The top relief surfaces of an hourglass worm gear hob are ground manually in the traditional manufacturing process,which cannot ensure the width of the land surfaces of the hob.Moreover,each geometric feature of the h...The top relief surfaces of an hourglass worm gear hob are ground manually in the traditional manufacturing process,which cannot ensure the width of the land surfaces of the hob.Moreover,each geometric feature of the hob has been produced through different manufacturing techniques and machine tools,which results in low efficiency.To solve this problem,we propose a semi-automatic computer aided design(CAD)method for hobs.The point clouds of each feature surface of a hob are calculated by combing mathematical equations of the top relief surfaces built by the proposed method with other existing equations of hob surfaces.According to the point clouds,the method can achieve the automatic modeling for the hob in three-dimensional(3D)software by classifying and extracting the parameter information of the feature-hierarchical knowledge of the hob.Based on the generated 3D model,the entire surfaces of the hob can be manufactured on a four-axis computer numerical control(CNC)milling machine through only twice clamping.Verification of the width of the land surface of the hob manufactured by semi-automatic CAD method on a measuring projector proved the precision of the designed width can be ensured.The edge of the contact area on the worm wheel in a meshing experiment is clear and distinct,which means the worm gear drive is meshed well and the hob manufactured by the proposed method has improved machinability.The method simplifies the processing technique,and improves the design efficiency and production accuracy.展开更多
In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented da...In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented data supply chains because the high complexity of the data supply chain makes the computation of similarity extremely complex and inefficient. In this paper, we propose a feature space representation model based on key points,which can extract the key features from the subsequences of the original data supply chain and simplify it into a feature vector form. Then, we formulate the similarity computation of the subsequences based on the multiscale features. Further, we propose an improved hierarchical clustering algorithm for a similarity search over the data supply chains. The main idea is to separate the subsequences into disjoint groups such that each group meets one specific clustering criteria; thus, the cluster containing the query object is the similarity search result. The experimental results show that the proposed approach is both effective and efficient for data supply chain retrieval.展开更多
基金supported by The Development of Design and Manufacturing Technology of Double-Enveloping Worm Pair in High-precision with Little Centre Distance(No.69190135)We would like to thank the Professor Workstation of China Agricultural University in Hebei Baoding Laibo Transmission Machinery Manufacturing Co.LTD(No.20200901).
文摘The top relief surfaces of an hourglass worm gear hob are ground manually in the traditional manufacturing process,which cannot ensure the width of the land surfaces of the hob.Moreover,each geometric feature of the hob has been produced through different manufacturing techniques and machine tools,which results in low efficiency.To solve this problem,we propose a semi-automatic computer aided design(CAD)method for hobs.The point clouds of each feature surface of a hob are calculated by combing mathematical equations of the top relief surfaces built by the proposed method with other existing equations of hob surfaces.According to the point clouds,the method can achieve the automatic modeling for the hob in three-dimensional(3D)software by classifying and extracting the parameter information of the feature-hierarchical knowledge of the hob.Based on the generated 3D model,the entire surfaces of the hob can be manufactured on a four-axis computer numerical control(CNC)milling machine through only twice clamping.Verification of the width of the land surface of the hob manufactured by semi-automatic CAD method on a measuring projector proved the precision of the designed width can be ensured.The edge of the contact area on the worm wheel in a meshing experiment is clear and distinct,which means the worm gear drive is meshed well and the hob manufactured by the proposed method has improved machinability.The method simplifies the processing technique,and improves the design efficiency and production accuracy.
基金partly supported by the National Natural Science Foundation of China(Nos.61532012,61370196,and 61672109)
文摘In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented data supply chains because the high complexity of the data supply chain makes the computation of similarity extremely complex and inefficient. In this paper, we propose a feature space representation model based on key points,which can extract the key features from the subsequences of the original data supply chain and simplify it into a feature vector form. Then, we formulate the similarity computation of the subsequences based on the multiscale features. Further, we propose an improved hierarchical clustering algorithm for a similarity search over the data supply chains. The main idea is to separate the subsequences into disjoint groups such that each group meets one specific clustering criteria; thus, the cluster containing the query object is the similarity search result. The experimental results show that the proposed approach is both effective and efficient for data supply chain retrieval.
