Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856108
Chengyu Hu, Zaimin Zhong, Junxing Li
Planar inductive position sensor based on PCB has the advantage of low cost and reducing the error caused by winding manufacturing. For inductive sensor with resonant structure, the undesired eddy current caused by conductive shell influences the amplitude and carrier phase of output signals when the sensor is integrated in the motor. This change affects signal demodulation feasibility of the sensor and reduces the signal-to-noise ratio. For this problem, the influence of ferromagnetic materials and eddy current is here discussed. A modified coupling model of multiple coils considering eddy current is proposed to describe a system with modulation characteristics, and the corresponding equivalent circuit equations are established. A prototype is manufactured to verify the performance of the proposed design, and the ferrite is used to suppresses the coupling between the sensor and metallic environment. According to the experimental results, the sensor signal demodulation is achieved properly, and the linear angle estimation realized at a uniform speed.
{"title":"Study on the Effect of Eddy Current for Inductive Angle Sensor with Resonant Structure","authors":"Chengyu Hu, Zaimin Zhong, Junxing Li","doi":"10.1109/ICMA54519.2022.9856108","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856108","url":null,"abstract":"Planar inductive position sensor based on PCB has the advantage of low cost and reducing the error caused by winding manufacturing. For inductive sensor with resonant structure, the undesired eddy current caused by conductive shell influences the amplitude and carrier phase of output signals when the sensor is integrated in the motor. This change affects signal demodulation feasibility of the sensor and reduces the signal-to-noise ratio. For this problem, the influence of ferromagnetic materials and eddy current is here discussed. A modified coupling model of multiple coils considering eddy current is proposed to describe a system with modulation characteristics, and the corresponding equivalent circuit equations are established. A prototype is manufactured to verify the performance of the proposed design, and the ferrite is used to suppresses the coupling between the sensor and metallic environment. According to the experimental results, the sensor signal demodulation is achieved properly, and the linear angle estimation realized at a uniform speed.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125312627","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856051
Defu Zhang, Kangli Wang, Jianfeng Gao, Xiuming Che
In order to improve the intelligent energy efficiency management of ships, evaluate the fuel utilization efficiency of marine diesel engine. In this paper, a fuel consumption model of marine diesel engine based on autoencoder and deep neural network is established, and the autoencoder is used to perform nonlinear dimensionality reduction on the data to obtain more valuable data features, thereby improving the accuracy of the model. The model is verified and compared using the sailing parameters, environmental parameters and fuel consumption of the actual ship during normal sailing. The accuracy rate of the model established in this paper reaches 95.19%, and the results show that the model in this paper can meet the prediction and evaluation analysis of the energy consumption of the marine diesel engine.
{"title":"Autoencoder and Deep Neural Network based Energy Consumption Analysis of Marine Diesel Engine","authors":"Defu Zhang, Kangli Wang, Jianfeng Gao, Xiuming Che","doi":"10.1109/ICMA54519.2022.9856051","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856051","url":null,"abstract":"In order to improve the intelligent energy efficiency management of ships, evaluate the fuel utilization efficiency of marine diesel engine. In this paper, a fuel consumption model of marine diesel engine based on autoencoder and deep neural network is established, and the autoencoder is used to perform nonlinear dimensionality reduction on the data to obtain more valuable data features, thereby improving the accuracy of the model. The model is verified and compared using the sailing parameters, environmental parameters and fuel consumption of the actual ship during normal sailing. The accuracy rate of the model established in this paper reaches 95.19%, and the results show that the model in this paper can meet the prediction and evaluation analysis of the energy consumption of the marine diesel engine.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134433680","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856376
Yang Liu, Shanshan Shi, Yu Song, Qiang Gao, Zeyu Li, Haotian Song, Siyuan Pang, Dong Li
In the field of cognitive neuroscience, mental workload assessment plays an important role. In this work, the power spectral density (PSD) feature of Electroencephalogram (EEG) signals is extracted based on spectrum analysis, and the problems of medium-level and high-level mental workload identification are studied. The classification accuracy of spectral features of each frequency band is evaluated by using AdaBoost, Decision Tree (DT), KNN and support vector machine (SVM). In addition, the features are selected according to the change of relative PSD of each frequency band. The results show that the classification accuracy of the data after feature selection can reach 76.62%, which has been improved with different levels in almost classifier than original data.
{"title":"EEG based Mental Workload Assessment by Power Spectral Density Feature","authors":"Yang Liu, Shanshan Shi, Yu Song, Qiang Gao, Zeyu Li, Haotian Song, Siyuan Pang, Dong Li","doi":"10.1109/ICMA54519.2022.9856376","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856376","url":null,"abstract":"In the field of cognitive neuroscience, mental workload assessment plays an important role. In this work, the power spectral density (PSD) feature of Electroencephalogram (EEG) signals is extracted based on spectrum analysis, and the problems of medium-level and high-level mental workload identification are studied. The classification accuracy of spectral features of each frequency band is evaluated by using AdaBoost, Decision Tree (DT), KNN and support vector machine (SVM). In addition, the features are selected according to the change of relative PSD of each frequency band. The results show that the classification accuracy of the data after feature selection can reach 76.62%, which has been improved with different levels in almost classifier than original data.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129087950","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856335
Peijian Qu, Nan Liu, Zhengpeng Qin, Tianbo Jin, Hongze Fu, Zihao Li, Peisheng Sang
In view of the current situation that the per capita cultivated land in agriculture is insufficient, the yield per mu is reduced and the degree of intelligence in the traditional greenhouse is low, A multi-layer intelligent farm with deep learning algorithm is proposed. Firstly, the overall design of the system is described in detail, including multi-layer greenhouse frame, water, fertilizer and medicine integrated machine, two-dimensional interpolation inspection robot, ventilation fan, fluorescent lamp, circulating water curtain; Secondly, the electrical system and cloud control system are designed. Finally, a deep learning network based on YoloV4-Tiny is installed on Raspberry PI to solve the image recognition problem of rose deficiency and insect pests. After a large number of experimental tests, it is found that the speed and accuracy of using YOLOV4-Tiny are improved compared with using YOLOV4. It solves the common problems of difficult to capture objects and slow recognition of features in other types of greenhouse systems, meets the requirements of ensuring good plant growth in different environments, and ensures the high quality and efficient operation of the greenhouse system.
{"title":"Deep learning based detection of plant nutrient deficiency symptom and design of multi-layer greenhouse system","authors":"Peijian Qu, Nan Liu, Zhengpeng Qin, Tianbo Jin, Hongze Fu, Zihao Li, Peisheng Sang","doi":"10.1109/ICMA54519.2022.9856335","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856335","url":null,"abstract":"In view of the current situation that the per capita cultivated land in agriculture is insufficient, the yield per mu is reduced and the degree of intelligence in the traditional greenhouse is low, A multi-layer intelligent farm with deep learning algorithm is proposed. Firstly, the overall design of the system is described in detail, including multi-layer greenhouse frame, water, fertilizer and medicine integrated machine, two-dimensional interpolation inspection robot, ventilation fan, fluorescent lamp, circulating water curtain; Secondly, the electrical system and cloud control system are designed. Finally, a deep learning network based on YoloV4-Tiny is installed on Raspberry PI to solve the image recognition problem of rose deficiency and insect pests. After a large number of experimental tests, it is found that the speed and accuracy of using YOLOV4-Tiny are improved compared with using YOLOV4. It solves the common problems of difficult to capture objects and slow recognition of features in other types of greenhouse systems, meets the requirements of ensuring good plant growth in different environments, and ensures the high quality and efficient operation of the greenhouse system.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":" 24","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132124290","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856224
Ming Li, Manyi Wang, Longmiao Chen, Liuxuan Wei
Due to the small number of samples of the inter-turn short-circuit fault of the current permanent magnet synchronous motor, and the motor working in a high-noise environment, the collected data contains complicated noise. So first the deep residual shrinkage network is pre-trained on the big data simulation dataset. And then to avoid imbalances between real data sets, GAN network is adopted to generate more datasets in this paper. Based on the aforementioned data set, the pretrained network is proposed to denoise the environment and other noise in the data set. And Spatial Dropout layer into the network is introduced to improve the accuracy and convergence speed of fault diagnosis. Experiments show that by combining GAN and DRSN methods for fault diagnosis of unbalanced samples, disturbances such as datasets and reducing environmental noise can be effectively balanced. The diagnostic accuracy is as high as 97.5%.
{"title":"GAN-DRSN based Inter-turn Short Circuit Fault Diagnosis of PMSM","authors":"Ming Li, Manyi Wang, Longmiao Chen, Liuxuan Wei","doi":"10.1109/ICMA54519.2022.9856224","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856224","url":null,"abstract":"Due to the small number of samples of the inter-turn short-circuit fault of the current permanent magnet synchronous motor, and the motor working in a high-noise environment, the collected data contains complicated noise. So first the deep residual shrinkage network is pre-trained on the big data simulation dataset. And then to avoid imbalances between real data sets, GAN network is adopted to generate more datasets in this paper. Based on the aforementioned data set, the pretrained network is proposed to denoise the environment and other noise in the data set. And Spatial Dropout layer into the network is introduced to improve the accuracy and convergence speed of fault diagnosis. Experiments show that by combining GAN and DRSN methods for fault diagnosis of unbalanced samples, disturbances such as datasets and reducing environmental noise can be effectively balanced. The diagnostic accuracy is as high as 97.5%.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131836064","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856377
Juan Li, Ning Fang
Task allocation is a very important part of multi-agent systems. When assigning tasks to one of the agents in multi-agent systems, many constraints need to be considered to achieve optimal allocation results. In this paper, an improved genetic algorithm (GA) is proposed to solve the multi-agent task allocation with time window constraints. Firstly, the mathematical model of task allocation is established, and the constraint problem of time window is analyzed. The penalty function method is used to deal with the constraint condition. Secondly, the improved Large Neighborhood Search (LNS) is added to the local search to increase the diversity of population, which can make the algorithm easier to jump out of local optimum. Then genetic algorithm is used to solve the multi-agent task allocation problem with time window constraints. Finally, the simulation verifies the optimization performance of the improved algorithm.
{"title":"Improved Genetic Algorithm for Multi-agent Task Allocation with Time Windows","authors":"Juan Li, Ning Fang","doi":"10.1109/ICMA54519.2022.9856377","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856377","url":null,"abstract":"Task allocation is a very important part of multi-agent systems. When assigning tasks to one of the agents in multi-agent systems, many constraints need to be considered to achieve optimal allocation results. In this paper, an improved genetic algorithm (GA) is proposed to solve the multi-agent task allocation with time window constraints. Firstly, the mathematical model of task allocation is established, and the constraint problem of time window is analyzed. The penalty function method is used to deal with the constraint condition. Secondly, the improved Large Neighborhood Search (LNS) is added to the local search to increase the diversity of population, which can make the algorithm easier to jump out of local optimum. Then genetic algorithm is used to solve the multi-agent task allocation problem with time window constraints. Finally, the simulation verifies the optimization performance of the improved algorithm.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132338456","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856178
Xianhui Liu, Luyuan Liu, Jianqiang Li, Fan Yang
The prefabricated concrete structure is conducive to the development of China’s building industrialization. It is one of the important directions for the development of China’s building structure, of which prestressed concrete structure is an important part of the prefabricated concrete structure. The key technology to achieve prestressed concrete is the tension of the prestressed steel strand. The tensioning process includes: 1 The prestressed steel strand penetrates the tension hole of the tensioning equipment. 2 the tensioning equipment continues to tension the prestressed steel strand. Among them, the perforation process of tension has always been manually realized. At present, industrial intelligence includes all walks of life, and equipment related to construction projects also conform to the development of intelligence. The intelligent tensioning robot proposed in this paper is based on the tensile equipment to add a robotic arm, sensors, etc., which can automatically find tensioning holes to facilitate the perforation process when the prestressed ribs are stretched, with the purpose of improving the efficiency of perforation, improving the safety of the tensioning process, and reducing the dependence of tensile construction on labor. In this article, the method of collecting anchor plate position information is introduced, and the modular program of MODBUS communication based on Delta PLC is provided.
{"title":"Application of MODBUS Communication Protocol in Intelligent Prestress Tension Robot","authors":"Xianhui Liu, Luyuan Liu, Jianqiang Li, Fan Yang","doi":"10.1109/ICMA54519.2022.9856178","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856178","url":null,"abstract":"The prefabricated concrete structure is conducive to the development of China’s building industrialization. It is one of the important directions for the development of China’s building structure, of which prestressed concrete structure is an important part of the prefabricated concrete structure. The key technology to achieve prestressed concrete is the tension of the prestressed steel strand. The tensioning process includes: 1 The prestressed steel strand penetrates the tension hole of the tensioning equipment. 2 the tensioning equipment continues to tension the prestressed steel strand. Among them, the perforation process of tension has always been manually realized. At present, industrial intelligence includes all walks of life, and equipment related to construction projects also conform to the development of intelligence. The intelligent tensioning robot proposed in this paper is based on the tensile equipment to add a robotic arm, sensors, etc., which can automatically find tensioning holes to facilitate the perforation process when the prestressed ribs are stretched, with the purpose of improving the efficiency of perforation, improving the safety of the tensioning process, and reducing the dependence of tensile construction on labor. In this article, the method of collecting anchor plate position information is introduced, and the modular program of MODBUS communication based on Delta PLC is provided.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133833628","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9855969
Taiga Kitano, Mina Asari, C. Ishii
In this paper, a laparoscopic surgical robot equipped with a new palpation system which can identify the location of an imitation tumor under use of a trocar was developed based on our previous studies. In robotic surgery, when palpation is performed under use of the trocar, it is difficult to realize force or tactile sense of the touched object because the forceps is affected by contact with the trocar. Therefore, cancelation of an influence of the trocar on the forceps was attempted by using the neural network which was previously trained the influence of the trocar on the forceps. In order to verify an effectiveness of the developed palpation system, location identification experiments were carried out for both longitudinal and lateral directions palpation, in which identification of location of the imitation tumor was attempted for 4 kinds of sample with each different tumor location, respectively. The results showed the effectiveness of the neural network, and identification error of location of the imitation tumor was less than 1mm. In addition, the physical burden added to the operator while performing palpation work using the developed palpation system was evaluated by comparison of the energy expenditure obtained through the analysis of expired gas under the following conditions; (a) only force feedback was conducted, (b) only tactile feedback was conducted, and (c) both force and tactile feedbacks were conducted. The result showed that the physical burden to the operator under the condition (c) was smallest.
{"title":"Development of a Robotic Palpation System and Evaluation of the Burden to an Operator in the Palpation","authors":"Taiga Kitano, Mina Asari, C. Ishii","doi":"10.1109/ICMA54519.2022.9855969","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9855969","url":null,"abstract":"In this paper, a laparoscopic surgical robot equipped with a new palpation system which can identify the location of an imitation tumor under use of a trocar was developed based on our previous studies. In robotic surgery, when palpation is performed under use of the trocar, it is difficult to realize force or tactile sense of the touched object because the forceps is affected by contact with the trocar. Therefore, cancelation of an influence of the trocar on the forceps was attempted by using the neural network which was previously trained the influence of the trocar on the forceps. In order to verify an effectiveness of the developed palpation system, location identification experiments were carried out for both longitudinal and lateral directions palpation, in which identification of location of the imitation tumor was attempted for 4 kinds of sample with each different tumor location, respectively. The results showed the effectiveness of the neural network, and identification error of location of the imitation tumor was less than 1mm. In addition, the physical burden added to the operator while performing palpation work using the developed palpation system was evaluated by comparison of the energy expenditure obtained through the analysis of expired gas under the following conditions; (a) only force feedback was conducted, (b) only tactile feedback was conducted, and (c) both force and tactile feedbacks were conducted. The result showed that the physical burden to the operator under the condition (c) was smallest.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132689185","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856152
Yuezong Wang, Lina Qiu, Haoran Jia
In order to measure the height of local areas on the surface of microstructures, an efficient computational method based on image sequence sharpness retrieval is proposed. First, a small depth-of-field visual system of a few microns is formed using a zoom microscope lens and a high magnification objective lens, which is moved equidistantly along the longitudinal direction to acquire image sequences of the local surface of the silicon sphere. Then, each image sequence is preprocessed to remove some of the blurred interfering images. Finally, the sharpness of the image sequence is calculated. In the first step, the sharpness of the image sequence is calculated by various methods; in the second step, the sharpness data are analyzed and counted to find the location of the sharpest image, and the height of the location is acquired by a Z-axis translation stage with a longitudinal grating ruler to obtain the height of the local area on the surface of the microstructure corresponding to the sharpest image. The experimental results show that the accurate sharpest image in the image sequence can be obtained by using the method in this paper, and the retrieval accuracy reaches 99.40%, which is obviously better than the existing sharpness methods.
{"title":"Estimation of Local Height of Microstructure Based on Depth from Focus Method","authors":"Yuezong Wang, Lina Qiu, Haoran Jia","doi":"10.1109/ICMA54519.2022.9856152","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856152","url":null,"abstract":"In order to measure the height of local areas on the surface of microstructures, an efficient computational method based on image sequence sharpness retrieval is proposed. First, a small depth-of-field visual system of a few microns is formed using a zoom microscope lens and a high magnification objective lens, which is moved equidistantly along the longitudinal direction to acquire image sequences of the local surface of the silicon sphere. Then, each image sequence is preprocessed to remove some of the blurred interfering images. Finally, the sharpness of the image sequence is calculated. In the first step, the sharpness of the image sequence is calculated by various methods; in the second step, the sharpness data are analyzed and counted to find the location of the sharpest image, and the height of the location is acquired by a Z-axis translation stage with a longitudinal grating ruler to obtain the height of the local area on the surface of the microstructure corresponding to the sharpest image. The experimental results show that the accurate sharpest image in the image sequence can be obtained by using the method in this paper, and the retrieval accuracy reaches 99.40%, which is obviously better than the existing sharpness methods.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117158393","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 : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856395
Jiaxing Sun, X. Xiao, Hanling Li
When vehicles work in high dynamic motion, SINS will carry more errors into the GNSS receiver carrier switching for system based on the deep combination of GNSS/SINS. It causes the receiver to lose the loop lock and work in an abnormal state. This paper analyzes the error source of the receiver and deduces the error transmission model of SINS speed auxiliary carrier ring under high dynamic conditions. Then, a method of SINS speed and acceleration aided compensation for carrier loop error is proposed to improve the maximum acceleration range that the carrier loop can bear. The simulation experiment analysis proves that this method is effective, and the maximum acceleration of the carrier can be increased by 4.5g-9g in satellite tracking in different line-of-sight directions.
{"title":"A carrier loop error compensation method for GNSS/SINS deep integration under high dynamics","authors":"Jiaxing Sun, X. Xiao, Hanling Li","doi":"10.1109/ICMA54519.2022.9856395","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856395","url":null,"abstract":"When vehicles work in high dynamic motion, SINS will carry more errors into the GNSS receiver carrier switching for system based on the deep combination of GNSS/SINS. It causes the receiver to lose the loop lock and work in an abnormal state. This paper analyzes the error source of the receiver and deduces the error transmission model of SINS speed auxiliary carrier ring under high dynamic conditions. Then, a method of SINS speed and acceleration aided compensation for carrier loop error is proposed to improve the maximum acceleration range that the carrier loop can bear. The simulation experiment analysis proves that this method is effective, and the maximum acceleration of the carrier can be increased by 4.5g-9g in satellite tracking in different line-of-sight directions.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"22 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116403974","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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