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2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)最新文献

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Surface Defect Detection Method of High Speed Railway Bridge Cables based on Optical Fiber Sensing Technology 基于光纤传感技术的高速铁路桥梁电缆表面缺陷检测方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332902
Xinghang Long, Xulan Gui, Weiwei Zhan
{"title":"Surface Defect Detection Method of High Speed Railway Bridge Cables based on Optical Fiber Sensing Technology","authors":"Xinghang Long, Xulan Gui, Weiwei Zhan","doi":"10.1109/IAAI51705.2020.9332902","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332902","url":null,"abstract":"Due to environmental loads, fatigue effects, corrosion and material aging and other factors, the surface of high-speed railway bridge cables will inevitably be damaged, which affects the safety of the bridge. Therefore, a method for detecting surface defects of high-speed railway bridge cables based on optical fiber sensing technology is proposed. Secondly, based on the theory of high-speed fiber-optic sensor, the defect of the bridge is detected and detected by the method of neural network. The results show that: under the application of the proposed method, the defect judgment is accurate, and the type identification is also accurate, which provides a reference for bridge safety and health monitoring.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125635967","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
Design Optimization of Ultra-Thin Asphalt Pavement on Cement Concrete Bridge Deck based on Artificial Intelligence 基于人工智能的水泥混凝土桥面超薄沥青路面设计优化
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332883
Wang Qiu-yun
{"title":"Design Optimization of Ultra-Thin Asphalt Pavement on Cement Concrete Bridge Deck based on Artificial Intelligence","authors":"Wang Qiu-yun","doi":"10.1109/IAAI51705.2020.9332883","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332883","url":null,"abstract":"In the design of cement concrete bridge deck ultra-thin layer asphalt pavement, due to the insufficient design of construction method and asphalt preparation ratio, the adhesion and firmness of the bridge deck ultra-thin layer are poor. Therefore, the optimization method of asphalt pavement design based on artificial intelligence is designed. Through the setting of coarse and fine aggregate technology and asphalt index, the preparation process of ultra-thin asphalt on cement concrete bridge deck is completed. Artificial intelligence technology is used to construct a visual finite element model of the ultra-thin asphalt pavement on the bridge deck, and the paving unit is set according to this model. Use asphalt macadam seal bridge deck construction technology to complete the paving process. At this point, the design optimization method of ultra-thin asphalt pavement on cement concrete bridge deck based on artificial intelligence is completed. Constructing the experimental link, through comparison, it can be seen that the adhesion and firmness of the ultra-thin bridge deck designed by this method are better than the other two methods. It can be seen that this method is more effective.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131931113","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
Numerical Simulation of Mechanical Properties of Asphalt Mixture Bridge Deck Pavement Based on Virtual Reality 基于虚拟现实的沥青混合料桥面铺装层力学特性数值模拟
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332845
Wang Qiu-yun
{"title":"Numerical Simulation of Mechanical Properties of Asphalt Mixture Bridge Deck Pavement Based on Virtual Reality","authors":"Wang Qiu-yun","doi":"10.1109/IAAI51705.2020.9332845","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332845","url":null,"abstract":"Numerical simulation of the actual bridge deck overlay of asphalt mixture performance, interface unit is thin, leading to the final simulated pavement displacement value is too large, do not meet the actual mechanics for this problem is proposed based on virtual reality overlay of asphalt mixture performance numerical simulation deck. The bridge deck pavement is described by the method based on continuum mechanics, the mechanical values are generated, the ductile damage rule is used to judge the output mechanical values, the mechanical performance model is constructed, and the virtual reality technology is used to realize the numerical simulation and complete the research and analysis. The asphalt mixture with certain parameters is selected to make the bridge deck pavement components, and the experimental environment is set up. Two traditional numerical simulation methods and the researched numerical simulation methods are used to carry out the experiments. The results show that: the bridge deck paving obtained by the researched numerical simulation method displacement value closest to the actual value of displacement, numerical simulation results more accurate.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134557432","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
Fast Segmentation of Complex Texture Image Based on Fractional Order CV Model 基于分数阶CV模型的复杂纹理图像快速分割
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332858
Yang Ying, Li Dong-rui, Huang Xiaofeng
{"title":"Fast Segmentation of Complex Texture Image Based on Fractional Order CV Model","authors":"Yang Ying, Li Dong-rui, Huang Xiaofeng","doi":"10.1109/IAAI51705.2020.9332858","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332858","url":null,"abstract":"To improve the segmentation effect of complex texture images, a fast segmentation method for complex texture images based on fractional CV model is proposed. On the basis of the fractional order CV model, the input image is divided into several compact, uniform and almost the same size super-pixel regions. The saliency value of the super-pixel region is enhanced by smoothing operation, and the global contrast of the complex texture image is calculated. The segmentation strategy from coarse to fine and step by step refinement is adopted. Finally, the segmentation algorithm is used to realize the segmentation of complex texture image. The experimental results show that this method can enhance the image segmentation effect, and the actual application effect is better.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131239133","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 the Integration Method of Ideological and Political Course Resources Based on Mobile Learning 基于移动学习的思想政治课资源整合方法研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332882
Xiaojun Chen
{"title":"Research on the Integration Method of Ideological and Political Course Resources Based on Mobile Learning","authors":"Xiaojun Chen","doi":"10.1109/IAAI51705.2020.9332882","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332882","url":null,"abstract":"In order to improve the learning effect of students' Ideological and political courses, this paper proposes a method of Integrating Ideological and Political Curriculum Resources Based on mobile learning. Through the establishment of resource integration framework, the ideological and political curriculum resources are mined, and the resources are transformed. According to the transformation results, the ideological and Political Curriculum Resources Integration Based on mobile learning is realized by using mobile learning method to allocate the resources of Ideological and political curriculum database in the network. The experimental results show that the method of Ideological and Political Curriculum Resource Integration Based on mobile learning is faster and shorter than the traditional integration method, and has certain practical significance.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133253994","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
Damage Identification Method of Reinforced Concrete Bridge Structure based on Modal Technology 基于模态技术的钢筋混凝土桥梁结构损伤识别方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332817
Weiwei Zhan, Xinghang Long, Xulan Gui
{"title":"Damage Identification Method of Reinforced Concrete Bridge Structure based on Modal Technology","authors":"Weiwei Zhan, Xinghang Long, Xulan Gui","doi":"10.1109/IAAI51705.2020.9332817","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332817","url":null,"abstract":"In the actual identification of reinforced concrete bridge structure damage, the sensitivity of each mode shape to the structure damage location is different, resulting in the final damage identification method which can identify the number of damage indicators is too small. In view of this deficiency, a damage identification method of reinforced concrete bridge structure based on Modal technology is proposed. Based on the reinforced concrete bridge structure data, the modal technology is used to calculate the curvature of the load surface, and the multi-order modal curvature is selected to comprehensively locate the damage, construct the relationship between the damage degree and the bridge area, and combine the structural damage mechanical characteristics to form a damage identification process. Complete the design of damage identification method. Two traditional damage identification methods and the identification method designed in this paper are used to carry out experiments. The results show that the proposed method can identify more structural damage indicators.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115556881","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
Artificial Intelligence-Based Optimal Control Method for Energy Saving in Food Supply Chain Logistics Transportation 基于人工智能的食品供应链物流运输节能优化控制方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332849
Sun Gui-e, Sun Jian-guo
{"title":"Artificial Intelligence-Based Optimal Control Method for Energy Saving in Food Supply Chain Logistics Transportation","authors":"Sun Gui-e, Sun Jian-guo","doi":"10.1109/IAAI51705.2020.9332849","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332849","url":null,"abstract":"Food supply chain logistics will produce a lot of energy consumption in the process of transportation, which has a great impact on the environment and production economy. Therefore, in order to reduce energy consumption as much as possible and complete the original transportation task, an optimization control method based on artificial intelligence for food supply chain logistics transportation is proposed. The artificial intelligence technology is used to realize the information sharing of transportation logistics, decompose the influence parameters of energy consumption of logistics transportation, plan the optimal road of target transportation, and reduce the energy consumption in transportation. The experimental results show that after the optimization of this method, the logistics transportation cost of food supply chain can be effectively reduced, and the energy consumption of transportation can be reduced.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127097450","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: 1
Research on on-line Monitoring Method of Automatic Production Line based on Industrial Internet of Things 基于工业物联网的自动化生产线在线监测方法研究
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332863
Dong-bao Ma, Ming-fei Qu
{"title":"Research on on-line Monitoring Method of Automatic Production Line based on Industrial Internet of Things","authors":"Dong-bao Ma, Ming-fei Qu","doi":"10.1109/IAAI51705.2020.9332863","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332863","url":null,"abstract":"The traditional monitoring method can only monitor part of the industrial production, and the continuity is poor, which is easy to cause the quality gap of different batches of products. To this end, this article designs a new online monitoring method for automated production lines based on the Industrial Internet of Things. First, establish an industrial field device-level network architecture, determine the functions and transmission methods between each layer of the framework, and ensure that the received data can be parsed, processed, and stored normally. Then the PLC technology is introduced to realize the logic control, analog control and motion control in the monitoring method stably, and the abnormal control chart is identified and corrected in time. The experimental results show that the quality of the products is more stable and more in line with the requirements of product standards after the application of the method in this paper.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130996355","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: 1
DC Side Voltage Monitoring Model of Transformer based on Pattern Recognition 基于模式识别的变压器直流侧电压监测模型
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332908
Liu Xian-zhong, Shao Wen-mian
{"title":"DC Side Voltage Monitoring Model of Transformer based on Pattern Recognition","authors":"Liu Xian-zhong, Shao Wen-mian","doi":"10.1109/IAAI51705.2020.9332908","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332908","url":null,"abstract":"Aiming at the problem that the transformer DC side voltage is affected by the voltage quality during the monitoring process, its monitoring performance is greatly reduced. In order to improve the monitoring effect of the transformer DC side voltage, a transformer DC side voltage monitoring model based on pattern recognition is designed. Pattern recognition based on the RMS method using DC voltage transformer discrete signal processing using a pure sinusoidal AC signal with the average RMS mathematical relationship, by calculating the average of the AC voltage, indirectly, of the DC voltage transformer Valid values. From the OPP-CI model that ignores the influence of the ZIB node and the OPP-CI model that considers the influence of the ZIB node, pattern recognition is used to establish the transformer DC side voltage OPP-CI model, and the transformer DC side voltage monitoring process design is combined to realize the transformer DC Monitoring of side voltage. The experimental results show that the error of the monitoring results of the proposed model is relatively low, indicating that the method can improve the monitoring effect of the transformer DC side voltage(Abstract).","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123374585","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
Method for Identifying Cracks In Mass Concrete of Bridge Engineering based on Image Processing 基于图像处理的桥梁工程大体积混凝土裂缝识别方法
2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) Pub Date : 2020-12-25 DOI: 10.1109/IAAI51705.2020.9332860
Chunbao Xiong
{"title":"Method for Identifying Cracks In Mass Concrete of Bridge Engineering based on Image Processing","authors":"Chunbao Xiong","doi":"10.1109/IAAI51705.2020.9332860","DOIUrl":"https://doi.org/10.1109/IAAI51705.2020.9332860","url":null,"abstract":"Due to the influence of the initial video image quality of concrete cracks, there are obvious identification errors in traditional bridge engineering mass concrete crack identification. Therefore, the image processing technology is used to optimize the design of mass concrete crack identification method. The image acquisition equipment is installed and calibrated to obtain the initial crack image of mass concrete of bridge engineering. The image processing technology is used to preprocess the initial image through the steps of graying, denoising, smoothing and smoothing. On this basis, the crack image features are extracted and fused to obtain the crack recognition results of mass concrete of bridge engineering including crack category, crack width and other information. Compared with the traditional recognition method, the average correct recognition rate of the design method is increased by 9.3%.","PeriodicalId":232194,"journal":{"name":"2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126087608","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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