Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9858957
Zhihai Wu, Linbo Xie
This paper investigates fault-tolerant consensus of single-integrator multi-agent systems (MASs) with partial agents subject to synchronous self-sensing function failure (SSFF). First, a strategy of recovering the connectivity of network topology among normal agents is proposed via multi-hop communication together with agents subject to SSFF as routing nodes. Second, a fault-tolerant consensus protocol with time-varying gains is designed. Then, consensus convergence is analyzed by separately investigating the dynamics of normal agents and agents subject to SSFF. It is proved that under proper time-varying gains, single-integrator MASs using the proposed strategy of recovering the connectivity of network topology and fault-tolerant consensus protocol can achieve consensus. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.
{"title":"Fault-Tolerant Consensus of Single-Integrator Multi-Agent Systems under Synchronous Self-Sensing Function Failure","authors":"Zhihai Wu, Linbo Xie","doi":"10.1109/ICMSP55950.2022.9858957","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9858957","url":null,"abstract":"This paper investigates fault-tolerant consensus of single-integrator multi-agent systems (MASs) with partial agents subject to synchronous self-sensing function failure (SSFF). First, a strategy of recovering the connectivity of network topology among normal agents is proposed via multi-hop communication together with agents subject to SSFF as routing nodes. Second, a fault-tolerant consensus protocol with time-varying gains is designed. Then, consensus convergence is analyzed by separately investigating the dynamics of normal agents and agents subject to SSFF. It is proved that under proper time-varying gains, single-integrator MASs using the proposed strategy of recovering the connectivity of network topology and fault-tolerant consensus protocol can achieve consensus. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117241975","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9859111
Fei Yuan, Dawei Li, Xiansen Jiang, Lihui Wang
In this paper, machine vision is combined with SCARA robot to realize the intelligent assembly of lithium battery.
本文将机器视觉与SCARA机器人相结合，实现锂电池的智能装配。
{"title":"Visual Scheme Design of Intelligent Assembly of Lithium Battery Using Robot","authors":"Fei Yuan, Dawei Li, Xiansen Jiang, Lihui Wang","doi":"10.1109/ICMSP55950.2022.9859111","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859111","url":null,"abstract":"In this paper, machine vision is combined with SCARA robot to realize the intelligent assembly of lithium battery.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121035795","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9858998
Zhaocheng Hu, D. Hu, Jiantao Wang, Jie Huang
Radar emitter signal recognition is a crucial means to distinguish unknown radars, and it depends on the high quality of received signals. However, signals of Low probability of intercept (LPI) radars are easily interfered with by noise, resulting in poor signal quality and low recognition accuracy. We propose a pulse accumulation method to improve the quality of pulse signals for LPI radar emitter signal recognition. Firstly, the pulse accumulation problem is described. Then we propose the time-domain alignment iterative method (TAIM) to improve the effect of pulse accumulation. Finally, time-frequency images of the accumulated signals are input to the deep residual network for recognition to verify the effect of the proposed method. This approach enhances the effect of pulse accumulation by employing the proposed TAIM, and ultimately improves the performance of signal recognition. Simulation results show that the proposed pulse accumulation method can improve the recognition accuracy by 7% more than that of single-pulse signals at −6dB.
{"title":"A Pulse Accumulation Method for LPI Radar Emitter Signal Recognition","authors":"Zhaocheng Hu, D. Hu, Jiantao Wang, Jie Huang","doi":"10.1109/ICMSP55950.2022.9858998","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9858998","url":null,"abstract":"Radar emitter signal recognition is a crucial means to distinguish unknown radars, and it depends on the high quality of received signals. However, signals of Low probability of intercept (LPI) radars are easily interfered with by noise, resulting in poor signal quality and low recognition accuracy. We propose a pulse accumulation method to improve the quality of pulse signals for LPI radar emitter signal recognition. Firstly, the pulse accumulation problem is described. Then we propose the time-domain alignment iterative method (TAIM) to improve the effect of pulse accumulation. Finally, time-frequency images of the accumulated signals are input to the deep residual network for recognition to verify the effect of the proposed method. This approach enhances the effect of pulse accumulation by employing the proposed TAIM, and ultimately improves the performance of signal recognition. Simulation results show that the proposed pulse accumulation method can improve the recognition accuracy by 7% more than that of single-pulse signals at −6dB.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124821310","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9859166
Ruirong Dang, Fanfan Zhao
This paper is based on data analysis, and on the basis of previous research, using the data obtained by the three-phase flow measuring instrument to conduct research on the three-phase flow rate and moisture content prediction, and establish a response time domain and frequency based on the moisture content meter. The support vector machine regression model (SVR Model) of domain eigenvalues is used to predict the moisture content calibration results of simulated well performance experiments with different flow rates. The model verification results show that the interpretation model can achieve higher moisture content prediction accuracy, and Comparing the proportion of moisture content in indoor experiments to achieve the target of interpretation accuracy of predicted moisture content. On the basis of the interpretation method research, the actual logging data is interpreted. Helps in calculating the production of oil wells in different regions.
{"title":"Predictive analysis of three-phase flow measurement data model","authors":"Ruirong Dang, Fanfan Zhao","doi":"10.1109/ICMSP55950.2022.9859166","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859166","url":null,"abstract":"This paper is based on data analysis, and on the basis of previous research, using the data obtained by the three-phase flow measuring instrument to conduct research on the three-phase flow rate and moisture content prediction, and establish a response time domain and frequency based on the moisture content meter. The support vector machine regression model (SVR Model) of domain eigenvalues is used to predict the moisture content calibration results of simulated well performance experiments with different flow rates. The model verification results show that the interpretation model can achieve higher moisture content prediction accuracy, and Comparing the proportion of moisture content in indoor experiments to achieve the target of interpretation accuracy of predicted moisture content. On the basis of the interpretation method research, the actual logging data is interpreted. Helps in calculating the production of oil wells in different regions.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125809688","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9859099
Shuncai Yao, Jinxuan Shi
This paper mainly studies how to collect useful point cloud data efficiently and accurately by 3D lidar and gives a set of effective fast 3D modeling method. Using LiDAR RS-LIDAR-16 to scan the roads and their surroundings at different measuring stations, the 3d laser point clouds of several stations were obtained. Point cloud registration and denoising were carried out to eliminate noisy scattered point clouds. The experimental results show that this method can realize the modeling of three-dimensional point clouds of different stations and has good modeling effect.
{"title":"Road 3D Point cloud Data Modeling based on LiDAR","authors":"Shuncai Yao, Jinxuan Shi","doi":"10.1109/ICMSP55950.2022.9859099","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859099","url":null,"abstract":"This paper mainly studies how to collect useful point cloud data efficiently and accurately by 3D lidar and gives a set of effective fast 3D modeling method. Using LiDAR RS-LIDAR-16 to scan the roads and their surroundings at different measuring stations, the 3d laser point clouds of several stations were obtained. Point cloud registration and denoising were carried out to eliminate noisy scattered point clouds. The experimental results show that this method can realize the modeling of three-dimensional point clouds of different stations and has good modeling effect.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126173678","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9859240
G. Lai, Xiuhua Zhang, Chengsan Lu, Jingyi Wang
As a typical complex equipment system, helicopter is designed and optimized for its physical entity, and condition monitoring and predictive maintenance is a challenging task. As the link between the physical world and the virtual world, the digital twin technology can express the helicopter with high precision, high real-time and high integration in the virtual space, so as to promote the further study of the helicopter. In this paper, the architecture and key technology of the digital twin system of the helicopter equipment with cloud edge integration are described, and the real-time simulation of the helicopter equipment is realized by making full use of the edge computing power, reducing the cloud computing demand, improving the whole system's computing power, reducing the time and economic consumption in the process of data transmission.
{"title":"The architecture and key technologies of the digital twin system of helicopter based on cloud-edge-end integration","authors":"G. Lai, Xiuhua Zhang, Chengsan Lu, Jingyi Wang","doi":"10.1109/ICMSP55950.2022.9859240","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859240","url":null,"abstract":"As a typical complex equipment system, helicopter is designed and optimized for its physical entity, and condition monitoring and predictive maintenance is a challenging task. As the link between the physical world and the virtual world, the digital twin technology can express the helicopter with high precision, high real-time and high integration in the virtual space, so as to promote the further study of the helicopter. In this paper, the architecture and key technology of the digital twin system of the helicopter equipment with cloud edge integration are described, and the real-time simulation of the helicopter equipment is realized by making full use of the edge computing power, reducing the cloud computing demand, improving the whole system's computing power, reducing the time and economic consumption in the process of data transmission.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123448806","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9858954
Shasha Pu, Lan Li, Yu Xiang, Xiaolong Qiu
Phase retrieval refers to the recovery of the original image using only the Fourier amplitude of the image. Due to the small amount of information contained in the Fourier amplitude, the common network structure cannot achieve accurate reconstruction of the image when the oversampling rate of the image is low. It is the key issue of phase retrieval to improve the structure of the neural network. We propose an application of end-to-end adversarial network to solve phase retrieval problems by adding a U-Net model to the conditional generative adversarial network(U-NetCGAN). This desired approach realizes multi-scale recognition and fusion of image features and improves the quality of image reconstruction. The experimental results show that the model is significantly better than the traditional phase retrieval algorithm. Compared to other algorithms, the evaluation indicators of PSNR and SSIM values in our approach have increased about 6 dB and 0.1, respectively.
{"title":"Phase Retrieval Based on Enhanced Generator Conditional Generative Adversarial Network","authors":"Shasha Pu, Lan Li, Yu Xiang, Xiaolong Qiu","doi":"10.1109/ICMSP55950.2022.9858954","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9858954","url":null,"abstract":"Phase retrieval refers to the recovery of the original image using only the Fourier amplitude of the image. Due to the small amount of information contained in the Fourier amplitude, the common network structure cannot achieve accurate reconstruction of the image when the oversampling rate of the image is low. It is the key issue of phase retrieval to improve the structure of the neural network. We propose an application of end-to-end adversarial network to solve phase retrieval problems by adding a U-Net model to the conditional generative adversarial network(U-NetCGAN). This desired approach realizes multi-scale recognition and fusion of image features and improves the quality of image reconstruction. The experimental results show that the model is significantly better than the traditional phase retrieval algorithm. Compared to other algorithms, the evaluation indicators of PSNR and SSIM values in our approach have increased about 6 dB and 0.1, respectively.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123603180","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}
Industrial product surface defect detection is a challenging task, In this paper, we take flange surface defect detection as the research target and propose a high-performance target detection framework to solve some problems in flange surface defect detection, such as inconspicuous features, small target scale and irregular morphology. The proposed model is based on the You Only Look Once (YOLOX) algorithm for improvement. The improved network architecture makes the model more sensitive to the details of the target by increasing the output of the backbone feature extraction network. The extraction and fusion of features is enhanced by using RFP (Recursive Feature Pyramid) and CBAM (Convolutional Block Attention Module) in the neck of the network. In addition, we compare the effect of different single data enhancement methods on the training effect and propose an enhancement method for flange surface defect data to address the problem of low defect data. Experiments show that the flange surface defect detection algorithm proposed in this paper balances accuracy and speed, outperforms existing advanced detection models, and has good detection capability.
工业产品表面缺陷检测是一项具有挑战性的任务，本文以法兰表面缺陷检测为研究目标，提出了一种高性能的目标检测框架，解决了法兰表面缺陷检测中存在的特征不明显、目标尺度小、形态不规则等问题。提出的模型是基于You Only Look Once (YOLOX)算法进行改进的。改进后的网络结构通过增加骨干特征提取网络的输出，使模型对目标的细节更加敏感。在网络颈部采用递归特征金字塔(RFP)和卷积块注意模块(CBAM)增强特征的提取和融合。此外，我们比较了不同单一数据增强方法对训练效果的影响，提出了一种针对法兰表面缺陷数据的增强方法，以解决缺陷数据低的问题。实验表明，本文提出的法兰表面缺陷检测算法平衡了精度和速度，优于现有的先进检测模型，具有良好的检测能力。
{"title":"Detection Approach Based on an Improved YOLOX for Flange Surface Defects","authors":"Yinghao Li, Panpan Liu, Yihao Xiang, Chengming Liu, Haogong Guo","doi":"10.1109/ICMSP55950.2022.9859056","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859056","url":null,"abstract":"Industrial product surface defect detection is a challenging task, In this paper, we take flange surface defect detection as the research target and propose a high-performance target detection framework to solve some problems in flange surface defect detection, such as inconspicuous features, small target scale and irregular morphology. The proposed model is based on the You Only Look Once (YOLOX) algorithm for improvement. The improved network architecture makes the model more sensitive to the details of the target by increasing the output of the backbone feature extraction network. The extraction and fusion of features is enhanced by using RFP (Recursive Feature Pyramid) and CBAM (Convolutional Block Attention Module) in the neck of the network. In addition, we compare the effect of different single data enhancement methods on the training effect and propose an enhancement method for flange surface defect data to address the problem of low defect data. Experiments show that the flange surface defect detection algorithm proposed in this paper balances accuracy and speed, outperforms existing advanced detection models, and has good detection capability.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125306748","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9859028
Juan Su, Liang Guo, Bing Li, Dongkai Huo, Jintao Huang
Horizontal wells increase the contact surface area between wells and reservoirs, so they can enhance oil recovery efficiency effectively. In order to obtain more logging information of horizontal wells, this paper studies the visualization detection technology of horizontal well. By using two-way coding and local large capacity high-speed storage equipment to realize three operation mode-three operation modes of surface readout mode, memory mode and compatibility mode. Special connectors are used to make VideoLog tool to work in three methods by parallel transmission. Video acquisition and analysis software realizes 3D modeling and quantitative analysis of casing pipe. Field tests of 8 horizontal wells show that VideoLog can provide a new horizontal well detection scheme.
{"title":"Video Log Visual Detection Technology of Horizontal Well and Its Application","authors":"Juan Su, Liang Guo, Bing Li, Dongkai Huo, Jintao Huang","doi":"10.1109/ICMSP55950.2022.9859028","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859028","url":null,"abstract":"Horizontal wells increase the contact surface area between wells and reservoirs, so they can enhance oil recovery efficiency effectively. In order to obtain more logging information of horizontal wells, this paper studies the visualization detection technology of horizontal well. By using two-way coding and local large capacity high-speed storage equipment to realize three operation mode-three operation modes of surface readout mode, memory mode and compatibility mode. Special connectors are used to make VideoLog tool to work in three methods by parallel transmission. Video acquisition and analysis software realizes 3D modeling and quantitative analysis of casing pipe. Field tests of 8 horizontal wells show that VideoLog can provide a new horizontal well detection scheme.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125580008","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}
Pub Date : 2022-07-08DOI: 10.1109/ICMSP55950.2022.9859089
Haiyao Wang, Ce Wang, TingTing He, Mengqi Yun, Cuining Feng
With the continuous exploitation of offshore oil and gas, the demand for replacement of damaged casing and recovery of abandoned casing is growing. Based on this demand, a monitoring method for abrasive jet cutting depth of casing pipe is proposed. According to the principle of abrasive jet cutting, the vibration signal produced by abrasive impacting casing is picked up by vibration sensor, and the data acquisition and output of vibration signal are carried out by NI-USB 6361. The upper computer operation display interface of the system is established by Labview, and the cutting state visualization interface is added. The experimental results show that the system can accurately judge the current cutting state and display it in real time at the main interface, which can realize the real-time monitoring of the cutting state of the abrasive jet casing and improve the efficiency of casing recovery in offshore abandoned oil wells.
{"title":"Monitoring method for abrasive jet cutting depth of casing pipes","authors":"Haiyao Wang, Ce Wang, TingTing He, Mengqi Yun, Cuining Feng","doi":"10.1109/ICMSP55950.2022.9859089","DOIUrl":"https://doi.org/10.1109/ICMSP55950.2022.9859089","url":null,"abstract":"With the continuous exploitation of offshore oil and gas, the demand for replacement of damaged casing and recovery of abandoned casing is growing. Based on this demand, a monitoring method for abrasive jet cutting depth of casing pipe is proposed. According to the principle of abrasive jet cutting, the vibration signal produced by abrasive impacting casing is picked up by vibration sensor, and the data acquisition and output of vibration signal are carried out by NI-USB 6361. The upper computer operation display interface of the system is established by Labview, and the cutting state visualization interface is added. The experimental results show that the system can accurately judge the current cutting state and display it in real time at the main interface, which can realize the real-time monitoring of the cutting state of the abrasive jet casing and improve the efficiency of casing recovery in offshore abandoned oil wells.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114151028","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}
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