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2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)最新文献

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Error Compensation for Long Arm Manipulator Based on Deflection Modeling and Neural Network 基于挠度建模和神经网络的长臂机械臂误差补偿
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668690
Haoying Li, Chenhao Fang, Jinze Shi, Baocheng Zeng, Chunlin Zhou
{"title":"Error Compensation for Long Arm Manipulator Based on Deflection Modeling and Neural Network","authors":"Haoying Li, Chenhao Fang, Jinze Shi, Baocheng Zeng, Chunlin Zhou","doi":"10.1109/AUTEEE52864.2021.9668690","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668690","url":null,"abstract":"Long arm manipulators are designed to work in special conditions including aviation, engineering, and other scenarios that require a large span operation. However, since the long arm will cause a large flexible error, the manipulators maintain large terminal absolute error and difficulty in control. In addition, testing in a real machine is time and economic consuming, and obtaining enough data is untoward. Under such conditions, this paper proposes an error compensation method for a long arm manipulator combining deflection error modeling and neural network, using a specially designed long arm manipulator. By using this method, better results are achieved than traditional error modeling alone since non-traceable errors are also compensated for. The result is also better than neural network compensation alone since in the case of less training data preferable results can still be achieved.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115475917","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
A Novel Digital watermarking Approach under the DCT and SVM 一种基于DCT和SVM的数字水印方法
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/auteee52864.2021.9668682
Hui Chen, Ling Zhang
{"title":"A Novel Digital watermarking Approach under the DCT and SVM","authors":"Hui Chen, Ling Zhang","doi":"10.1109/auteee52864.2021.9668682","DOIUrl":"https://doi.org/10.1109/auteee52864.2021.9668682","url":null,"abstract":"The important direction of information hiding is digital watermarking technology. The traditional digital watermarking is advantage to against general attacks, but it is difficult to the geometrial distortions. This paper proposes a novel digital watermarking based on discrete cosine transform and support vector machine. Firstly, the block discrete cosine transformation is used for watermarking embedding, then the trained support vector machine is used to roughly correct the geometric parameters and the template matching method is used to correct the existing errors. Experiments show that the purposed algorithm is not only against traditional attacks such as noise, filtering and clipping, but also better robustness against geometrial distortions.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890404","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 output characteristics of piezoelectric energy harvester with different circuit load 不同电路负载下压电能量采集器输出特性研究
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668770
Kai Zhang, Liansai Dong, Y. Zhu
{"title":"Research on output characteristics of piezoelectric energy harvester with different circuit load","authors":"Kai Zhang, Liansai Dong, Y. Zhu","doi":"10.1109/AUTEEE52864.2021.9668770","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668770","url":null,"abstract":"The energy output characteristics of piezoelectric stack energy collection device are studied in this paper, the electromechanical coupling dynamic model of piezoelectric vibration system with different loads is established, and the general mathematical expressions of system output voltage and output power are obtained. Taking the piezoelectric material of PZT-5A as an example, The simulation calculation and analysis are carried out by using the model, and the piezoelectric materials, excitation frequency The voltage output characteristics of excitation force amplitude under different loads are analyzed, and the influencing factors and optimization conditions of system optimal output characteristics under different conditions are analyzed.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124707346","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
Practical application of pedestrian intelligent detection technology based on computer vision 基于计算机视觉的行人智能检测技术的实际应用
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668691
M. Liu
{"title":"Practical application of pedestrian intelligent detection technology based on computer vision","authors":"M. Liu","doi":"10.1109/AUTEEE52864.2021.9668691","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668691","url":null,"abstract":"Pedestrian detection based on computer vision technology uses camera equipment mounted in vehicles to obtain driving image data, and then calculates whether pedestrians exist from the image or sequence and gives accurate positioning. It improves the safety of driverless vehicles to a large extent and greatly reduces the probability of accidents Pedestrian detection is the use of computer vision technology to determine whether there is a pedestrian in the image or sequence, and at the same time to locate the pedestrian technology. In this paper, first of all, the threshold method, image segmentation technology is described, and then the feature extraction method is divided into two different categories of bottom features and machine learning to make an introduction, and then the classifier construction method is summarized. Finally, the future research of pedestrian detection technology is prospected through the existing problems.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125038902","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
Anti-freezing performances of novel natural draft dry cooling tower with double-layer air-cooled heat exchanger 新型双层空冷式自然通风干式冷却塔的防冻性能
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/auteee52864.2021.9668833
Tongrui Cheng, Zhenning Zhao, Junfu Lv, Hangqiang Yu
{"title":"Anti-freezing performances of novel natural draft dry cooling tower with double-layer air-cooled heat exchanger","authors":"Tongrui Cheng, Zhenning Zhao, Junfu Lv, Hangqiang Yu","doi":"10.1109/auteee52864.2021.9668833","DOIUrl":"https://doi.org/10.1109/auteee52864.2021.9668833","url":null,"abstract":"To the purpose of lower initial cost, the novel natural draft dry cooling tower (NDDCT) with the double-layer air-cooled heat exchanger (ACHE) is employed in a $2times 660{mathrm {MW}}$ dry cooling power plant. In cold days, the NDDCT may encounter the frozen risk due to redundant cooling capability of the cooling air. To revealing the anti-freezing performances of the novel NDDCT, the coupling effects of the ambient temperature with the circulating water flow rate, the circulating water outlet temperature and the heat load are investigated by numerical calculation. As a result, the critical anti-freezing parameters are obtained. Furthermore, the precondition of the units working under the chocking turbine back pressure is assumed for the energy-efficient operation of the power plant. The results show that, when the power output drops, the critical anti-freezing circulating water flow rate decreases and the critical anti-freezing ambient temperature rises. The strategy of reducing the number of the sector in operation is able to diminish the critical anti-freezing ambient temperature significantly with better anti-freezing performances. The NDDCT with one unit in operation has better anti-freezing performances than that with two units due to the deteriorated heat flow performance of the NDDCT, which is caused by the large amount of cold air flows into the NDDCT via the disconnected sectors. With increasing the wind speed at 4 m/s, the critical anti-freezing water flow rate increases, but the critical anti-freezing ambient temperature varies little. In conclusion, this research may provide valuable references of the frozen protection to the safe and economic operation of this novel NDDCT with double-layer ACHE.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"395 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115993471","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
Prediction of ROP Method Based on Online Machine Learning and Multi-source Data Preprocessing Technology 基于在线机器学习和多源数据预处理技术的ROP预测方法
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668634
Yang Yu, M. Cui, Kai Huang, Lei Luo, Xiuling Zhang, Hui Li
{"title":"Prediction of ROP Method Based on Online Machine Learning and Multi-source Data Preprocessing Technology","authors":"Yang Yu, M. Cui, Kai Huang, Lei Luo, Xiuling Zhang, Hui Li","doi":"10.1109/AUTEEE52864.2021.9668634","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668634","url":null,"abstract":"The drilling operation is a large scale, technically complex and systematic project, which has always taken the top position of investment in oil exploration and development. Speed and efficiency are the primary goals of drilling engineering. Using information technology to optimize drilling parameters can reduce the complexity of accidents, improve the time efficiency of drilling, and significantly shorten the drilling construction cycle and save exploration and development costs. Forecasting drilling rate of penetration (ROP) is an essential component of drilling optimization. This paper introduces a machine learning-based permeability prediction method and its application effects. In response to the drilling rate of penetration (ROP) problem, a drilling rate of penetration (ROP) model based on an integrated learning algorithm is designed and implemented by mining the historical data collected from a specific block. Meanwhile, this approach is compared with traditional machine learning algorithms such as SVM, LR and KNN. The experimental results indicate that the algorithm has better accuracy and applicability than other methods, which can provide a scientific and reliable reference for improving drilling rate of penetration (ROP) and technical support for realizing intelligent drilling.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128455607","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
Computer intelligent prediction model of internet impulsive reward based on user portrait algorithm 基于用户画像算法的网络脉冲奖励计算机智能预测模型
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668736
Na Wang
{"title":"Computer intelligent prediction model of internet impulsive reward based on user portrait algorithm","authors":"Na Wang","doi":"10.1109/AUTEEE52864.2021.9668736","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668736","url":null,"abstract":"In order to improve the matching degree between the prediction results of minors' impulsive reward behavior and the actual results, the design and research of minors' impulsive reward behavior prediction method based on user portrait is carried out. Take a webcast platform as an example to obtain the impulse reward data of some minors; Combined with the data, the attribute tag statistical database of minor users is constructed to describe the abnormal reward behavior of minors; Combined with the use of association rules, the trend of minors' impulsive reward is predicted, so as to complete the design of the prediction method of minors' impulsive reward behavior. The experimental results show that the designed method can accurately predict the impulsive reward behavior of minors in practical application, and the accuracy rate of prediction results is more than 0.90.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126694836","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
A Short-term Load Forecasting Model Based on Neural Network Considering Weather Features 考虑天气特征的神经网络短期负荷预测模型
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/auteee52864.2021.9668698
Feifei Xu, Wenjun Xu, Yidan Qiu, Mei Wu, Ruoyu Wang, Yonghui Li, Peixiao Fan, Jun Yang
{"title":"A Short-term Load Forecasting Model Based on Neural Network Considering Weather Features","authors":"Feifei Xu, Wenjun Xu, Yidan Qiu, Mei Wu, Ruoyu Wang, Yonghui Li, Peixiao Fan, Jun Yang","doi":"10.1109/auteee52864.2021.9668698","DOIUrl":"https://doi.org/10.1109/auteee52864.2021.9668698","url":null,"abstract":"In recent years, the grid load has been significantly affected by meteorological factors, showing strong nonlinearity and unpredictability, which brings great difficulties to load forecasting. Therefore, the use of meteorological factors for short-term load forecasting has become an indispensable factor to improve the application of smart grid. This paper first collects and analyzes the data of grid load, then disposes the abnormal load data. Secondly, meteorological factors such as temperature, humidity, wind speed, daily radiation, and rainfall are analyzed one by one, and the trend of load changes with temperature and humidity is obtained from this. Besides, these meteorological factors are coupled, and a comprehensive weather perception index is proposed to express the influence of the above factors on human skin perception. Finally, with the comprehensive weather perception index and load data as input, a BP neural network model is established for load forecasting, and actual calculation examples prove the high accuracy and rapidity of the method.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129108328","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
A fault time detection method for distribution network based on multi-order wavelet function transform 基于多阶小波函数变换的配电网故障时间检测方法
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668679
Zhi Li, Kai Wang, Yong Li, Shibiao Tang, Shaofeng Yu
{"title":"A fault time detection method for distribution network based on multi-order wavelet function transform","authors":"Zhi Li, Kai Wang, Yong Li, Shibiao Tang, Shaofeng Yu","doi":"10.1109/AUTEEE52864.2021.9668679","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668679","url":null,"abstract":"distribution network fault time is the key to realize fault data synchronization and fault location, and it is also the core of advanced application of fault location algorithm in distribution automation master station. Therefore, on the basis of summarizing the applicability of fault location methods, this paper proposes a distribution network fault time detection method based on multi-order wavelet transform for engineering applications. Firstly, the fault occurrence interval is located by sliding window FFT, the characteristic signal to be decomposed is extracted, and the characteristic signal is decomposed by multi-order wavelet transform. The modulus maxima is used to solve the time of fault occurrence. Finally, through the simulation of single-phase grounding fault in multi scenario distribution network, the simulation results show that this method can accurately calculate the time of fault, and has good robustness and high reliability.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130658430","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
Optimal Dispatching of Wind Storage Combined Power System Based on Particle Swarm Optimization in Low Carbon Economy 低碳经济下基于粒子群优化的风储联电系统优化调度
2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2021-11-19 DOI: 10.1109/AUTEEE52864.2021.9668777
K. Sun
{"title":"Optimal Dispatching of Wind Storage Combined Power System Based on Particle Swarm Optimization in Low Carbon Economy","authors":"K. Sun","doi":"10.1109/AUTEEE52864.2021.9668777","DOIUrl":"https://doi.org/10.1109/AUTEEE52864.2021.9668777","url":null,"abstract":"With the continuous progress of global economy and sci & tech, the demand for various kinds of energy is increasing exponentially, and the energy industry is also developing on an unprecedented scale. Wind energy is a widely used new energy, with the characteristics of cleanness and environmental protection. It is one of the new energy sources with the most mature research technology and the highest degree of development and utilization. At present, the environmental economic dispatch with wind farm has become a very important research topic. Due to the randomness and volatility of wind force, the conventional power system analysis, dispatching and control methods are facing new challenges. In this paper, the optimal dispatching problem of power system with wind farm is deeply studied, and a dispatching model based on multi-objective particle swarm optimization algorithm is established.","PeriodicalId":406050,"journal":{"name":"2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127676481","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
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