2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)最新文献

Spatial Positioning and Regional Intrusion Monitoring Method Based on 3D Real Scene Model of Converter Station 基于换流站三维实景模型的空间定位与区域入侵监控方法

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796491

Weiming Li, Yaohui Xiao, S. He, An Chang, Zhenzhen Zhou, Hua-shan Huang, G. Zhao

{"title":"Spatial Positioning and Regional Intrusion Monitoring Method Based on 3D Real Scene Model of Converter Station","authors":"Weiming Li, Yaohui Xiao, S. He, An Chang, Zhenzhen Zhou, Hua-shan Huang, G. Zhao","doi":"10.1109/IDITR54676.2022.9796491","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796491","url":null,"abstract":"At present, the converter station mainly monitors regional intrusion through manual inspection, which has low monitoring efficiency and is prone to mistakes, which can not ensure the security of key areas of the converter station. In view of the above problems, a spatial positioning and regional intrusion monitoring method based on the three-dimensional real scene model of the converter station is proposed. The three-dimensional real scene model of converter station is constructed by ANSYS modeling method; Based on the three-dimensional real scene model, locate the three-dimensional warning space; Target tracking algorithm is used to monitor intrusion characters. The experimental results show that for five intrusion events, the average deviation of monitoring is always less than 1.675m, the deviation of positioning warning space is small, and has better spatial positioning effect; The highest missed detection rate and the highest false detection rate are not more than 1%, and the monitoring accuracy is high; The overall average monitoring time is 0.53s, which improves the monitoring efficiency and ensures the safety of key areas of the converter station.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128815384","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

Research on transaction mode and interactive control strategy for aggregated thermostatically controlled load based on block chain technology 基于区块链技术的聚合恒温控制负载事务模式及交互控制策略研究

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796502

M. Chai, Ciwei Gao, Chaoliang Wang, L. Li, Wei Liu, Jingju Wang

引用次数: 1

Processing and Recognition of Characters Image in Complex Environment 复杂环境下字符图像的处理与识别

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796487

Ji Yuan, MinYang Guo, Binyan Huang, Ruiqi Hu, S. Dian

{"title":"Processing and Recognition of Characters Image in Complex Environment","authors":"Ji Yuan, MinYang Guo, Binyan Huang, Ruiqi Hu, S. Dian","doi":"10.1109/IDITR54676.2022.9796487","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796487","url":null,"abstract":"Aiming at the recognition in complex backgrounds using the Optical Character Recognition (OCR) technology, a model with high detection and recognition accuracy for small texts and codes in the images is proposed in this paper. Before recognition, the Retinex image enhancement and median filtering are performed to weaken the influence of ambient lighting and to enhance the image features. The Otsu threshold segmentation is adopted to segment the small text images from the background. Finally, the Differentiable Binarization (DB) algorithm is applied to detect the characters and the Convolutional Recurrent Neural Network (CRNN) algorithm is employed to recognize the detected characters. The experimental results show that in the life scenes, the workpiece components scenes, and the Chinese characters scenes, the recognition accuracies of the proposed model are 95.6%, 98.4%, and 90.9%, respectively; and the recognition times are 0.78s, 0.59s, and 0.63s, respectively. Overall, the average recognition accuracy of the model proposed in this paper reaches up to 94.9%, and the average recognition time is only 0.67s, which verifies the effectiveness and the advancement of the model.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127779554","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

Pipeline damage identification based on weak fiber Bragg grating sensor array 基于弱光纤光栅传感器阵列的管道损伤识别

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796504

Hongreng Li, Feiyang Pu, Qiankui Feng, X. Tong

引用次数: 0

Sub-pixel Underwater Object Size Measurement Algorithm Based on Improved Otsu Binarization and Edge Curvature Filtering 基于改进Otsu二值化和边缘曲率滤波的亚像素水下目标尺寸测量算法

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796503

Chen Chen, Hangbin Cao, Jun Liu, Shaolin Hu, J. Ru, Hongli Xu

{"title":"Sub-pixel Underwater Object Size Measurement Algorithm Based on Improved Otsu Binarization and Edge Curvature Filtering","authors":"Chen Chen, Hangbin Cao, Jun Liu, Shaolin Hu, J. Ru, Hongli Xu","doi":"10.1109/IDITR54676.2022.9796503","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796503","url":null,"abstract":"In the field of target recognition, shape size is an important attribute of object. There have been many research bases on vision-based size measurement in air, but few studies have been done on underwater target size measurement. This paper mainly proposes solutions to the problems of external lighting conditions, the reflective properties of object materials, and the disturbance of robot motion. Firstly, based on the improvement of Otsu, an Otsu method suitable for bimodal or multimodal object images is proposed. Secondly, a linear interpolation denoising method based on edge contour curvature fluctuation is proposed, which combines polynomial interpolation sub-pixel technology to achieve contour edge smoothing. Finally, using polynomial interpolation sub-pixel technology, taking the image threshold segmentation effect and the measurement accuracy of the object size as the measurement standard, the underwater ball and pipeline are tested, and the measurement accuracy is improved by more than 2%, which verifies the robustness of the method.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131316100","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

Gas Sensor with Fractal Geometry Optimized Electrode Structure 分形电极结构气体传感器

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9795934

Taicong Yang, Fengchun Tian, Anyan Jiang, Maogang Jiang

引用次数: 0

Off road path planning based on hybrid artificial potential field and ant colony algorithm 基于人工势场和蚁群算法的越野路径规划

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796489

Yan Xiaodong, Chang Tianqing, Chu Kaixuan, Zhao Liyang, Zhang Jie

引用次数: 1

Prescribed Performance Formation Control Method of Multiple Autonomous Underwater Vehicles Based on Leader-follower 基于Leader-follower的多自主水下航行器预定性能编队控制方法

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796477

W. Yuliang, L. Yiping

引用次数: 0

Collaborative Multi-Chain Architecture for Data Transmission across Homogeneous Blockchain 跨同构区块链数据传输的协同多链架构

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796483

Yousif Abuidris, Chang-Da Wang, Wanan Yang

引用次数: 1

Design of the control and risk automatic warning platform for power grid operation based on AI+video technology 基于AI+视频技术的电网运行控制与风险自动预警平台设计

2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR) Pub Date : 2022-05-01 DOI: 10.1109/IDITR54676.2022.9796476

S. He, Weiming Li, Gang Zhao, Yunhai Song, Yaohui Xiao, Zhenzhen Zhou, An Chang

{"title":"Design of the control and risk automatic warning platform for power grid operation based on AI+video technology","authors":"S. He, Weiming Li, Gang Zhao, Yunhai Song, Yaohui Xiao, Zhenzhen Zhou, An Chang","doi":"10.1109/IDITR54676.2022.9796476","DOIUrl":"https://doi.org/10.1109/IDITR54676.2022.9796476","url":null,"abstract":"In order to accurately identify the risk behavior in the power grid operation, ensure the life safety of operators and the development of power enterprises, the power grid operation behavior control and automatic risk early warning platform based on AI+video technology is designed. The platform is composed of infrastructure layer, data resource layer, application support layer, platform management, and AI+video monitoring layer. The infrastructure layer is mainly responsible for collecting video of grid operation behavior, and considering the actual situation of grid operation, and accurately extracting the prospect target in the video image (i. e. monitoring target) under the jitter condition of the video camera. The data resource layer and the application support layer are responsible for selecting different power grid operation risk behavior judgment algorithms under different application scenarios; the platform management and AI+video monitoring layer are responsible for showing the monitoring and early warning results of the operation behavior of the power grid to users. The experimental results show that, under the condition of monitoring camera jitter, the prospect of grid behavior control and automatic risk warning platform based on AI+video technology is closest to the benchmark map, and the risk behavior identification results are consistent with the relevant standards of power grid operation in China. The area under the ROC curve has remained above 0.6, which can effectively identify the risk behavior in power grid operation, reduce the risk behavior of network operation and improve the safety of grid operation.","PeriodicalId":111403,"journal":{"name":"2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122746547","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