Pub Date : 2022-02-01DOI: 10.1109/ICTech55460.2022.00082
Zhe Sun, H. Yang
In order to help beginners to quickly understand and participate in skiing, researchers put forward the design of skiing simulator during the design and research, which includes safety protection, sports training, virtual simulation of these three aspects. VR virtual simulation system can accurately simulate the scene of skiing training, so that the training personnel can feel the real charm of skiing in the participation. The sports training system contains a number of institutions, which can maximize the simulation of skiing posture, and the safety protection system can provide comprehensive protection to participants. The effective integration of Will technology and trainer can help people simulate multi-dimensional skiing posture in real skiing scene experience, and promote them to have a real experience during simulated training. In this paper, on the basis of understanding the design experience and composition of multi-sensor, the attitude training simulator of ski machine with multi-sensor as the core is deeply studied, so as to build a good simulation for skiing participants. The final results show that the attitude training simulator based on multi-sensor can show positive advantages in practical application.
{"title":"Development of a Multi-Sensor Based Ski Machine Attitude Training Simulator","authors":"Zhe Sun, H. Yang","doi":"10.1109/ICTech55460.2022.00082","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00082","url":null,"abstract":"In order to help beginners to quickly understand and participate in skiing, researchers put forward the design of skiing simulator during the design and research, which includes safety protection, sports training, virtual simulation of these three aspects. VR virtual simulation system can accurately simulate the scene of skiing training, so that the training personnel can feel the real charm of skiing in the participation. The sports training system contains a number of institutions, which can maximize the simulation of skiing posture, and the safety protection system can provide comprehensive protection to participants. The effective integration of Will technology and trainer can help people simulate multi-dimensional skiing posture in real skiing scene experience, and promote them to have a real experience during simulated training. In this paper, on the basis of understanding the design experience and composition of multi-sensor, the attitude training simulator of ski machine with multi-sensor as the core is deeply studied, so as to build a good simulation for skiing participants. The final results show that the attitude training simulator based on multi-sensor can show positive advantages in practical application.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133293248","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00027
Mingrui Sha, Zhenhao Gu
With the rapid development of electric power industry and the acceleration of the marketization process of electric power system reform, the importance of electric power safety production is more prominent. The traditional electronic fence mostly adopts radio frequency or infrared monitoring, which cannot be accurately identified. False positives will be generated when animals or inanimate objects enter the monitoring area. This paper aims to use interval capture method to extract feature through HOG, PCA and other feature extraction methods in real time, and then use SVM classifier to discriminate for the transgression detection system in key monitoring areas of power grid. In order to achieve the key areas of personnel crossing the precise monitoring.
{"title":"Research and Application of HOG Feature Based Power Grid Key Area Out of Bounds Detection","authors":"Mingrui Sha, Zhenhao Gu","doi":"10.1109/ICTech55460.2022.00027","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00027","url":null,"abstract":"With the rapid development of electric power industry and the acceleration of the marketization process of electric power system reform, the importance of electric power safety production is more prominent. The traditional electronic fence mostly adopts radio frequency or infrared monitoring, which cannot be accurately identified. False positives will be generated when animals or inanimate objects enter the monitoring area. This paper aims to use interval capture method to extract feature through HOG, PCA and other feature extraction methods in real time, and then use SVM classifier to discriminate for the transgression detection system in key monitoring areas of power grid. In order to achieve the key areas of personnel crossing the precise monitoring.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129844825","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00042
Ning Zhang, Fangjian Shang, Xin Li, Wenjun Zhu
At present, the application of artificial intelligence technology to test data generation has become one of the research hotspots. However, its research method is not suitable for the field of electric power Internet of Things. This paper analyzes the specific functions of the unified IOT management platform in the power IOT, and applies ant colony algorithm to realize the automatic generation of test data. so as to solve the problems of time-consuming and nonstandard manual data compilation by users and improve the test efficiency of the system.
{"title":"Research on Test Data Generation Method of IOT Management Platform Based on Ant Colony Algorithm","authors":"Ning Zhang, Fangjian Shang, Xin Li, Wenjun Zhu","doi":"10.1109/ICTech55460.2022.00042","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00042","url":null,"abstract":"At present, the application of artificial intelligence technology to test data generation has become one of the research hotspots. However, its research method is not suitable for the field of electric power Internet of Things. This paper analyzes the specific functions of the unified IOT management platform in the power IOT, and applies ant colony algorithm to realize the automatic generation of test data. so as to solve the problems of time-consuming and nonstandard manual data compilation by users and improve the test efficiency of the system.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132358154","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00068
Zhixin Jing, Rui Fan, Wan-zhao Liu, Yan Shi, Fengjiu Yang
With the rapid development of China's data industry, power big data has gradually become the main object of national construction and innovation. Especially in the promotion of sensors and intelligent equipment and so on, more and more electric power data sources, the type characteristics shown more complex, the use of big data related to technology, the hidden data information, not only can improve the efficiency of the power system, can also provide effective basis for warehouse management. As the main management tool for power big data, power load prediction can guarantee the power system and power supply quality on the one hand, and can provide more effective information by warehouse management on the other hand, and the actual prediction results directly affect the accuracy of the whole system operation. Therefore, on the basis of understanding the development trend of power big data, this paper takes data mining technology as the core to improve and explore the power load prediction, so as to ensure the accuracy and effectiveness of online tools and data management of warehouse management.
{"title":"Evaluation of Online Tool Data Management for Warehouse Management for Power Big Data","authors":"Zhixin Jing, Rui Fan, Wan-zhao Liu, Yan Shi, Fengjiu Yang","doi":"10.1109/ICTech55460.2022.00068","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00068","url":null,"abstract":"With the rapid development of China's data industry, power big data has gradually become the main object of national construction and innovation. Especially in the promotion of sensors and intelligent equipment and so on, more and more electric power data sources, the type characteristics shown more complex, the use of big data related to technology, the hidden data information, not only can improve the efficiency of the power system, can also provide effective basis for warehouse management. As the main management tool for power big data, power load prediction can guarantee the power system and power supply quality on the one hand, and can provide more effective information by warehouse management on the other hand, and the actual prediction results directly affect the accuracy of the whole system operation. Therefore, on the basis of understanding the development trend of power big data, this paper takes data mining technology as the core to improve and explore the power load prediction, so as to ensure the accuracy and effectiveness of online tools and data management of warehouse management.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132319858","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00091
Jiaming Zhang, Anying Chai
In recent years, the deep integration of a new generation of information technology and manufacturing technology as an intelligent manufacturing model. It triggers a new round of manufacturing transformation. As an important carrier to realize intelligent manufacturing, smart factory realizes the intelligence of the production process by building intelligent production systems and networked distribution production facilities. It further improves production efficiency. However, the traditional communication system based on C/S architecture cannot realize the real-time transmission of data generated by much industrial equipment and sensor devices in the smart factory. This situation further leads to increased time delay and reduced data transmission efficiency for various types of data such as device status data, sensing data, audio, and video data, etc. The system is unable to monitor and manage each device in real-time. This paper proposes a distributed communication model for smart factories. According to the actual production requirements, we design the general architecture of the distributed communication model for smart factories. A message agent is used to implement the publish/subscribe mechanism of the distributed communication model, which has the advantages of low power consumption, security, reliability, and scalability. Meanwhile, a dynamic awareness scheduling algorithm based on WFQ (DAWFQ) is proposed. According to the length of the queue backlog, the algorithm dynamically adjusts the weights of real-time data streams and non-real-time data streams. It enables the model to send real-time data in priority and meet the demand for reliable transmission of real-time data. The experimental results show that the model designed in this paper can complete the distributed communication of the smart factory network. It shows good performance in terms of both real-time and reliability. The model ensures the real-time and reliable demand of smart factory devices under the constrained network resources and improves the quality of service of the whole communication network.
{"title":"Modeling Distributed Communication for Smart Factory","authors":"Jiaming Zhang, Anying Chai","doi":"10.1109/ICTech55460.2022.00091","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00091","url":null,"abstract":"In recent years, the deep integration of a new generation of information technology and manufacturing technology as an intelligent manufacturing model. It triggers a new round of manufacturing transformation. As an important carrier to realize intelligent manufacturing, smart factory realizes the intelligence of the production process by building intelligent production systems and networked distribution production facilities. It further improves production efficiency. However, the traditional communication system based on C/S architecture cannot realize the real-time transmission of data generated by much industrial equipment and sensor devices in the smart factory. This situation further leads to increased time delay and reduced data transmission efficiency for various types of data such as device status data, sensing data, audio, and video data, etc. The system is unable to monitor and manage each device in real-time. This paper proposes a distributed communication model for smart factories. According to the actual production requirements, we design the general architecture of the distributed communication model for smart factories. A message agent is used to implement the publish/subscribe mechanism of the distributed communication model, which has the advantages of low power consumption, security, reliability, and scalability. Meanwhile, a dynamic awareness scheduling algorithm based on WFQ (DAWFQ) is proposed. According to the length of the queue backlog, the algorithm dynamically adjusts the weights of real-time data streams and non-real-time data streams. It enables the model to send real-time data in priority and meet the demand for reliable transmission of real-time data. The experimental results show that the model designed in this paper can complete the distributed communication of the smart factory network. It shows good performance in terms of both real-time and reliability. The model ensures the real-time and reliable demand of smart factory devices under the constrained network resources and improves the quality of service of the whole communication network.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114973174","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00040
Conglei Lv, Xiwang Li, Wen Wang
With the development of network scale, network technology affects every aspect of people's life. It is of great significance to detect network intrusion. Traditional research is mostly based on open data sets, the open data sets lack timeliness, and the validity of the research results is unknown. Based on the previous research, this paper proposed a novel intrusion detection method based on convolutional neural network. Firstly, real abnormal data packets were obtained by building a network environment and using real network attack tools. Second, abnormal data packets were used to generate features. Furthermore those futures are transformed into gray images for visual analysis. In order to evaluate effectiveness and superiority of proposed method, several evaluating indicators were introduced. The experimental result shows that precision, recall and F1 value of the proposed method reached 0.99, 0.99 and 0.99 respectively, which were all superior to the traditional machine learning methods.
{"title":"Application of Convolution Neural Network in Network Abnormal Traffic Detection","authors":"Conglei Lv, Xiwang Li, Wen Wang","doi":"10.1109/ICTech55460.2022.00040","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00040","url":null,"abstract":"With the development of network scale, network technology affects every aspect of people's life. It is of great significance to detect network intrusion. Traditional research is mostly based on open data sets, the open data sets lack timeliness, and the validity of the research results is unknown. Based on the previous research, this paper proposed a novel intrusion detection method based on convolutional neural network. Firstly, real abnormal data packets were obtained by building a network environment and using real network attack tools. Second, abnormal data packets were used to generate features. Furthermore those futures are transformed into gray images for visual analysis. In order to evaluate effectiveness and superiority of proposed method, several evaluating indicators were introduced. The experimental result shows that precision, recall and F1 value of the proposed method reached 0.99, 0.99 and 0.99 respectively, which were all superior to the traditional machine learning methods.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125089426","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00108
Zhimin He, Aidi Dong, Jianhong Pan
With the rapid development of the digital economy, combined with changes in the company's internal and external development situations, the digitization of grid companies is extending from supporting management digitization to serving energy Internet digitization applications, extending from serving internally to internally and externally, and helping to improve quality and efficiency. To empower emerging industries to upgrade and extend, the digital construction of power grid companies will become an important core task for the construction of the energy Internet. This article is based on the quantitative control dynamic technology of digital economic benefit evaluation, through the analysis of business types, project cycles., new business development, etc., using big data analysis., data governance, machine learning and other technologies to capture, integrate, and analyze project data, To form an architectural feature model, to screen and effectively correlate digital economic benefit evaluation indicators, and finally complete the construction of a dynamic analysis model for digital economic benefit evaluation intelligent quantitative control.
{"title":"Research on Dynamic Technology of Digital Benefit Intelligent Quantitative Control","authors":"Zhimin He, Aidi Dong, Jianhong Pan","doi":"10.1109/ICTech55460.2022.00108","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00108","url":null,"abstract":"With the rapid development of the digital economy, combined with changes in the company's internal and external development situations, the digitization of grid companies is extending from supporting management digitization to serving energy Internet digitization applications, extending from serving internally to internally and externally, and helping to improve quality and efficiency. To empower emerging industries to upgrade and extend, the digital construction of power grid companies will become an important core task for the construction of the energy Internet. This article is based on the quantitative control dynamic technology of digital economic benefit evaluation, through the analysis of business types, project cycles., new business development, etc., using big data analysis., data governance, machine learning and other technologies to capture, integrate, and analyze project data, To form an architectural feature model, to screen and effectively correlate digital economic benefit evaluation indicators, and finally complete the construction of a dynamic analysis model for digital economic benefit evaluation intelligent quantitative control.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295304","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00055
Ying Gao, Xiaojun Xia
In the industrial production process, the rolling bearing failures of huge mechanical equipment such as CNC machine tools frequently occur, which seriously affects the production performance and service life of the machine tools. In order to identify the types of faults in rolling bearings and improve the safety of the equipment, this paper presents a fault diagnosis method on account of an improved Convolution Neural Network (CNN). The improved CNN model is to add a convolutional layer before the fully connected layer, after several convolutional layers and several pooling layers, and use an improved stochastic gradient descent training algorithm with momentum to speed up the training speed to enhance the serviceability of the model. Traditional fault diagnosis methods are time-consuming, high in labor costs and low in work efficiency. The method in this paper improves the intelligence of the rolling bearing of CNC machine tools fault diagnosis process, improves the correctness of fault diagnosis, and adapts to the characteristics of big data fault diagnosis. Finally, the data set of Case Western Reserve University's rolling bearing database is used for experimental verification. The experimental results reveal that this method has a high recognition accuracy rate for various types and severity of rolling bearing faults, and has good practicability and application prospect.
{"title":"A Fault Diagnosis Method of Rolling Bearing of CNC Machine Tool Based on Improved Convolutional Neural Network","authors":"Ying Gao, Xiaojun Xia","doi":"10.1109/ICTech55460.2022.00055","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00055","url":null,"abstract":"In the industrial production process, the rolling bearing failures of huge mechanical equipment such as CNC machine tools frequently occur, which seriously affects the production performance and service life of the machine tools. In order to identify the types of faults in rolling bearings and improve the safety of the equipment, this paper presents a fault diagnosis method on account of an improved Convolution Neural Network (CNN). The improved CNN model is to add a convolutional layer before the fully connected layer, after several convolutional layers and several pooling layers, and use an improved stochastic gradient descent training algorithm with momentum to speed up the training speed to enhance the serviceability of the model. Traditional fault diagnosis methods are time-consuming, high in labor costs and low in work efficiency. The method in this paper improves the intelligence of the rolling bearing of CNC machine tools fault diagnosis process, improves the correctness of fault diagnosis, and adapts to the characteristics of big data fault diagnosis. Finally, the data set of Case Western Reserve University's rolling bearing database is used for experimental verification. The experimental results reveal that this method has a high recognition accuracy rate for various types and severity of rolling bearing faults, and has good practicability and application prospect.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128864366","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00070
Fan Zhou, Yang Wang
In the era of big data, with lower costs and higher efficiency, web crawlers access resources and information from the Internet, bringing a lot of convenience to businesses and individuals. Nevertheless, there are two sides to everything, as malicious crawlers bring incalculable threats and losses to websites. In order to prevent web crawlers from being abused or even developing into malicious crawlers, web sites usually perform anti-crawler based on techniques such as ip access frequency, browsing page speed, account login, input captcha, js encryption, ajax obfuscation, etc. Anti-crawlers cannot completely block crawlers with a particular technique, but only find ways to increase the cost of crawling for attackers, forcing the catching party to make the right choice after weighing the cost-benefit.
{"title":"Exploring The Role of Web Crawler and Anti-Crawler Technology in Big Data Era","authors":"Fan Zhou, Yang Wang","doi":"10.1109/ICTech55460.2022.00070","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00070","url":null,"abstract":"In the era of big data, with lower costs and higher efficiency, web crawlers access resources and information from the Internet, bringing a lot of convenience to businesses and individuals. Nevertheless, there are two sides to everything, as malicious crawlers bring incalculable threats and losses to websites. In order to prevent web crawlers from being abused or even developing into malicious crawlers, web sites usually perform anti-crawler based on techniques such as ip access frequency, browsing page speed, account login, input captcha, js encryption, ajax obfuscation, etc. Anti-crawlers cannot completely block crawlers with a particular technique, but only find ways to increase the cost of crawling for attackers, forcing the catching party to make the right choice after weighing the cost-benefit.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123587020","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 : 2022-02-01DOI: 10.1109/ICTech55460.2022.00116
Rundong Shen, Jicheng Duan, Kechang Zhang
Hydraulic braking has the advantages of small volume, light weight, compact structure, smooth braking and fast response speed, so it can achieve short distance fast braking. Hydraulic braking device is widely used in railway locomotive and vehicle. The assembly of brake cylinder is the key part of hydraulic braking device, which plays the role of spring energy storage and continuous braking force. As the parent of the assembly, the brake cylinder carries the braking force and controls the whole process of braking action. In practical application, the brake cylinder and spring seat often produce stuck phenomenon, the reason is that the brake cylinder shape tolerance requirements are very high, there is a great difficulty in the processing process. In this paper, the processing technology of the brake cylinder is optimized to improve the processing accuracy of the brake cylinder, and the assembly accuracy of the brake cylinder assembly is improved.
{"title":"Research on Optimization design of Hydraulic Brake Cylinder processing technology for Railway Vehicle","authors":"Rundong Shen, Jicheng Duan, Kechang Zhang","doi":"10.1109/ICTech55460.2022.00116","DOIUrl":"https://doi.org/10.1109/ICTech55460.2022.00116","url":null,"abstract":"Hydraulic braking has the advantages of small volume, light weight, compact structure, smooth braking and fast response speed, so it can achieve short distance fast braking. Hydraulic braking device is widely used in railway locomotive and vehicle. The assembly of brake cylinder is the key part of hydraulic braking device, which plays the role of spring energy storage and continuous braking force. As the parent of the assembly, the brake cylinder carries the braking force and controls the whole process of braking action. In practical application, the brake cylinder and spring seat often produce stuck phenomenon, the reason is that the brake cylinder shape tolerance requirements are very high, there is a great difficulty in the processing process. In this paper, the processing technology of the brake cylinder is optimized to improve the processing accuracy of the brake cylinder, and the assembly accuracy of the brake cylinder assembly is improved.","PeriodicalId":290836,"journal":{"name":"2022 11th International Conference of Information and Communication Technology (ICTech))","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127667502","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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