2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)最新文献_第9页

A Digital Twin Model for Dynamic Optimization of Metal Cutting Process Parameters 金属切削工艺参数动态优化的数字孪生模型

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734359

Zhiyong Luo, Honglei Deng, Qing Xia, Jiping Yang, Chuan Yang, Chun-Xu Jiang, Xiaorong Gong

{"title":"A Digital Twin Model for Dynamic Optimization of Metal Cutting Process Parameters","authors":"Zhiyong Luo, Honglei Deng, Qing Xia, Jiping Yang, Chuan Yang, Chun-Xu Jiang, Xiaorong Gong","doi":"10.1109/ITOEC53115.2022.9734359","DOIUrl":"https://doi.org/10.1109/ITOEC53115.2022.9734359","url":null,"abstract":"Metal cutting process optimization problem has been extensively studied in the past few decades, researchers either conduct experimental design, develop heuristic algorithms or design expert system to optimize process parameters. The main idea of the past research is to optimize a set of process parameters before executing the entire process steps, which fails to effectively respond to the needs of dynamic manufacture environment. However, very little research has focused on the dynamic optimization of process parameters during the process. Digital twin is commonly known as the enabling technology to solve the dynamic problem in the industrial sector. This paper proposes a novel digital twin framework for metal cutting process dynamic optimization during the metal cutting process. Five characteristics of digital twin model of the proposed framework are analyzed. In this framework, a metal cutting process digital twin model is proposed to dynamically infer the optimal process parameters while interacting with its physical counterpart during the process. An information model for the metal cutting process digital twin is put forward to formalize the representation of the comprehensive information between the digital twin and its physical counterpart. The effectiveness and feasibility of the proposed digital twin model are tested in a case study on a milling process.","PeriodicalId":127300,"journal":{"name":"2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114679017","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

Predication of remaining useful life of aircraft engines based on Multi-head Attention and LSTM 基于多头关注和LSTM的飞机发动机剩余使用寿命预测

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734660

Shuangshuang Zhao, Yucai Pang, Jipeng Chen, Jian Liu

{"title":"Predication of remaining useful life of aircraft engines based on Multi-head Attention and LSTM","authors":"Shuangshuang Zhao, Yucai Pang, Jipeng Chen, Jian Liu","doi":"10.1109/ITOEC53115.2022.9734660","DOIUrl":"https://doi.org/10.1109/ITOEC53115.2022.9734660","url":null,"abstract":"According to the large amount of high-dimensional time series data generated by sensors, and the insufficient utilization of time series information in the network model in the prediction on remaining useful life (RUL) of aircraft engines, a data-driven model for RUL prediction based on a Multi-head Attention mechanism and a long short-term memory neural network (LSTM) is proposed in this paper to optimize RUL of aircraft engine. The model can select the key features in the time-series data, then input them into the LSTM layer to mine the internal connections, and finally obtain RUL predicted results through two fully connected layers. Using the CMAPSS dataset provided by NASA for verification and comparing with other algorithms, the accuracy of this method outperforms shallow neural networks based on support vector regression (SVM) and deep learning methods such as convolutional neural networks (CNN), multi-layered LSTM and multi-layered BiLSTM, which provides a powerful support for health management of aircraft engines, operation and maintenance decisions.","PeriodicalId":127300,"journal":{"name":"2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117115820","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: 2

Research on Asynchronous Motor Vector Control System with Fuzzy Slide Mode Speed Regulator 模糊滑模调速异步电机矢量控制系统的研究

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734460

Chengyang Li, Siyi Xu, Wei Zhang

引用次数: 1

Realization of Electric Power Communication Network 电力通信网的实现

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734354

Peipei Yan, Zhiwei Xiang

引用次数: 1

Multi-camera System Depth Estimation 多相机系统深度估计

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734714

Feng Yang, Zhao Liming, Zhang Yi, Kuang Hengyang

引用次数: 0

Design and implementation of subway automatic ticketing system based on Verilog HDL 基于Verilog HDL的地铁自动售票系统的设计与实现

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734441

Liu ZiKuan, Li Chao, Yang Guo Yuan

引用次数: 0

Research on Multi-mode Control System and Autonomous Cruise Method for Unmanned Surface Vehicles 无人水面车辆多模式控制系统及自主巡航方法研究

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734390

Shi Xiao, Daoyang Yu, Minqiang Li, Linhua Sheng, Wei Lu, Liyan Zhu, Sunyun Li, Shengming Qin

引用次数: 2

Military medical remote emergency system framework based on ESIA theory 基于ESIA理论的军事医疗远程应急系统框架

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734644

Xiaohua Hu, Hongwei Cao, Yongzhong Zhang, Yonghui Dai

引用次数: 0

A Class of Adaptive Control for Stochastic Nonlinear Systems Based on Backstepping Technology 一类基于反演技术的随机非线性系统自适应控制

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734470

Yingying Ge

引用次数: 0

Minimum variance and range-based k-means optimization algorithm-Rdk-means algorithm 最小方差和基于距离的k-means优化算法- rdk -means算法

2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC) Pub Date : 2022-03-04 DOI: 10.1109/ITOEC53115.2022.9734450

Hao Wang, Mengyao Wu, Xiaoxia Lin, Jiashuai Zong

引用次数: 0