汽车制动皮碗割模的改进

分析汽车制动皮碗的特点 ,指出传统皮碗割模存在产品切割尺寸不稳定 ,废品率高的缺点。介绍一种效率较高的皮碗割模 ,其特点是 ,在硫化工序中产品内孔不需将胶边撕掉 ,只需将皮碗外缘胶边撕掉就可以切割。同时在切割皮碗时不需在下割模中放入橡胶缓冲垫来帮助切割产品内缘 ,操作方便 ,模具加工、设计也方便。产品合格率也相应提高。

悬臂式掘进机器人截割臂建模与二阶滑模控制器设计

根据悬臂式掘进机器人截割工艺和结构特点，建立了截割臂动力学模型．将一种基于有限状态结构的二阶滑模控制扩展到多输入多输出系统中，在无速度观测器的情况下，保证了滑模量及其导数在有限时间收敛到零．算法消弱了传统滑模控制中的抖动问题，提高了控制系统精度．利用提出的多输入多输出二阶滑模控制算法，设计了截割臂控制器．通过仿真和实验，证明了算法的有效性．

简易调节割圆模

在没有专用设备的前提下,要在钢板上下圆盘形坯料,或在钢板上割出圆腔,如果只靠划线手动气割,往往保证不了精度,而且效率很低。为此,我们设计制作了简易调节割圆模(结构见附图),解决了上述问题。

Research on the LA-UMamba Model for Asymmetric Modules with Added Auxiliary Information

Deep learning techniques are revolutionizing the developmentof medical image segmentation.With the advancement of Transformer models,especially ViT and Swin-Transformer,which enhances the remote-dependent modeling capability of the model through the self-attention mechanism,better segmentation performance can be achieve.Moreover,the high computational cost of Transformer has motivated researchers to explore more efficient models,such as the Mamba model based on state-space modeling(SSM),and for the field of medical segmentation,reducing the number of model parameters is also necessary.In this study,a novel asymmetric model called LA-UMamba was proposed,which integrates visual Mamba module to efficiently capture complex visual features and remote dependencies.The classical design of U-Net was adopted in the upsampling phase to help reduce the number of references and recover more details.To mitigate the information loss problem,an auxiliary U-Net downsampling layer was designed to focus on sizing without extracting features,thus enhancing the protection of input information while maintaining the efficiency of the model.The experiments were conducted on the ACDC MRI cardiac segmentation dataset,and the results showed that the proposed LA-UMamba achieves proved performance compared to the baseline model in several evaluation metrics,such as IoU,Accuracy,Precision,HD and ASD,which improved that the model is successful in optimizing the detail processing and reducing the complexity of the model,providing a new perspective for further optimization of medical image segmentation techniques.

A new fuzzy edge detection algorithm

Based upon the maximum entropy theorem of information theory, a novel fuzzy approach for edge detection is presented. Firstly, a definition of fuzzy partition entropy is proposed after introducing the concepts of fuzzy probability and fuzzy partition. The relation of the probability partition and the fuzzy c-partition of the image gradient are used in the algorithm. Secondly, based on the conditional probabilities and the fuzzy partition, the optimal thresholding is searched adaptively through the maximum fuzzy entropy principle, and then the edge image is obtained. Lastly, an edge-enhancing procedure is executed on the edge image. The experimental results show that the proposed approach performs well.

1-3型压电复合材料的制备及性能分析

简要介绍了压电复合材料的复合理论及有限元方法(FEM),并结合具体材料的参数,得到了1-3型压电复合材料各性能参数随PZT相体积比变化的曲线;同时,通过有限元软件对1-3型压电复合材料进行了仿真;最后,利用割模-浇铸法制作了1-3型压电复合材料,并对其性能进行了测试及分析。

A SIMULATED ANNEALING METHOD FOR FAULT TREE ANALYSIS

This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.

EFFECTIVE IMAGE SEGMENTATION FRAMEWORK FOR GAUSSIAN MIXTURE MODEL INCORPORATING LOCAL INFORMATION

A new two-step framework is proposed for image segmentation. In the first step, the gray-value distribution of the given image is reshaped to have larger inter-class variance and less intra-class variance. In the sec- ond step, the discriminant-based methods or clustering-based methods are performed on the reformed distribution. It is focused on the typical clustering methods-Gaussian mixture model （GMM） and its variant to demonstrate the feasibility of the framework. Due to the independence of the first step in its second step, it can be integrated into the pixel-based and the histogram-based methods to improve their segmentation quality. The experiments on artificial and real images show that the framework can achieve effective and robust segmentation results.

FOUR-AXIS WIRE-EDM SIMULATION OF COMPLICATED MODELS

In the verification of wire electrical discharge machining （EDM）, the motion and the performance of the wire-EDM system are analyzed. The maximum inclining angle of the wire is calculated. The relevant judgment methods are used for the collision between the wire, the fixture, and the machining table. In the wire-EDM simulation, the generated solid model can he used to investigate programming results and to check the machining accuracy. The generation algorithm for the solid model in the simulation is solved based on Boolean operations. The wire swept volume for each cutting step is united to form the entire wire swept volume. Through Boolean subtraction between the stock model and the entire wire swept volume, the solid model in the wire-EDM simulation is generated. The method is also suitable for the wire path intersection occurred in cutting cone-shaped models. Finally, experiments are given to prove the method.

拟阵M+M^e中集的结构与关系

研究拟阵M+Me中集的结构与关系。应用单扩张与模割的一一对应,讨论了X∈L(M+Me)的各种情况。讨论了在单平行扩张下拟阵M+Me,模割M,主模割MF的等价关系。给出了拟阵主扩张M+Fe中基与极小圈的表示。

拟阵族N的分裂子M(K_5)

研究拟阵族N的分裂子M(K5)。先应用分裂子定理和拟阵的单扩张定理证明:若N={M:M是二元域拟阵且M不含有同构于F*7的拟阵},则F7是N的一个分裂子。据此证明了两个结论:1.若N={M:M是正则拟阵且M不含M(K3,3)-幼阵},则M(K5)是N的一个分裂子;2.M(K5)是EX(U2,4,F7,M(K3,3))和EX(U2,4,F7*,M(K3,3))的分裂子,并得到了这两个拟阵族的正则拟阵分解表示。

拟阵的单扩张与分裂子的确定

研究用拟阵的单扩张M′=M+Ee来确定拟阵族N的分裂子的方法。首先证明了M′=M+Eer(M′)=r(M),并且对每个M中包含e的极小圈C,都有|C|=r(M)+1。讨论了拟阵AG(3,2)和拟阵P6的性质。给出了拟阵M具有性质(P)的充要条件。由以上结果用两种方法证明了:若M=AG(3,2),E=E(M),令N={M:M不含有幼阵同构于w3或P6},则M+Ee是N的一个分裂子。

Fame:A Fast Detailed Placement Algorithm for Standard\| Cell Layout Based on Mixed Mincut and Enumeration

Rapid progress in manufacturing greatly challenges to the VLSI physical design in both speed and performance. A fast detailed placement algorithm, FAME is presented in this paper, according to these demands. It inherits the optimal positions of cells given by a global placer and exact position to each cell by local optimization. FM Mincut heuristic and local enumeration are used to optimize the total wirelength in y and x directions respectively, and a two way mixed optimizing flow is adopted to combine the two methods for a better performance. Furthermore, a better enumeration strategy is introduced to speed up the algorithm. An extension dealing with blockages in placement has also been discussed. Experimental results show that FAME runs 4 times faster than RITUAL and achieves a 5% short in total wirelength on average.

EFFECTIVE FEATURE ANALYSIS FOR COLOR IMAGE SEGMENTATION

An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. The determination of effective color features depends on the analysis of various color features from each tested color image via the designed feature encoding. It is different from the pervious methods where self organized feature map (SOFM) is used for constructing the feature encoding so that the feature encoding can self organize the effective features for different color images. Fuzzy clustering is applied for the final segmentation when the well suited color features and the initial parameter are available. The proposed method has been applied in segmenting different types of color images and the experimental results show that it outperforms the classical clustering method. The study shows that the feature encoding approach offers great promise in automating and optimizing the segmentation of color images.

Evolution of deformation property and strength component mobilization for thermally treated Beishan granite under compression

The cohesion weakening and friction strengthening(CWFS)model for rock reveals the strength components mobilization process during progressive brittle failure process of rock,which is very helpful in understanding mechanical properties of rock.However,the used incremental cyclic loading−unloading compression test for the determination of strength components is very complicated,which limits the application of CWFS model.In this paper,incremental cyclic loading−unloading compression test was firstly carried out to study the evolution of deformation and the strength properties of Beishan granite after various temperatures treated under different confining pressures.We found the axial and lateral unloading modulus are closely related to the applied stress and damage state of rock.Based on these findings,we can accurately determine the plastic strain during the entire failure process using conventional tri-axial compression test data.Furthermore,a strength component(cohesive and frictional strength)determination method was developed using conventional triaxial compression test.Using this method,we analyzed the variation of strength mobilization and deformation properties of Beishan granite after various temperatures treated.At last,a non-simultaneous strength mobilization model for thermally treated granite was obtained and verified by numerical simulation,which demonstrated the effectiveness of the proposed strength determination method.

Selectivity of escape-hole size in tube traps for white-spotted conger Conger myriaster

Comparative fishing experiments were carried out in 2010 using tube traps with five hole diameters (8, 15, 18, 20 and 22 mm) to establish the size selectivity of escape holes for white-spotted conger. Selectivity and split parameters of the SELECT model were calculated using the estimated-split and equal-spilt model. From likelihood ratio tests and AIC (Akaike's Information Criterion) values, the estimated-split model was selected as the best-fit model. Size selectivity of escape holes in the tube traps was expressed as a logistic curve, similar to mesh selectivity. The 50% selection length of white-spotted conger in the estimated-split model was 28.26, 33.35, 39.31 and 47.30 cm for escape-hole diameters of 15, 18, 20 and 22 mm, respectively. The optimum escape-hole size is discussed with respect to management of the white-spotted conger fishery. The results indicate that tube traps with escape holes of 18 mm in diameter would benefit this fishery.

New two-dimensional fuzzy C-means clustering algorithm for image segmentation

To solve the problem of poor anti-noise performance of the traditional fuzzy C-means (FCM) algorithm in image segmentation, a novel two-dimensional FCM clustering algorithm for image segmentation was proposed. In this method, the image segmentation was converted into an optimization problem. The fitness function containing neighbor information was set up based on the gray information and the neighbor relations between the pixels described by the improved two-dimensional histogram. By making use of the global searching ability of the predator-prey particle swarm optimization, the optimal cluster center could be obtained by iterative optimization, and the image segmentation could be accomplished. The simulation results show that the segmentation accuracy ratio of the proposed method is above 99%. The proposed algorithm has strong anti-noise capability, high clustering accuracy and good segment effect, indicating that it is an effective algorithm for image segmentation.

New Cutting Force Modeling Approach for Flat End Mill

A new mechanistic cutting force model for flat end milling using the instantaneous cutting force coefficients is proposed. An in-depth analysis shows that the total cutting forces can be separated into two terms: a nominal component independent of the runout and a perturbation component induced by the runout. The instantaneous value of the nominal component is used to calibrate the cutting force coefficients. With the help of the perturbation component and the cutting force coefficients obtained above, the cutter runout is identified. Based on simulation and experimental results, the validity of the identification approach is demonstrated. The advantage of the proposed method lies in that the calibration performed with data of one cutting test under a specific regime can be applied for a great range of cutting conditions.

Brain MRI Segmentation Using KFCM and Chan-Vese Model

To extract region of interests （ROI） in brain magnetic resonance imaging （MRI） with more than two objects and improve the segmentation accuracy, a hybrid model of a kemel-based fuzzy c-means （KFCM） clustering algorithm and Chan-Vese （CV） model for brain MRI segmentation is proposed. The approach consists of two succes- sive stages. Firstly, the KFCM is used to make a coarse segmentation, which achieves the automatic selection of initial contour. Then an improved CV model is utilized to subdivide the image. Fuzzy membership degree from KFCM clus- tering is incorporated into the fidelity term of the 2-phase piecewise constant CV model to obtain accurate multi-object segmentation. Experimental results show that the proposed model has advantages both in accuracy and in robustness to noise in comparison with fuzzy c-means （FCM） clustering, KFCM, and the hybrid model of FCM and CV on brain MRI segmentation.

3D modeling of geological anomalies based on segmentation of multiattribute fusion

3D modeling of geological bodies based on 3D seismic data is used to define the shape and volume of the bodies, which then can be directly applied to reservoir prediction, reserve estimation, and exploration. However, multiattributes are not effectively used in 3D modeling. To solve this problem, we propose a novel method for building of 3D model of geological anomalies based on the segmentation of multiattribute fusion. First, we divide the seismic attributes into edge- and region-based seismic attributes. Then, the segmentation model incorporating the edge- and region-based models is constructed within the levelset- based framework. Finally, the marching cubes algorithm is adopted to extract the zero level set based on the segmentation results and build the 3D model of the geological anomaly. Combining the edge-and region-based attributes to build the segmentation model, we satisfy the independence requirement and avoid the problem of insufficient data of single seismic attribute in capturing the boundaries of geological anomalies. We apply the proposed method to seismic data from the Sichuan Basin in southwestern China and obtain 3D models of caves and channels. Compared with 3D models obtained based on single seismic attributes, the results are better agreement with reality.