism is quantitatively analyzed by statistical theory and variance analysis. The results show that the variances of pitch radius and roller radius of turntable are 0.021 and 0.043 respectively, both of which are less than 0.05 and sensitive to the constraint mode of globoidal cam, followed by the pressure angle and the roller width. The results provide a basis for the study of vibration and noise of globoidal cam mechanism design.

Characterising the energy efficiency grades of machining systems (MS) is an effective analytical methodology or management tool that helps to establish the high energy-efficient MS. However, the current MS energy efficiency approaches still lack scientific and practical formulation strategies to addresses this issue due to its multi-source and variable energy consumption characteristics. Focusing on this challenge, a new concept of inherent energy efficiency (IEE), which is formed in the design and formation phases of the MS, is proposed. Meanwhile, a novel energy efficiency grade evaluation (EEGE) approach based on IEE is also presented. The proposed EEGE approach not only can evaluate the MS energy efficiency grades, but also can reveal the MS high energy-efficient intervals. According to the analysis of IEE in MS, the EEGE approach is developed in three steps: (i) the establishment of IEE evaluating indicator system from both inherent energy utilisation (IEU) and inherent specific energy (ISE), (ii) the acquisition of the IEE, and (iii) the development of a quantitative method for the EEGE in MS. Finally, a case study of energy efficiency grade evaluation and analysis for an XK714D CNC milling machining centre is examined, illustrating the practicability of the proposed method. [ABSTRACT FROM AUTHOR]

Grinding is widely used in mechanical manufacturing to obtain both precision and part requirements. In order to achieve carbon efficiency improvement and save costs, carbon emission and processing cost models of the grinding process are established in this study. In the modeling process, a speed-change-based adjustment function was introduced to dynamically derive the change of the target model. The carbon emission model was derived from the grinding force using regression. Considering the constraints of machine tool equipment performance and processing quality requirements, the grinding wheel's linear velocity, cutting feed rate, and the rotation speed of the workpiece were selected as the optimization variables, and the improved NSGA-II algorithm was applied to solve the optimization model. Finally, fuzzy matter element analysis was used to evaluate the most optimal processing plan. [ABSTRACT FROM AUTHOR]

Objective . The early diagnosis of lung cancer depends on the precise segmentation of lung nodules. However, the variable size, uneven intensity, and blurred borders of lung nodules bring many challenges to the precise segmentation of lung nodules. Approach. We propose a shape attention-guided contextual residual network to address the difficult problem in lung nodule segmentation. Firstly, we establish a selective kernel convolution residual module to replace the original encoder and decoder. This module incorporates selective kernel convolution, which automatically selects convolutions with different receptive fields to acquire multi-scale spatial features. Secondly, we construct a multi-scale contextual attention module to assist the network in extracting multi-scale contextual features of local feature maps. Finally, we develop a shape attention-guided module to assist the network to restore details such as the boundary and shape of lung nodules during the upsampling phase. Main results. The proposed network is comprehensively analyzed using the publicly available LUNA16 data set, and an ablation experiment is designed to validate the effectiveness of each individual component. Ultimately, the dice similarity coefficient of the experimental results reaches 87.39% on the test set. Compared to other state-of-the-art segmentation methods, the proposed network achieves superior performance in lung nodule segmentation. Significance. Our proposed network improves the accuracy of lung nodule segmentation, which provides an important support for physicians to subsequently develop treatment plans., (© 2023 Institute of Physics and Engineering in Medicine.)