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2020 2nd International Conference on Industrial Artificial Intelligence (IAI)最新文献

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Fault detection for wind turbines via long short-term memory network 基于长短期记忆网络的风力发电机故障检测
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262179
Xiaoxuan Dou, W. Tan, Sixuan Chen, Mengjie Li
{"title":"Fault detection for wind turbines via long short-term memory network","authors":"Xiaoxuan Dou, W. Tan, Sixuan Chen, Mengjie Li","doi":"10.1109/IAI50351.2020.9262179","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262179","url":null,"abstract":"Wind energy is renewable and clean, which plays an important role in energy structure nowadays. However, the operation and maintenance cost of wind turbines (WT) is high, imposing restrictions on its development. Thus, it is necessary to detect early faults in wind turbines. This paper proposes a real-time wind turbine fault detection method. The method utilizes long short-term memory (LSTM) network as the residual generator. The improved network cross-LSTM learns all collected variables to predict the output of wind turbine benchmark, and then the differences between the predicted and true value from the residuals. It also combines the real-time signal processing with LSTM network to classify the faults defined in the benchmark. The simulation results for this method have been compared with other three methods on the benchmark, showing that the former has better accuracy.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131923510","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
Modeling and Verification of Train Operation in Stations and Block Sections Using Petri Nets 基于Petri网的站段列车运行建模与验证
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262235
Luxi Wang, Yin Tong, Xiaomin Wang
{"title":"Modeling and Verification of Train Operation in Stations and Block Sections Using Petri Nets","authors":"Luxi Wang, Yin Tong, Xiaomin Wang","doi":"10.1109/IAI50351.2020.9262235","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262235","url":null,"abstract":"The feasibility of train operation plans is an important issue in the field of railway transportation. The train operation plan provides departure, arrival and passing time of the train at each station. This paper not only studies the feasibility of train operation plans, but also considers dispatching operations in stations. Based on a given track layout including stations and block sections, its Petri net model is constructed to verify the feasibility of block section operations and station dispatch. According to the time constraints of the train operation, time factors are assigned to corresponding transitions in the Petri net model. We have further developed a feasibility verification algorithm. Petri net simulation tool TINA is used to verify the feasibility of the proposed train operation plan. We have shown that the proposed feasibility verification algorithm can identify the faults and provide amendments if a train operation plan is not feasible.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"229 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133571568","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
Fuzzy Control Method for an Intelligent Walking Training Robot for User Fall Prevention 智能步行训练机器人防跌倒模糊控制方法
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262226
Bo Shen, Junfeng Wang, Shuoyu Wang, H. Enoki, K. Ishida
{"title":"Fuzzy Control Method for an Intelligent Walking Training Robot for User Fall Prevention","authors":"Bo Shen, Junfeng Wang, Shuoyu Wang, H. Enoki, K. Ishida","doi":"10.1109/IAI50351.2020.9262226","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262226","url":null,"abstract":"In this paper, a fuzzy control method is proposed for user fall prevention during walking training of the intelligent walking training robot (IWTR). In clinical rehabilitation sites, an experienced human caregiver can always assist patients with walk training and prevent them from falling risks by providing observational and force interaction information. However, for a robot to detect the user's falling risk and make the appropriate movement to help the user to obtain balance is challenging. In this study, we investigated a fuzzy control method for motion control of an IWTR to implement a falling prevention strategy that would be the same as provided by human experts during walking rehabilitation. By extracting the knowledge of human experts on fall prevention as fuzzy rules, the IWTR can determine the appropriate falling prevention motion according the information from a monocular camera and four force sensors. The monocular camera is applied to sense the relative position of the user to the IWTR. The force sensors are placed under the armrest of the IWTR to detect the interaction force between the user and IWTR. The distance and interaction force information are taken as the input for the fuzzy controller, and the motion velocity can be determine to control the IWTR to prevent users from falling down similar to human rehabilitation experts. Finally, experiments were implemented for verification. The result showed the effectiveness of the proposed method for fall prevention.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133326846","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 Railway Freight Loading and Reinforcement Schemes based on Case-based Reasoning, CBR 基于案例推理的铁路货物装载与加固方案研究
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262156
Qingwei Kong, Nan Li, Xiaofang Feng, Weibin Liu
{"title":"Research on Railway Freight Loading and Reinforcement Schemes based on Case-based Reasoning, CBR","authors":"Qingwei Kong, Nan Li, Xiaofang Feng, Weibin Liu","doi":"10.1109/IAI50351.2020.9262156","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262156","url":null,"abstract":"Railway freight loading and reinforcement plays an essential role in transportation security. China has an enormous spread of freight operation, however, a great number of freight stations still use manual drawing and calculation based on the staff's experience, which causes poor practicability and low efficiency. In this research, a method of generating schemes based on Case-based Reasoning (CBR) and extension theory was proposed. The study combines intelligent algorithms and theoretical knowledge in railway freight loading and reinforcement, which can implement auto-matching and generation of loading and reinforcement schemes under complex loading scenarios. The reliability of the scheme is also verified through an example. The research simplifies the generation process of loading and reinforcement scheme. It has a great significance in increasing freight operation efficiency and developing intelligent control technology.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123916882","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
Fault classification and detection using an improved statistical analysis method 采用改进的统计分析方法进行故障分类和检测
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262214
X. Tang, H.Z. Zhang, Y. Li
{"title":"Fault classification and detection using an improved statistical analysis method","authors":"X. Tang, H.Z. Zhang, Y. Li","doi":"10.1109/IAI50351.2020.9262214","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262214","url":null,"abstract":"In this paper, a new statistical method for fault classification and fault detection based on independent component analysis (ICA) and Fisher discriminant analysis (FDA) is proposed. In this method, The ICA method is used to extract feature from original data space. Then, FDA method is performed in ICA feature space for fault classification and detection. Based on such a mixing method, the performance of fault classification and detection is improved. The proposed method is applied to Iris classification and Tennessee Eastman process (TEP). The results show proposed method has more superior performance of fault classification and fault detection.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"462 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116558389","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
Attitude Control for Rocket Main-stage-booster Recovery with Parafoil Using Sliding Mode Control 采用滑模控制的火箭主助推器带伞回收姿态控制
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262185
Fenghao Li, Xiaojun Xing, Yiming Guo, Xiaoran Chen, Yilin Xun, Qi Wei
{"title":"Attitude Control for Rocket Main-stage-booster Recovery with Parafoil Using Sliding Mode Control","authors":"Fenghao Li, Xiaojun Xing, Yiming Guo, Xiaoran Chen, Yilin Xun, Qi Wei","doi":"10.1109/IAI50351.2020.9262185","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262185","url":null,"abstract":"Parafoil-based rocket booster recovery technology currently has been a very important research field in aerospace, which is helpful in booster reusage, cost reduction, landing domain narrowing of rocket launch. In order to guarantee the accurate recovery of a certain rocket main-stage-booster using parafoil, the 6-DOF nonlinear mathematical model of the parafoil with main-stage-booster is established according to dynamics and kinemics analysis. Subsequently, the sliding mode variable structure control, which based on the exponential approach law, is proposed to develop the attitude and trajectory tracking control of the combination of parafoil and main-stage booster. The simulation results show that the attitude controller has favorable performance, and the trajectory controller tracks the desired flight path very well.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124737261","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 Relative Position Control of Ducking Phase for Helicopter Aerial Refueling 直升机空中加油俯冲阶段相对位置控制研究
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262223
Junfei Zhang, D. Yuan, Zhifu Tang, Yi Gao, Xiaojun Xing, Yuquan He
{"title":"Research on Relative Position Control of Ducking Phase for Helicopter Aerial Refueling","authors":"Junfei Zhang, D. Yuan, Zhifu Tang, Yi Gao, Xiaojun Xing, Yuquan He","doi":"10.1109/IAI50351.2020.9262223","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262223","url":null,"abstract":"For conventional helicopters, the combat radius is restricted to a certain extent by the limitations of the tank capacity and the maximum takeoff weight. Aerial refueling can expand the combat radius of helicopter, so helicopter aerial refueling technology has become one of the key areas of research in various countries. The docking process is the key to the implementation of aerial refueling, which is related to the successful completion of aerial refueling task. Based on the linearized model of helicopter with small disturbances, the control strategy during the docking stage is designed in this paper, and then the aerial refueling position control system is designed. Finally, in order to improve the control precision of position control system, the flight control law based on LQR is designed and simulation experiments are carried out. The simulation results show that the position control system can successfully achieve the control of the relative distance between the tanker and receiver in the docking stage.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128542927","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 Weapon Equipment Procurement Policy Hot Topics Based on LDA Model 基于LDA模型的武器装备采购政策热点问题研究
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262165
Xiaosong Li, Xinran Peng, Zenghua Li
{"title":"Research on Weapon Equipment Procurement Policy Hot Topics Based on LDA Model","authors":"Xiaosong Li, Xinran Peng, Zenghua Li","doi":"10.1109/IAI50351.2020.9262165","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262165","url":null,"abstract":"A scientific, systematic and standardized procurement policy of weapon equipment is an important guarantee for the modernization of weapon equipment. This paper proposed the hot topic analysis of weapon equipment procurement policy based on the LDA model, analyzed the keywords of weapon equipment procurement policy text, used the LDA model to analyze the text topic, obtained the topic and topic word probability distribution, and calculates the text topic popularity. On this basis, hot topics such as weapon equipment procurement project management, supervision and inspection, license management, confidentiality management, and fair competition were analyzed. The research conclusions provide reference for finding the hot topics of weapon equipment procurement policy and further improving weapon equipment procurement policy system.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125452929","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
Phasmatodea population evolution algorithm and its application in length-changeable incremental extreme learning machine Phasmatodea种群进化算法及其在变长增量极限学习机中的应用
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262236
Pei-Cheng Song, S. Chu, Jeng-Shyang Pan, Hong-Mei Yang
{"title":"Phasmatodea population evolution algorithm and its application in length-changeable incremental extreme learning machine","authors":"Pei-Cheng Song, S. Chu, Jeng-Shyang Pan, Hong-Mei Yang","doi":"10.1109/IAI50351.2020.9262236","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262236","url":null,"abstract":"Extreme learning machine (ELM) is an effective classification and prediction learning algorithm based on feedforward neural network (FNN). This paper presents the Phasmatodea (stick insect) population evolution algorithm (PPE), which is different from other algorithms, in which each solution represents a population and has two attributes: quantity and growth rate. Combining the concept of similar evolution and the model of population competition, it is a new local search method. The algorithm is compared with the other algorithms on benchmark functions and engineering problems. Then use it to enhance a variant of the ELM model. The results show that the proposed algorithm has a certain competitiveness.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114145778","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: 12
A New Ensemble Learning Method Embedded with PCA-ReliefF Algorithm 一种嵌入PCA-ReliefF算法的集成学习方法
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262231
Yujiao Jiang, Bin Lv, Xiaosong Li, Jing Zhou
{"title":"A New Ensemble Learning Method Embedded with PCA-ReliefF Algorithm","authors":"Yujiao Jiang, Bin Lv, Xiaosong Li, Jing Zhou","doi":"10.1109/IAI50351.2020.9262231","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262231","url":null,"abstract":"Improving the generalization ability of ensemble learning is very important. This paper proposes a new ensemble learning method embedded with PCA-ReliefF Algorithm. It can efficiently remove the influence of noise features, and improve the classification accuracy of ensemble learning. Experiments on UCI dataset show that the method in this paper is feasible and effective, and provides a new research approach for feature classification in pattern recognition.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129034719","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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