Nuclear safety management is the basic work of nuclear energy development and utilization, and is the guarantee of safe operation of nuclear power plant. Nuclear safety management is a kind of planning, supervision, management, decision-making and information processing activities related to organization, laws and standards, cultural thoughts and the whole life and many aspects of nuclear power plant. In order to improve the ability and efficiency of nuclear safety management and decision-making, artificial intelligence is introduced into nuclear safety management and decision-making. According to the development requirements of nuclear safety management in nuclear power plant, the application method of artificial intelligence in nuclear safety management and decision-making is explored. On this basis, combining artificial intelligence with information management and decision-making technology, an nuclear safety intelligent management and decision-making system(NSIMDS) is proposed, and the framework of nuclear safety intelligent management and decision-making system is designed. This study provides a new approach to solve the problem of nuclear safety management and decision-making, and provides a basis for the development of nuclear safety intelligent management and decision-making system.
{"title":"RESEARCH ON NUCLEAR SAFETY INTELLIGENT MANAGEMENT AND DECISION SYSTEM BASED ON ARTIFICIAL INTELLIGENCE","authors":"G. Zhou, X. Wang","doi":"10.1049/ICP.2021.1321","DOIUrl":"https://doi.org/10.1049/ICP.2021.1321","url":null,"abstract":"Nuclear safety management is the basic work of nuclear energy development and utilization, and is the guarantee of safe operation of nuclear power plant. Nuclear safety management is a kind of planning, supervision, management, decision-making and information processing activities related to organization, laws and standards, cultural thoughts and the whole life and many aspects of nuclear power plant. In order to improve the ability and efficiency of nuclear safety management and decision-making, artificial intelligence is introduced into nuclear safety management and decision-making. According to the development requirements of nuclear safety management in nuclear power plant, the application method of artificial intelligence in nuclear safety management and decision-making is explored. On this basis, combining artificial intelligence with information management and decision-making technology, an nuclear safety intelligent management and decision-making system(NSIMDS) is proposed, and the framework of nuclear safety intelligent management and decision-making system is designed. This study provides a new approach to solve the problem of nuclear safety management and decision-making, and provides a basis for the development of nuclear safety intelligent management and decision-making system.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125080732","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}
Described an measuring system for the use of gauge block measurement. Optical sources of the system is a highly stabilized laser with the wavelength of 532nm, and a 633nm wavelength laser of worse laser monochromaticity. For the use of interference graph capturing, a CCD sensor is introduced into the system. Fractional part of the interference fringes is calculated by image processing procedures. Gauge length is obtained by the interference fringe fraction coincident method. By applying Steger algorithm to extract by fringe centerline, fractional part of the interference fringe order can be accurately obtained. Highly accurate gauge length measurement in relatively simple experiment conditions can be realized with the system, as the demand on laser monochromaticity that interference fringe fraction coincidence method raises can be markedly decreased.
{"title":"OPTIMIZED MEASUREMENT METHOD OF SMALL GAUGE LENGTH USING STEGER ALGORITHM","authors":"Y. Liu, H. Gao, Y. Cheng, Z. Wang, S. Sun","doi":"10.1049/icp.2021.1301","DOIUrl":"https://doi.org/10.1049/icp.2021.1301","url":null,"abstract":"Described an measuring system for the use of gauge block measurement. Optical sources of the system is a highly stabilized laser with the wavelength of 532nm, and a 633nm wavelength laser of worse laser monochromaticity. For the use of interference graph capturing, a CCD sensor is introduced into the system. Fractional part of the interference fringes is calculated by image processing procedures. Gauge length is obtained by the interference fringe fraction coincident method. By applying Steger algorithm to extract by fringe centerline, fractional part of the interference fringe order can be accurately obtained. Highly accurate gauge length measurement in relatively simple experiment conditions can be realized with the system, as the demand on laser monochromaticity that interference fringe fraction coincidence method raises can be markedly decreased.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129090296","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}
There are common faults in planetary gearbox that it is not suitable for shutdown detection at the initial stage or there are many kinds of faults which are not easy to classify accurately. Based on the above reasons, this paper proposes a method combining multi population genetic algorithm (MPGA) and BP neural network. Traditional BP neural network uses a variety of genetic algorithms to optimize the initial weights between layers and the initial threshold corresponding to the single layer network. The traditional method greatly increases the global optimization ability of BP neural network when gradient drops, so we avoid the problem that the local optimal of selecting initial weight and initial threshold. This paper uses the tradition BP neural network and optimized MPGA BP neural network to classify the common faults of planetary gearbox. Then we compare the results of traditional BP neural network and MPGA BP neural network in planetary gearbox fault classification. The results show that: MPGA BP neural network has higher prediction accuracy than traditional BP neural network, so this method can be used for fault classification of planetary gearboxes.
{"title":"RESEARCH ON FAULT DIAGNOSIS OF PLANETARY GEARBOX BASED ON MPGA-BP NEURAL NETWORK","authors":"Y. Fu, Z. Luan, F. Zhou, S. Wang","doi":"10.1049/icp.2021.1324","DOIUrl":"https://doi.org/10.1049/icp.2021.1324","url":null,"abstract":"There are common faults in planetary gearbox that it is not suitable for shutdown detection at the initial stage or there are many kinds of faults which are not easy to classify accurately. Based on the above reasons, this paper proposes a method combining multi population genetic algorithm (MPGA) and BP neural network. Traditional BP neural network uses a variety of genetic algorithms to optimize the initial weights between layers and the initial threshold corresponding to the single layer network. The traditional method greatly increases the global optimization ability of BP neural network when gradient drops, so we avoid the problem that the local optimal of selecting initial weight and initial threshold. This paper uses the tradition BP neural network and optimized MPGA BP neural network to classify the common faults of planetary gearbox. Then we compare the results of traditional BP neural network and MPGA BP neural network in planetary gearbox fault classification. The results show that: MPGA BP neural network has higher prediction accuracy than traditional BP neural network, so this method can be used for fault classification of planetary gearboxes.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131217387","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}
Affected by COVID-19, the demand for nucleic acid detection at home and abroad is gradually increasing, and nucleic acid detection generally requires qualitative analysis of PCR amplification products. At present, the commonly used analysis method of amplification products is agarose gel electrophoresis. In this paper, the whole process of agarose gel production is analyzed, and a fuzzy-neural network PID joint control scheme is proposed for different concentrations of agarose solution reagents to realize different temperature control strategies for different stages of the same concentration solution reagents and different concentration solution reagents. For the glue-making process with the same concentration of reagent, fuzzy control is used to improve the heating power when the temperature difference is large. On the contrary, the BP neural network is used to train the best PID parameter for gelatinizing at the current concentration, so as to realize the temperature control of the whole process of agarose heating and gelatinizing at different concentrations. The sol instrument experimental platform built by this algorithm realizes the glue preparation experiment of different concentration solution and the remelting experiment of the same concentration solution, which achieves the temperature control precision of ±1 ℃ and achieves a better glue preparation effect.
{"title":"RESEARCH ON ACCURATE TEMPERATURE CONTROL ALGORITHM OF AGAROSE GEL SOL APPARATUS FOR NUCLEIC ACID DETECTION","authors":"S. Zhang, X. Lang, A. Tuerhong","doi":"10.1049/icp.2021.1310","DOIUrl":"https://doi.org/10.1049/icp.2021.1310","url":null,"abstract":"Affected by COVID-19, the demand for nucleic acid detection at home and abroad is gradually increasing, and nucleic acid detection generally requires qualitative analysis of PCR amplification products. At present, the commonly used analysis method of amplification products is agarose gel electrophoresis. In this paper, the whole process of agarose gel production is analyzed, and a fuzzy-neural network PID joint control scheme is proposed for different concentrations of agarose solution reagents to realize different temperature control strategies for different stages of the same concentration solution reagents and different concentration solution reagents. For the glue-making process with the same concentration of reagent, fuzzy control is used to improve the heating power when the temperature difference is large. On the contrary, the BP neural network is used to train the best PID parameter for gelatinizing at the current concentration, so as to realize the temperature control of the whole process of agarose heating and gelatinizing at different concentrations. The sol instrument experimental platform built by this algorithm realizes the glue preparation experiment of different concentration solution and the remelting experiment of the same concentration solution, which achieves the temperature control precision of ±1 ℃ and achieves a better glue preparation effect.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132753553","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}
At present, the ship power system when a lot of pressure sensor, the stand or fall of its performance is directly related to the safety of the ship, and the pressure sensor temperature at work usually at about 200 °C. However, the dynamic calibration of pressure sensors by various metering institutions is generally carried out at room temperature, which cannot truly reflect the performance state of pressure sensors in actual use. [1] Therefore, in view of the above practical problems, this paper studies the pressure sensor high temperature dynamic calibration device, and adds a temperature control link to enable it to obtain the temperature response characteristics of the pressure sensor. At the same time, it can simulate the calibration environment under the actual working state of the pressure sensor, so as to achieve the high temperature dynamic calibration of the pressure sensor.[2]
{"title":"RESEARCH ON HIGH TEMPERATURE DYNAMIC CALIBRATION TECHNOLOGY OF SHIP PRESSURE SENSOR","authors":"X. Bai","doi":"10.1049/icp.2021.1340","DOIUrl":"https://doi.org/10.1049/icp.2021.1340","url":null,"abstract":"At present, the ship power system when a lot of pressure sensor, the stand or fall of its performance is directly related to the safety of the ship, and the pressure sensor temperature at work usually at about 200 °C. However, the dynamic calibration of pressure sensors by various metering institutions is generally carried out at room temperature, which cannot truly reflect the performance state of pressure sensors in actual use. [1] Therefore, in view of the above practical problems, this paper studies the pressure sensor high temperature dynamic calibration device, and adds a temperature control link to enable it to obtain the temperature response characteristics of the pressure sensor. At the same time, it can simulate the calibration environment under the actual working state of the pressure sensor, so as to achieve the high temperature dynamic calibration of the pressure sensor.[2]","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114643047","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}
Aiming at the problem of low accuracy of traditional face detection methods for large-volume mask-wearing people during the prevention and control of the new crown pneumonia epidemic, this paper proposes a real-time detection method for large-volume mask-wearing faces based on deep learning. The method uses the overall design of the backbone network, the FPN feature fusion network, the detection network and the parameter optimization method of the algorithm, and completes the model training on the mask-wearing face training set. In the detection process, the NMS algorithm is used to post-process the prediction results to realize multi-scale perception of the input face and improve the detection accuracy of the face wearing a mask. Experimentally verified, the detection accuracy of this method on the mask-wearing face test set is 0.919, and the average of Easy-0.841, Medium-0.802 and Hard-0.600 is obtained on the three subsets of the WIDER FACE test set. Detection accuracy (mAP). Compared with traditional face detection methods, it has universal advantages, and the video inference speed of the method in this paper reaches 55fps, which can meet the task requirements of real-time face detection with large traffic. In addition, the project team has successfully deployed this method to a fully automatic infrared thermal imaging temperature measurement warning system and put it into use in many places in Beijing, which is of great significance to preventing the spread of the epidemic.
{"title":"RESEARCH ON REAL-TIME DETECTION METHOD OF FACE WEARING MASK WITH LARGE TRAFFIC BASED ON DEEP LEARNING","authors":"Y. Meng, N. Liu, Z. Su, X. Wang, H. Wang","doi":"10.1049/icp.2021.1338","DOIUrl":"https://doi.org/10.1049/icp.2021.1338","url":null,"abstract":"Aiming at the problem of low accuracy of traditional face detection methods for large-volume mask-wearing people during the prevention and control of the new crown pneumonia epidemic, this paper proposes a real-time detection method for large-volume mask-wearing faces based on deep learning. The method uses the overall design of the backbone network, the FPN feature fusion network, the detection network and the parameter optimization method of the algorithm, and completes the model training on the mask-wearing face training set. In the detection process, the NMS algorithm is used to post-process the prediction results to realize multi-scale perception of the input face and improve the detection accuracy of the face wearing a mask. Experimentally verified, the detection accuracy of this method on the mask-wearing face test set is 0.919, and the average of Easy-0.841, Medium-0.802 and Hard-0.600 is obtained on the three subsets of the WIDER FACE test set. Detection accuracy (mAP). Compared with traditional face detection methods, it has universal advantages, and the video inference speed of the method in this paper reaches 55fps, which can meet the task requirements of real-time face detection with large traffic. In addition, the project team has successfully deployed this method to a fully automatic infrared thermal imaging temperature measurement warning system and put it into use in many places in Beijing, which is of great significance to preventing the spread of the epidemic.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129724211","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}
The performance of attitude measurement system has a direct impact on the guidance and control accurate of high-spin projectile. Attitude hardware-in-the-loop simulation (HILS) experiment is an important means to verify, evaluate and optimize the performance of attitude measurement system of high spinning projectile. The traditional attitude HILS system transmits the command contained angular rate to the three-axis turntable through a simulation computer with low timing accuracy directly. There is a problem that the transmission rate of command does not match the sampling frequency of the inertial measurement component, and this mismatch will seriously affect the simulation effect of the attitude in a high-spin environment. In order to solve the problem, the instruction transmission method is improved. Firstly, a high-speed data transmission board based on the STM32 ARM core is designed to improve the transmission rate of command. Secondly, the finite impulse response filter (FIR) is used to suppress the noise of the data send from the turntable for improving the accuracy of data and reducing the simulation error of attitude. The results show that the attitude error is less than 0.1°. The HILS system is simple to implement, low cost, high simulation accuracy, and has practical application value.
{"title":"RESEARCH ON THE HARDWARE-IN-THE-LOOP SIMULATION TECHNOLOGY OF THE HIGH SPINNING PROJECTILE'S ATTITUDE","authors":"T. Tian, N. Liu, Z. Su","doi":"10.1049/icp.2021.1311","DOIUrl":"https://doi.org/10.1049/icp.2021.1311","url":null,"abstract":"The performance of attitude measurement system has a direct impact on the guidance and control accurate of high-spin projectile. Attitude hardware-in-the-loop simulation (HILS) experiment is an important means to verify, evaluate and optimize the performance of attitude measurement system of high spinning projectile. The traditional attitude HILS system transmits the command contained angular rate to the three-axis turntable through a simulation computer with low timing accuracy directly. There is a problem that the transmission rate of command does not match the sampling frequency of the inertial measurement component, and this mismatch will seriously affect the simulation effect of the attitude in a high-spin environment. In order to solve the problem, the instruction transmission method is improved. Firstly, a high-speed data transmission board based on the STM32 ARM core is designed to improve the transmission rate of command. Secondly, the finite impulse response filter (FIR) is used to suppress the noise of the data send from the turntable for improving the accuracy of data and reducing the simulation error of attitude. The results show that the attitude error is less than 0.1°. The HILS system is simple to implement, low cost, high simulation accuracy, and has practical application value.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126785532","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}
With the development of the times, robotics technology has gradually been no longer confined to the laboratory, but more integrated into the lives of the public. As a researcher in the field of intelligent science, one should contribute his own contribution to the development of robotics. The visual processing of robots is an important topic in today's science and technology circles, and my team and I have developed a strong interest in this field. For the specific realization of visual processing, we have selected a technology that is very close to the lives of ordinary people-SLAM mapping technology and application for related research. I will use the construction of ROS robot as a starting point to briefly explain how to develop and apply SLAM algorithms on the ROS platform. At the same time, I will explore the derivation of SLAM algorithms-the role and difference of Hector algorithm and Karto algorithm in building maps. By sharing some of my insights on SLAM technology, I believe it can provide some reference for subsequent research.
{"title":"RESEARCH ON SLAM TECHNOLOGY OF ROBOT BASED ON ROS","authors":"Y. Chen, C. Li, Y. Zhou, F. Che, H. Li","doi":"10.1049/ICP.2021.1318","DOIUrl":"https://doi.org/10.1049/ICP.2021.1318","url":null,"abstract":"With the development of the times, robotics technology has gradually been no longer confined to the laboratory, but more integrated into the lives of the public. As a researcher in the field of intelligent science, one should contribute his own contribution to the development of robotics. The visual processing of robots is an important topic in today's science and technology circles, and my team and I have developed a strong interest in this field. For the specific realization of visual processing, we have selected a technology that is very close to the lives of ordinary people-SLAM mapping technology and application for related research. I will use the construction of ROS robot as a starting point to briefly explain how to develop and apply SLAM algorithms on the ROS platform. At the same time, I will explore the derivation of SLAM algorithms-the role and difference of Hector algorithm and Karto algorithm in building maps. By sharing some of my insights on SLAM technology, I believe it can provide some reference for subsequent research.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120883714","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}
Objected to fault diagnosis of planetary gearbox, the research and implementation of classification model on small sample with semi-supervised learning and DPN in this paper is carried out. Firstly, the acceleration sample data for four status of the planetary gearbox are obtained, which are including the normal, internal ring gear fault, sun gear fault and Coupling fault between planetary gear and bearing. And the feature vector is built with characteristic parameters such as average amplitude, kurtosis, root mean square, root square amplitude, form factor, crest factor and margin factor. Then the data is delt with CEEMD method for noise reduction and continually the parameters are computed. Then the vector is as input of DBN and Semi-supervised Learning algorithm to fault diagnosis for planetary gear system. Also the comparison competition are done by using DBN and SVM. The results show that under the small sample data, the method of CEEMD - DBN could be more effective under small sample data. The research could provide an effective method for the diagnosis and classification of small sampling projects.
{"title":"RESEARCH ON FAULT DIAGNOSIS WITH SMALL SAMPLE FOR PLANETARY GEAR SYSTEM WITH SEMI-SUPERVISED LEARNING AND DBN ALGORITHM","authors":"C. Ma, L. Song, S. Wang, Z. Yang","doi":"10.1049/ICP.2021.1305","DOIUrl":"https://doi.org/10.1049/ICP.2021.1305","url":null,"abstract":"Objected to fault diagnosis of planetary gearbox, the research and implementation of classification model on small sample with semi-supervised learning and DPN in this paper is carried out. Firstly, the acceleration sample data for four status of the planetary gearbox are obtained, which are including the normal, internal ring gear fault, sun gear fault and Coupling fault between planetary gear and bearing. And the feature vector is built with characteristic parameters such as average amplitude, kurtosis, root mean square, root square amplitude, form factor, crest factor and margin factor. Then the data is delt with CEEMD method for noise reduction and continually the parameters are computed. Then the vector is as input of DBN and Semi-supervised Learning algorithm to fault diagnosis for planetary gear system. Also the comparison competition are done by using DBN and SVM. The results show that under the small sample data, the method of CEEMD - DBN could be more effective under small sample data. The research could provide an effective method for the diagnosis and classification of small sampling projects.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123721105","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}
The geometrical size of the aeroengine blade profile are mainly measured by coordinate measuring machines. And then the parameters are evaluated by software analysis. Now the software for evaluating blade parameters mainly includes products of companies such as Renishaw, Hexagon, Zeiss, and Geomagic. By using the same coordinate measuring machines (CMM) and different software to carry out the comparative experiment of measuring the parameters of model and actual blade with the contour section, the method for experimenting and comparing with the algorithms of the blade profile parameter is proposed. It expounds the general parameters, general algorithms and the magnitude of data discrepancy of measurement software. The experiment results show that Hexagon and Renishaw are more comprehensive than Zeiss and Geomagic in terms of parameter algorithms. On the other hand, the contour of the actual blade is not perfect curve, which leads to errors in measurement, so that the deviation of the evaluation value of the parameters on the actual blade is much larger than that on the model.
{"title":"APPLICATION RESEARCH ON EVALUATION OF AERO-ENGINE BLADE PROFILE PARAMETERS","authors":"T. Pan, X. He, G. Wu, X. He, X. L. Xu","doi":"10.1049/icp.2021.1314","DOIUrl":"https://doi.org/10.1049/icp.2021.1314","url":null,"abstract":"The geometrical size of the aeroengine blade profile are mainly measured by coordinate measuring machines. And then the parameters are evaluated by software analysis. Now the software for evaluating blade parameters mainly includes products of companies such as Renishaw, Hexagon, Zeiss, and Geomagic. By using the same coordinate measuring machines (CMM) and different software to carry out the comparative experiment of measuring the parameters of model and actual blade with the contour section, the method for experimenting and comparing with the algorithms of the blade profile parameter is proposed. It expounds the general parameters, general algorithms and the magnitude of data discrepancy of measurement software. The experiment results show that Hexagon and Renishaw are more comprehensive than Zeiss and Geomagic in terms of parameter algorithms. On the other hand, the contour of the actual blade is not perfect curve, which leads to errors in measurement, so that the deviation of the evaluation value of the parameters on the actual blade is much larger than that on the model.","PeriodicalId":337028,"journal":{"name":"The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)","volume":"2020 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130182544","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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