Pub Date : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101554
Sun Jiang, Xing Hongyan, Wu Jiajia
In order to improve the detection accuracy of sea clutter wavelet prediction model further, a sea clutter hybrid denosing algorithm based on variational modal decomposition (VMD) is proposed. The VMD is adopted to decompose the sea clutter signal into a finite number of intrinsic modal functions (IMF) with limited bandwidths of different center frequencies. Then, we analyze the auto-correlation property of the decomposed signal and perform wavelet hard threshold filtering on the modal component with noise characteristics. Reconstructing the filtered component and the residual component to obtain a denosied signal. The sea clutter prediction model based on LSSVM is adopted to verify the denosing result, and the denosing result is evaluated by comparing the predicted root mean square error (RMSE) before and after denosing. Comparing the prediction results of the two groups of experiments, it is not difficult to find that the predicted RMSE after denosing is 0.00055, which is two orders of magnitude lower than the predicted RMS error before denosing (0.0125).
{"title":"Sea clutter hybrid denoising algorithm based on VMD","authors":"Sun Jiang, Xing Hongyan, Wu Jiajia","doi":"10.1109/ICEMI46757.2019.9101554","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101554","url":null,"abstract":"In order to improve the detection accuracy of sea clutter wavelet prediction model further, a sea clutter hybrid denosing algorithm based on variational modal decomposition (VMD) is proposed. The VMD is adopted to decompose the sea clutter signal into a finite number of intrinsic modal functions (IMF) with limited bandwidths of different center frequencies. Then, we analyze the auto-correlation property of the decomposed signal and perform wavelet hard threshold filtering on the modal component with noise characteristics. Reconstructing the filtered component and the residual component to obtain a denosied signal. The sea clutter prediction model based on LSSVM is adopted to verify the denosing result, and the denosing result is evaluated by comparing the predicted root mean square error (RMSE) before and after denosing. Comparing the prediction results of the two groups of experiments, it is not difficult to find that the predicted RMSE after denosing is 0.00055, which is two orders of magnitude lower than the predicted RMS error before denosing (0.0125).","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134361134","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101447
Du Enwu, Jiang Jian, L. Jiannan, Zou Hai
-There will be great number of settleable residues during shooting of firearms. In traditional smoke chamber-detection, taking smoke chambers before and after shooting as the data test environment may affect the detection result. Considering this, we propose to measure data in a smoke-free environment created by automatically discharging smoke in detection system after analyzing the impact of settable residues on detection results, which may effectively avoid such impact. Results of detection of transmittance of muzzle smokes of 5.8mm and 7.62mm ordinary guns indicate that average efficiency of transmittance of improved detection method is improved by 3.04% and 3.09%, standard deviation decreased by 0.0117 and 0.0079 respectively compared with traditional detection method, with improved reliability, reduced detection time and significantly enhanced detection efficiency.
{"title":"Methods and research on detection of transmittance of muzzle smoke","authors":"Du Enwu, Jiang Jian, L. Jiannan, Zou Hai","doi":"10.1109/ICEMI46757.2019.9101447","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101447","url":null,"abstract":"-There will be great number of settleable residues during shooting of firearms. In traditional smoke chamber-detection, taking smoke chambers before and after shooting as the data test environment may affect the detection result. Considering this, we propose to measure data in a smoke-free environment created by automatically discharging smoke in detection system after analyzing the impact of settable residues on detection results, which may effectively avoid such impact. Results of detection of transmittance of muzzle smokes of 5.8mm and 7.62mm ordinary guns indicate that average efficiency of transmittance of improved detection method is improved by 3.04% and 3.09%, standard deviation decreased by 0.0117 and 0.0079 respectively compared with traditional detection method, with improved reliability, reduced detection time and significantly enhanced detection efficiency.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129005459","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101840
Z. Guangquan, Wu Kankan, Gao Yong-cheng, L. Yongmei, Hu Cong
In recent years, machine learning technology is widely used in the field of fault diagnosis for bearings. Although these methods usually work well, the following defects still exist when they are dealing with large amount of fault data: (1) feature extraction methods need to rely on expertise or signal processing technologies. Therefore, there is a lack of a feature extraction method that is common to different diagnostic problems; (2) shallow models can't learn more complex mapping relationships well; (3) traditional intelligent diagnostic methods are usually computationally intensive and slow in convergence. Inspired by the Auto-encoder’s (AE) feature extraction capability and fast training speed of the Extreme Learning Machine (ELM), a new fault diagnosis method for bearings based on Extreme Learning Machine-Autoencoder (ELM-AE) is proposed in this paper. With its automatic feature extraction capability and very efficient learning strategy, the raw vibration signals of bearings are directly sent to the model without any manual feature extraction for fault diagnosis, which overcomes the above drawbacks. The experimental results on CWRU bearing dataset show that the proposed method takes into account both diagnostic accuracy and time efficiency. Compared with existing literatures, our proposed method obtains superior accuracy.
{"title":"Bearing fault diagnosis from raw vibration signals using multi-layer extreme learning machine","authors":"Z. Guangquan, Wu Kankan, Gao Yong-cheng, L. Yongmei, Hu Cong","doi":"10.1109/ICEMI46757.2019.9101840","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101840","url":null,"abstract":"In recent years, machine learning technology is widely used in the field of fault diagnosis for bearings. Although these methods usually work well, the following defects still exist when they are dealing with large amount of fault data: (1) feature extraction methods need to rely on expertise or signal processing technologies. Therefore, there is a lack of a feature extraction method that is common to different diagnostic problems; (2) shallow models can't learn more complex mapping relationships well; (3) traditional intelligent diagnostic methods are usually computationally intensive and slow in convergence. Inspired by the Auto-encoder’s (AE) feature extraction capability and fast training speed of the Extreme Learning Machine (ELM), a new fault diagnosis method for bearings based on Extreme Learning Machine-Autoencoder (ELM-AE) is proposed in this paper. With its automatic feature extraction capability and very efficient learning strategy, the raw vibration signals of bearings are directly sent to the model without any manual feature extraction for fault diagnosis, which overcomes the above drawbacks. The experimental results on CWRU bearing dataset show that the proposed method takes into account both diagnostic accuracy and time efficiency. Compared with existing literatures, our proposed method obtains superior accuracy.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131602800","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101518
Wang Zhenya, Yong Yingqiong, Zheng Benchang, Lu Ying
Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limitation of spatial information bandwidth and initial information, few shot learning based incremental fault diagnosis provides a new way for on-line fault detection of on-orbit equipment. In this paper, an incremental fault diagnosis method for on-orbit equipment based on cut edge weight estimation is proposed by combining the framework of collaborative learning and the idea of graph theory data editing. The experiment of applying above method to space actuating system was also carried out.
{"title":"Incremental fault diagnosis method for space on-orbit equipment","authors":"Wang Zhenya, Yong Yingqiong, Zheng Benchang, Lu Ying","doi":"10.1109/ICEMI46757.2019.9101518","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101518","url":null,"abstract":"Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limitation of spatial information bandwidth and initial information, few shot learning based incremental fault diagnosis provides a new way for on-line fault detection of on-orbit equipment. In this paper, an incremental fault diagnosis method for on-orbit equipment based on cut edge weight estimation is proposed by combining the framework of collaborative learning and the idea of graph theory data editing. The experiment of applying above method to space actuating system was also carried out.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122411779","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101656
Zhang Bo, L. Jun, Liu Li, Gao Qi, Cui Xiuhai
With the increasing demand for test data and increasing timeliness requirement of the satellite on-orbit test system, the traditional satellite on-orbit test system exposes the problem of insufficient rate, low efficiency and large software resource overhead during data transmission between units in the system. Aiming at problem stand above, this paper proposes a high-speed transmission channel based on serial Rapid IO (SRIO) protocol to realize data transmission between units of the system. The proposed high-speed data transmission channel uses SRIO protocol and DMA technology, based on the ZYNQ MPSoC, to design the data transmission channel between the information processing unit and the data storage-unit. Finally, we tested two Xilinx Zynq-7000 SoC Devices, and built 4 SRIO channels between boards developed by the laboratory. Under the condition of less software resources, the single-channel transmission speed can reach 4.4Gb/s and the transmission efficiency is over 88%. The result indicates that the proposed channel has the characteristics of high speed, high efficiency, light weight and high reliability.
{"title":"Design of high-speed information channel for satellite test based on serial Rapid I/O","authors":"Zhang Bo, L. Jun, Liu Li, Gao Qi, Cui Xiuhai","doi":"10.1109/ICEMI46757.2019.9101656","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101656","url":null,"abstract":"With the increasing demand for test data and increasing timeliness requirement of the satellite on-orbit test system, the traditional satellite on-orbit test system exposes the problem of insufficient rate, low efficiency and large software resource overhead during data transmission between units in the system. Aiming at problem stand above, this paper proposes a high-speed transmission channel based on serial Rapid IO (SRIO) protocol to realize data transmission between units of the system. The proposed high-speed data transmission channel uses SRIO protocol and DMA technology, based on the ZYNQ MPSoC, to design the data transmission channel between the information processing unit and the data storage-unit. Finally, we tested two Xilinx Zynq-7000 SoC Devices, and built 4 SRIO channels between boards developed by the laboratory. Under the condition of less software resources, the single-channel transmission speed can reach 4.4Gb/s and the transmission efficiency is over 88%. The result indicates that the proposed channel has the characteristics of high speed, high efficiency, light weight and high reliability.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122901412","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101494
Shi Xin, Tian Wenbin
The energy consumption of industrial buildings continues to increase. Improving the energy efficiency of buildings and effectively reducing energy consumption are urgent problems to be solved. In order to effectively evaluate the energy consumption of industrial buildings, this paper proposes a method for constructing the indoor energy flow state model of industrial buildings. The state of energy flow in the building is described by the state of temperature, humidity and wind speed. The control space adopts PCA, and the global space adopts KPCA to extract energy flow state characteristic parameters, then K-means cluster it. The clustering areas are defined as energy nodes, then extracted fusion points and stable points from energy nodes to describe energy flow state. Comparative experiments were carried out with the original temperature and humidity monitoring model of industrial buildings. Based on CFD, the model ensure the accuracy, the effective coverage is increased by 20%, and the amount of information feedback is reduced by 55%.
{"title":"An energy node-based modelling method for indoor energy flow state of industrial buildings","authors":"Shi Xin, Tian Wenbin","doi":"10.1109/ICEMI46757.2019.9101494","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101494","url":null,"abstract":"The energy consumption of industrial buildings continues to increase. Improving the energy efficiency of buildings and effectively reducing energy consumption are urgent problems to be solved. In order to effectively evaluate the energy consumption of industrial buildings, this paper proposes a method for constructing the indoor energy flow state model of industrial buildings. The state of energy flow in the building is described by the state of temperature, humidity and wind speed. The control space adopts PCA, and the global space adopts KPCA to extract energy flow state characteristic parameters, then K-means cluster it. The clustering areas are defined as energy nodes, then extracted fusion points and stable points from energy nodes to describe energy flow state. Comparative experiments were carried out with the original temperature and humidity monitoring model of industrial buildings. Based on CFD, the model ensure the accuracy, the effective coverage is increased by 20%, and the amount of information feedback is reduced by 55%.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123028952","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101803
L. Liwei, Zhao Zijun, Xu Qian, Wu Liang
Temperature variation will lead to expansion or contraction of different components in the optical system of aerospace camera and change of refractive index of optical materials, which will bring changes in parameters in the optical system, thus affecting the camera. For temperature variation and the parameters of the theoretical study is less, in this paper, through establishing the model of image point drift is put forward based on the change of temperature change and the lens optical system parameters of BP neural network model, parameter variation within the temperature variation and the fitting results show that the model can be estimated by temperature variation parameter variation. hange.
{"title":"Study on BP neural network model of optical system parameters based on temperature variation","authors":"L. Liwei, Zhao Zijun, Xu Qian, Wu Liang","doi":"10.1109/ICEMI46757.2019.9101803","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101803","url":null,"abstract":"Temperature variation will lead to expansion or contraction of different components in the optical system of aerospace camera and change of refractive index of optical materials, which will bring changes in parameters in the optical system, thus affecting the camera. For temperature variation and the parameters of the theoretical study is less, in this paper, through establishing the model of image point drift is put forward based on the change of temperature change and the lens optical system parameters of BP neural network model, parameter variation within the temperature variation and the fitting results show that the model can be estimated by temperature variation parameter variation. hange.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124036059","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101629
Pan Jihui
With the development of high altitude long endurance UAV, Flight Control System in high altitude long endurance UAV must have so strong failure-tolerant ability that it can improve the whole system reliability. Using redundancy technique can extremely improve failure-tolerant and reliability of flight control system. Compared among civil and military aircraft and UAV, the architectures and redundancy management of fault-tolerant flight control computer (FCC) systems are introduced. Then, give a new architectures and redundancy management of fault-tolerant FCC systems for high altitude long endurance UAV. The experimental results show that the system meets the UAV’s demand of high reliability, low cost and good expansibility, maximize the utilization of system resources and effectively improve the fault tolerant capability of airborne computer and the reliability of sensor subsystem. With fault injection test method, the results show that the fault tolerant methods improve fault detection rate and fault isolation rate.
{"title":"Research on fault-tolerant flight control computer for unmanned air vehicle","authors":"Pan Jihui","doi":"10.1109/ICEMI46757.2019.9101629","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101629","url":null,"abstract":"With the development of high altitude long endurance UAV, Flight Control System in high altitude long endurance UAV must have so strong failure-tolerant ability that it can improve the whole system reliability. Using redundancy technique can extremely improve failure-tolerant and reliability of flight control system. Compared among civil and military aircraft and UAV, the architectures and redundancy management of fault-tolerant flight control computer (FCC) systems are introduced. Then, give a new architectures and redundancy management of fault-tolerant FCC systems for high altitude long endurance UAV. The experimental results show that the system meets the UAV’s demand of high reliability, low cost and good expansibility, maximize the utilization of system resources and effectively improve the fault tolerant capability of airborne computer and the reliability of sensor subsystem. With fault injection test method, the results show that the fault tolerant methods improve fault detection rate and fault isolation rate.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121279683","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101433
Zhao Dongfang, Kang Wenjing, Li Tao, Li Gongliang
With the rapid development of the automobile industry, the demand for autonomous driving becomes more and more urgent, and the traffic sign recognition technology in autonomous driving is an indispensable technology. This paper proposes a GoogLeNet based convolutional neural network for traffic signs. This convolutional neural network improves each of the underlying Inception Modules and adds the Batch Normalization layer, effectively avoiding over-fitting of the network. We use a sparse structure that conforms to the Hebbain principle to reduce the parameters and improve the generalization ability of the network, which can extract the features of the image more accurately. Meanwhile, the network also reduces the parameters of the full connection layer by 20 times through the continuous two-layer pooling layer, which greatly speeds up the network training. Finally, the network is trained using the GTSRB data set and the classification accuracy rate can reach 98%. At the same time, we also verified the validity of the network on the MNIST dataset and the pneumonia dataset. The classification accuracy rate can reach 100% on the above two datasets. Experimental results on the above data sets show the validity of the convolutional neural network.
{"title":"Traffic sign classification network using inception module","authors":"Zhao Dongfang, Kang Wenjing, Li Tao, Li Gongliang","doi":"10.1109/ICEMI46757.2019.9101433","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101433","url":null,"abstract":"With the rapid development of the automobile industry, the demand for autonomous driving becomes more and more urgent, and the traffic sign recognition technology in autonomous driving is an indispensable technology. This paper proposes a GoogLeNet based convolutional neural network for traffic signs. This convolutional neural network improves each of the underlying Inception Modules and adds the Batch Normalization layer, effectively avoiding over-fitting of the network. We use a sparse structure that conforms to the Hebbain principle to reduce the parameters and improve the generalization ability of the network, which can extract the features of the image more accurately. Meanwhile, the network also reduces the parameters of the full connection layer by 20 times through the continuous two-layer pooling layer, which greatly speeds up the network training. Finally, the network is trained using the GTSRB data set and the classification accuracy rate can reach 98%. At the same time, we also verified the validity of the network on the MNIST dataset and the pneumonia dataset. The classification accuracy rate can reach 100% on the above two datasets. Experimental results on the above data sets show the validity of the convolutional neural network.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128722420","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 : 2019-11-01DOI: 10.1109/ICEMI46757.2019.9101519
Guo Siming, Wan PeiWei, Wang Ji, Wu Jinjie, Zhang Jian
Absolute measurement of high fluence rate X-ray dose was required in thermonuclear fusion research and plasma diagnostic measurement. An ionization chamber used for the reproducibility of air-kerma in high fluence rate X-rays was designed, and the monoenergetic X-rays of (6-20) keV were absolutely measured on Beijing Synchrotron Radiation Facility. The air attenuation and recombination correction factors of the free-air ionization chamber were obtained experimentally. Thus, the air-kerma for the $(6 sim 20)$ keV monoenergetic X-rays can be determined.
{"title":"Measurement of air attenuation and recombination correction factors in synchrotron radiation X-rays","authors":"Guo Siming, Wan PeiWei, Wang Ji, Wu Jinjie, Zhang Jian","doi":"10.1109/ICEMI46757.2019.9101519","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101519","url":null,"abstract":"Absolute measurement of high fluence rate X-ray dose was required in thermonuclear fusion research and plasma diagnostic measurement. An ionization chamber used for the reproducibility of air-kerma in high fluence rate X-rays was designed, and the monoenergetic X-rays of (6-20) keV were absolutely measured on Beijing Synchrotron Radiation Facility. The air attenuation and recombination correction factors of the free-air ionization chamber were obtained experimentally. Thus, the air-kerma for the $(6 sim 20)$ keV monoenergetic X-rays can be determined.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116719864","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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