2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP)最新文献_第7页

Airborne Lidar Point Cloud Classification fusing Spectral Information 融合光谱信息的机载激光雷达点云分类

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513396

Guoliang Chen, Qi Jin, Xu-qing Zhang, Hai-ming Zhang

{"title":"Airborne Lidar Point Cloud Classification fusing Spectral Information","authors":"Guoliang Chen, Qi Jin, Xu-qing Zhang, Hai-ming Zhang","doi":"10.1109/ICMSP53480.2021.9513396","DOIUrl":"https://doi.org/10.1109/ICMSP53480.2021.9513396","url":null,"abstract":"Airborne lidar scanning technology can quickly obtain a large amount of three-dimensional coordinate information on the surface of ground objects. However, due to the disorder and sparseness of point cloud, how to efficiently process the point cloud has become a research hotspot. In order to achieve a more accurate point cloud classification and solve the problem that the inefficient classification is difficult to meet the follow-up processing requirements of point cloud caused by the lack of point cloud information, an airborne lidar point cloud classification method combining spectral information is proposed. Pointnet ++ is used as the basis of the network. As the perspective changes, we enlarged the radius of the extracted sphere neighborhood and improved the segmentation range of the network input subset. In order to improve the distinction of points, three-dimensional information, laser intensity information and spectral information were fused to make the fused data set. The results of the experiment using the Vaihingen regional benchmark airborne LiDAR point cloud sets provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) show that the overall classification accuracy reached 86.21% after the fusion of spectral information, which was 10.02% higher than that before the fusion. The fusion of spectral information can effectively improve the classification effect and provide reliable information for the follow-up processing of airborne lidar point cloud.","PeriodicalId":153663,"journal":{"name":"2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128890752","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 time-domain response characteristics of RLC resonant circuit based on magnetostrictive transducer under sinusoidal excitation 正弦激励下磁致伸缩换能器RLC谐振电路的时域响应特性研究

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513337

Z. Li, Q. Zhang, Jia Tian Zhang, K. Shi

{"title":"Research on the time-domain response characteristics of RLC resonant circuit based on magnetostrictive transducer under sinusoidal excitation","authors":"Z. Li, Q. Zhang, Jia Tian Zhang, K. Shi","doi":"10.1109/ICMSP53480.2021.9513337","DOIUrl":"https://doi.org/10.1109/ICMSP53480.2021.9513337","url":null,"abstract":"Submerged arc furnace, also known as electric arc furnace or resistance electric furnace, it is an industrial electric furnace with continuous operation and huge power consumption. It is mainly used for smelting calcium carbide, industrial silicon, ferrosilicon, silicomanganese, ferronickel, ferrochrome and other important modern industries. In order to solve the problems of the accuracy of length measurement in the submerged arc furnace and the difficulty of the upper computer to collect and process the acoustic signal, In this paper, the loss characteristics and propagation characteristics of the ultrasonic in the submerged arc furnace and the time-domain response characteristics of the RLC resonant circuit based on the magnetostrictive transducer under the excitation of the sinusoidal signal are optimized. The study found that in the under-damped response, the time for the magnetostrictive transducer RLC resonant circuit to reach the steady-state response has an exponential relationship with the external resistance of the resonant circuit. In other words, a suitable external resistance can be selected under the under-damped response. The external resistance value not only ensures that the time for the current to reach a steady state is less than 200us, but also ensures that the impedance of the loop is small enough to obtain a current that meets the requirements.","PeriodicalId":153663,"journal":{"name":"2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124593518","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

The Synthesis And Evaluation of a High-Efficiency Crude Oil Pour Point Depressant 一种高效原油降凝剂的合成与评价

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513382

Lv Zhifeng, Wang Liming, Gao Ruimei, Xu Jiahui, Mou Guoyi

引用次数: 0

Design of online traffic monitoring system based on STM32 and Lora 基于STM32和Lora的在线交通监控系统设计

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513356

Dang Ruirong, Qiao Jianyu

引用次数: 1

An ECG pre-amplifier with $2.89 mumathrm{W}$ and 86.73dB CMRR 一种心电前置放大器，具有2.89 mumath {W}$和86.73dB CMRR

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513380

Yixin Cao, Yixin Dai, Bohang Ye

引用次数: 0

Research on Decline Pattern Recognition of Hydraulic System 液压系统衰落模式识别研究

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513411

Qi Ma, D. Song, Bobing Liu

引用次数: 0

Fracture Analysis of Stress Corrosion Cracking in Heat Exchanger Tubes 换热器管应力腐蚀开裂断裂分析

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513397

Jin-hui Zhai, Beibei Sun

引用次数: 0

Simulation Study on Thickness Measurement Characteristics of Pipeline Axial Shear Wave based on EMAT 基于EMAT的管道轴向横波测厚特性仿真研究

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513404

Guo-wang Gao, Wei Yang, Yulong Qu, Le Hua, Dongliang Zhao, Runsen Bai

引用次数: 1

Distributed temperature sensing technology for oil and gas Wells based on weak reflection Fiber Bragg Grating 基于弱反射光纤光栅的油气井分布式温度传感技术

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513422

X. Zhong, Min Yang, Lei Shi, L. Chai, Sai Ye

{"title":"Distributed temperature sensing technology for oil and gas Wells based on weak reflection Fiber Bragg Grating","authors":"X. Zhong, Min Yang, Lei Shi, L. Chai, Sai Ye","doi":"10.1109/ICMSP53480.2021.9513422","DOIUrl":"https://doi.org/10.1109/ICMSP53480.2021.9513422","url":null,"abstract":"For the down-hole distributed temperature measurement problem in the oil industry, the paper uses femtosecond laser direct-written weak reflection fiber Bragg grating (FBG) to construct a down-hole distributed temperature measurement system. The paper analyzes the principle and technical advantages of weak reflection FBG to form a large-scale distributed temperature sensing array; proposes a dual optical path noise suppression method, which effectively eliminates the influence of optical power fluctuations on the measurement results and improves the accuracy and stability of the system temperature measurement; uses self-developed strongly coupled multi-core optical fiber to build a ramp filter, which solves the key problem of fast demodulation of the output of the weak reflection FBG array. The technical problems of fast demodulation of the output of weak FBG arrays were solved by using self-developed strong-coupled multi-core optical fiber. Finally, the developed temperature measurement system was experimentally calibrated and tested in a simulated well, and the test results showed that the accuracy of the system reached 0.5°C with a spatial resolution of 50 cm. The down-hole experimental tests showed that the system has good resistance to high pressure and can operate stably for a long time under high temperature and pressure.","PeriodicalId":153663,"journal":{"name":"2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP)","volume":"460 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133303732","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

High Resolution Remote Sensing Image Classification Using Hybrid Ensemble Learning 基于混合集成学习的高分辨率遥感图像分类

2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP) Pub Date : 2021-07-23 DOI: 10.1109/ICMSP53480.2021.9513420

Jiangbo Xi, Dashuai Xie, Wandong Jiang, Yaobing Xiang

{"title":"High Resolution Remote Sensing Image Classification Using Hybrid Ensemble Learning","authors":"Jiangbo Xi, Dashuai Xie, Wandong Jiang, Yaobing Xiang","doi":"10.1109/ICMSP53480.2021.9513420","DOIUrl":"https://doi.org/10.1109/ICMSP53480.2021.9513420","url":null,"abstract":"The classification of the high resolution remote sensing image has become very complex as the resolution improves. Recently, deep learning has been used successfully for high resolution image classification. But it is hard to classify different objects with a large number of pixels, and a small number of pixels at the same time with a single learning model. In this paper the hybrid ensemble learning method is proposed, which combines three kinds of networks: fully connected network, convolutional neural network, and fully convolutional network, to obtain high classification performance. Firstly, the fully connected network is carried out using pixel brightness as features for classification. Secondly, the object-oriented segmentation was used, and the convolutional block was extracted from the center of gravity and the convolutional neural network was used for classification. Thirdly, images were clipped into image blocks, and fully convolutional network U-Net was used with one versus all. Finally, the hybrid ensemble learning method is used, in which a fully connected network is trained for probabilistic combination using the classification results of the three base classifiers. The proposed method was tested with a large number of experiments on Vaihingen aerial image dataset, and the results showed the hybrid ensemble learning method has best performance compared with the single classical neural network and the deep learning method.","PeriodicalId":153663,"journal":{"name":"2021 3rd International Conference on Intelligent Control, Measurement and Signal Processing and Intelligent Oil Field (ICMSP)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127555479","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