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Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot 基于神经网络的分类器用于 3-DOF 工业机器人的碰撞分类和识别

Automation Pub Date : 2024-03-14 DOI: 10.3390/automation5010002

Khaled H. Mahmoud, G. Abdel-Jaber, Abdel-Nasser Sharkawy

{"title":"Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot","authors":"Khaled H. Mahmoud, G. Abdel-Jaber, Abdel-Nasser Sharkawy","doi":"10.3390/automation5010002","DOIUrl":"https://doi.org/10.3390/automation5010002","url":null,"abstract":"In this paper, the aim is to classify torque signals that are received from a 3-DOF manipulator using a pattern recognition neural network (PR-NN). The output signals of the proposed PR-NN classifier model are classified into four indicators. The first predicts that no collisions occur. The other three indicators predict collisions on the three links of the manipulator. The input data to train the PR-NN model are the values of torque exerted by the joints. The output of the model predicts and identifies the link on which the collision occurs. In our previous work, the position data for a 3-DOF robot were used to estimate the external collision torques exerted by the joints when applying collisions on each link, based on a recurrent neural network (RNN). The estimated external torques were used to design the current PR-NN model. In this work, the PR-NN model, while training, could successfully classify 56,592 samples out of 56,619 samples. Thus, the model achieved overall effectiveness (accuracy) in classifying collisions on the robot of 99.95%, which is almost 100%. The sensitivity of the model in detecting collisions on the links “Link 1, Link 2, and Link 3” was 97.9%, 99.7%, and 99.9%, respectively. The overall effectiveness of the trained model is presented and compared with other previous entries from the literature.","PeriodicalId":514640,"journal":{"name":"Automation","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140244358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Virtual Commissioning of Linked Cells Using Digital Models in an Industrial Metaverse 在工业元网中使用数字模型对关联单元进行虚拟调试

Automation Pub Date : 2024-02-02 DOI: 10.3390/automation5010001

Marco Ullrich, Rashik Thalappully, F. Heieck, Bernd Lüdemann-Ravit

{"title":"Virtual Commissioning of Linked Cells Using Digital Models in an Industrial Metaverse","authors":"Marco Ullrich, Rashik Thalappully, F. Heieck, Bernd Lüdemann-Ravit","doi":"10.3390/automation5010001","DOIUrl":"https://doi.org/10.3390/automation5010001","url":null,"abstract":"Various software environments have been developed in the past to create digital twins of single cells or a digital twin of a factory. Each environment has its own strengths and weaknesses and has been designed with a specific focus. The environments that are able to holistically simulate complete factories are limited in terms of the modelling details required for the analysis of single manufacturing cells (e.g., manufacturer-independence of the individual digital twins) and their ability for virtual commissioning. This paper presents three options for realising a virtual commissioning of linked cells using a 3D integration platform with NVIDIA Omniverse, consisting of two different digital models fused into a combined model, also representing material flow. First, with a source/sink solution and unidirectional connector controlled by OPC UA; secondly, with a bidirectional connector, developed in the course of this elaboration, and an extension of the 3D integration platform controlled by Apache Kafka; thirdly, with a bidirectional connector and using only an extension of the 3D integration platform. The research demonstrates that virtually commissioning multiple linked digital twins from different manufacturers in a 3D platform with material flow makes a significant contribution to the industrial metaverse.","PeriodicalId":514640,"journal":{"name":"Automation","volume":"3 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139683451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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