The outlet cross-sectional area of standard nozzle affects the air mass flow value of TPS. Through the jet simulation of three standard nozzles with different outlet sizes under different boundary conditions, the relationship between outlet diameter and boundary conditions and jet turbulence intensity and near-field and far-field noise is studied. The simulation results show that the outlet cross-sectional area affects the value and range of the turbulence intensity, and has a great change in the mixing region of the turbulent boundary layer. However, under the excitation of the sound source quadrupole, it has no great impact on the propagation trend and extreme value of the sound wave.
{"title":"Prediction of jet noise in compressible turbulent boundary layer using TPS nozzle scale model","authors":"Hongjie Sun, Guozhen Mu, Wanru Liu, Xuewen Liu, Xinggui Ren","doi":"10.1117/12.2672145","DOIUrl":"https://doi.org/10.1117/12.2672145","url":null,"abstract":"The outlet cross-sectional area of standard nozzle affects the air mass flow value of TPS. Through the jet simulation of three standard nozzles with different outlet sizes under different boundary conditions, the relationship between outlet diameter and boundary conditions and jet turbulence intensity and near-field and far-field noise is studied. The simulation results show that the outlet cross-sectional area affects the value and range of the turbulence intensity, and has a great change in the mixing region of the turbulent boundary layer. However, under the excitation of the sound source quadrupole, it has no great impact on the propagation trend and extreme value of the sound wave.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134378799","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 current research status and shortcomings of the mechanical characteristic condition monitoring system of high voltage circuit breaker, a condition monitoring system of high voltage circuit breaker based on DSP is developed in order to find the operation state of circuit breaker in time and improve the reliability. The system uses TMS320C28346 as the control core and AD7606 as the sampling chip, which can realize the collection, conversion, transmission and display of monitoring data, and can monitor the closing and opening coil current and contact stroke of the circuit breaker in real time. Through experimental tests, the results show that the system meets the design requirements of each parameter error below 2%.
{"title":"Mechanical characteristic condition monitoring system of high voltage circuit breaker","authors":"Z. Bowen, L. Siyuan","doi":"10.1117/12.2672265","DOIUrl":"https://doi.org/10.1117/12.2672265","url":null,"abstract":"Aiming at the current research status and shortcomings of the mechanical characteristic condition monitoring system of high voltage circuit breaker, a condition monitoring system of high voltage circuit breaker based on DSP is developed in order to find the operation state of circuit breaker in time and improve the reliability. The system uses TMS320C28346 as the control core and AD7606 as the sampling chip, which can realize the collection, conversion, transmission and display of monitoring data, and can monitor the closing and opening coil current and contact stroke of the circuit breaker in real time. Through experimental tests, the results show that the system meets the design requirements of each parameter error below 2%.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256613","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}
In stations, airports and other places, contraband detection faces many problems such as false positives, omissions and slow detection speed caused by object background interference and human factors. This paper proposes an improved network based on YOLO-lightweight. The attention mechanism module is embedded in the backbone network, focusing on the important features from different channels. CBAM-FPN (Convolution Block Attention Module and Feature Pyramid Networks) structure is adopted in the network neck to reduce the loss of network features. Attention mechanism module is added in the bottom-up feature fusion process. Finally, CIOU is used as the edge optimization loss function to accelerate the network convergence and optimize the network model. Compared with YOLOv4-tiny, the precision is improved by 3.8%, reaching 87.5%. The detection speed reaches 60.3fps. The improved network only occupies 23.4M memory, which is convenient for embedding mobile devices. The improved network meets the real-time detection requirements.
在车站、机场等场所，由于物体背景干扰和人为因素，违禁品检测面临误报、漏检、检测速度慢等诸多问题。本文提出了一种基于yolo -轻量级的改进网络。注意机制模块嵌入到骨干网中，关注来自不同渠道的重要特征。网络颈部采用CBAM-FPN (Convolution Block Attention Module and Feature Pyramid Networks)结构，减少网络特征的损失。在自底向上的特征融合过程中增加了注意机制模块。最后，利用CIOU作为边缘优化损失函数，加快网络收敛速度，优化网络模型。与YOLOv4-tiny相比，精度提高了3.8%，达到87.5%。检测速度达到60.3fps。改进后的网络仅占用23.4M内存，便于嵌入移动设备。改进后的网络满足实时检测的要求。
{"title":"YOLO lightweight contraband detection network using attention mechanism","authors":"Yifei Dai, Puchun Chen","doi":"10.1117/12.2672161","DOIUrl":"https://doi.org/10.1117/12.2672161","url":null,"abstract":"In stations, airports and other places, contraband detection faces many problems such as false positives, omissions and slow detection speed caused by object background interference and human factors. This paper proposes an improved network based on YOLO-lightweight. The attention mechanism module is embedded in the backbone network, focusing on the important features from different channels. CBAM-FPN (Convolution Block Attention Module and Feature Pyramid Networks) structure is adopted in the network neck to reduce the loss of network features. Attention mechanism module is added in the bottom-up feature fusion process. Finally, CIOU is used as the edge optimization loss function to accelerate the network convergence and optimize the network model. Compared with YOLOv4-tiny, the precision is improved by 3.8%, reaching 87.5%. The detection speed reaches 60.3fps. The improved network only occupies 23.4M memory, which is convenient for embedding mobile devices. The improved network meets the real-time detection requirements.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130582778","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}
One of the most important aspects of Computer General Force (CGF) is to understand what the opponent is doing and predict their possible future actions. In this paper, we propose an extended event graph named Probability Event Graph (PEG) to predict the opponent’s future events. Compared with the basic event graph model, the element of event node, logical node, causal edge and time window is redefines in PEG. Through these novel elements, PEG can describe the event and causal relationship about the system comprehensively. The PEG model is the fundamental of forecast analysis. Firstly, the behaviour characteristics of opponents are analysed and the corresponding PEG model is established according to domain knowledge. Then, the parameters are acquired by training data generated by simulation. Finally, the reasoning algorithm based on PEG model is proposed, and the possibility and principal analysis are carried out.
计算机通用力量(Computer General Force, CGF)最重要的方面之一是理解对手在做什么，并预测他们未来可能采取的行动。本文提出了一种扩展的事件图——概率事件图(Probability event graph, PEG)来预测对手的未来事件。与基本事件图模型相比，PEG重新定义了事件节点、逻辑节点、因果边和时间窗口的元素。通过这些新颖的元素，聚乙二醇可以全面地描述系统的事件和因果关系。PEG模型是预测分析的基础。首先，分析对手的行为特征，根据领域知识建立相应的聚乙二醇模型;然后，利用仿真生成的训练数据获取参数。最后，提出了基于PEG模型的推理算法，并进行了可行性分析和主体分析。
{"title":"An extended event graph with probability for causal tracing and event prediction","authors":"Qiwang Huang, Yang Zhang, Tao Wang, X. Liu","doi":"10.1117/12.2673047","DOIUrl":"https://doi.org/10.1117/12.2673047","url":null,"abstract":"One of the most important aspects of Computer General Force (CGF) is to understand what the opponent is doing and predict their possible future actions. In this paper, we propose an extended event graph named Probability Event Graph (PEG) to predict the opponent’s future events. Compared with the basic event graph model, the element of event node, logical node, causal edge and time window is redefines in PEG. Through these novel elements, PEG can describe the event and causal relationship about the system comprehensively. The PEG model is the fundamental of forecast analysis. Firstly, the behaviour characteristics of opponents are analysed and the corresponding PEG model is established according to domain knowledge. Then, the parameters are acquired by training data generated by simulation. Finally, the reasoning algorithm based on PEG model is proposed, and the possibility and principal analysis are carried out.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122337790","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}
In order to realize the lightweight design of the wing structure, the internal structure of the wing was taken as the research object. Topology optimization took structural compliance as the objective function, and size optimization took mass as the objective function. The variable density method based on the SIMP stiffness interpolation model was used to optimize the structural layout of the wing. On this basis, the finite element model (FEM)of shell-rod structure was established, and the feasible direction method (MFD) was used to optimize the wing structure size. The mass of structure is reduced by 28.7% compared with the initial structure, the optimal design scheme of the wing is obtained.
{"title":"Optimization design of the wing structure based on variable density method and feasible direction method","authors":"Bohao He, Jianjiang Zeng","doi":"10.1117/12.2671838","DOIUrl":"https://doi.org/10.1117/12.2671838","url":null,"abstract":"In order to realize the lightweight design of the wing structure, the internal structure of the wing was taken as the research object. Topology optimization took structural compliance as the objective function, and size optimization took mass as the objective function. The variable density method based on the SIMP stiffness interpolation model was used to optimize the structural layout of the wing. On this basis, the finite element model (FEM)of shell-rod structure was established, and the feasible direction method (MFD) was used to optimize the wing structure size. The mass of structure is reduced by 28.7% compared with the initial structure, the optimal design scheme of the wing is obtained.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124678968","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}
In the process of pumping and shore blowing of trailing suction dredger, the mud and sand movement mechanism of mud tank and sludge discharge pipeline is complex and strongly coupled. It is difficult to obtain the relationship between mud transportation concentration and pumping hatch, mud pump, high-pressure flushing, submarine diversion valve and pipeline through mechanism analysis. Aiming at this problem, this paper proposes a prediction method of instantaneous output of trailing suction dredger pumping and bank blowing based on BP neural network. Through the training of historical construction data, PSO and GA algorithms are used to optimize respectively, and the prediction model of instantaneous output of trailing suction dredger pumping and bank blowing is established. The simulation results show that this method can effectively predict the production of mud from the suction dredger.
{"title":"Research on the prediction method of yield in extraction process of trailing suction dredger","authors":"Jie Guo, Mengxi Yu, Bowen Zhou","doi":"10.1117/12.2671909","DOIUrl":"https://doi.org/10.1117/12.2671909","url":null,"abstract":"In the process of pumping and shore blowing of trailing suction dredger, the mud and sand movement mechanism of mud tank and sludge discharge pipeline is complex and strongly coupled. It is difficult to obtain the relationship between mud transportation concentration and pumping hatch, mud pump, high-pressure flushing, submarine diversion valve and pipeline through mechanism analysis. Aiming at this problem, this paper proposes a prediction method of instantaneous output of trailing suction dredger pumping and bank blowing based on BP neural network. Through the training of historical construction data, PSO and GA algorithms are used to optimize respectively, and the prediction model of instantaneous output of trailing suction dredger pumping and bank blowing is established. The simulation results show that this method can effectively predict the production of mud from the suction dredger.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126414045","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 reliable operation of wind turbines is the foundation of efficient application of wind energy, and it can promote the development of new energy. Drive system is the key link to realize wind power generation, which affects the power generation efficiency, economic benefits and safe operation of wind farms. This paper introduces the components of the wind turbine drive system, analyzes the common failures of its components, analyzes the causes of the failures, and puts forward some suggestions to improve the reliability of the wind turbine drive system, which can provide a reference for wind farm operators.
{"title":"Failure analysis of wind turbine drive system","authors":"Wang Liqiang, Zhang Xiuqi","doi":"10.1117/12.2671861","DOIUrl":"https://doi.org/10.1117/12.2671861","url":null,"abstract":"The reliable operation of wind turbines is the foundation of efficient application of wind energy, and it can promote the development of new energy. Drive system is the key link to realize wind power generation, which affects the power generation efficiency, economic benefits and safe operation of wind farms. This paper introduces the components of the wind turbine drive system, analyzes the common failures of its components, analyzes the causes of the failures, and puts forward some suggestions to improve the reliability of the wind turbine drive system, which can provide a reference for wind farm operators.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"12596 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128932314","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}
In view of the existence of a large number of conventional state monitoring devices in power transmission and transformation equipment, the use of state monitoring communication gateway is an effective method to solve the problem that conventional state monitoring devices are connected to the power transmission and transformation property management platform. Based on the analysis of Modbus and IEC61850 models, the model mapping method of Modbus and IEC61850 is proposed, including the mapping between IEC61850 object reference and MODBUS address, the mapping between public data type and MODBUS parameter type, and the mapping between abstract communication service and Modbus protocol data unit. The data model of Modbus is built by object-oriented technology. According to the principle of hierarchical semantic equivalence, the mapping relationship of information and service models among Modbus, IEC61850 and MMS is established. Based on the established mapping model, the design of Modbus and IEC 61850-8-1 conversion module and the reading and writing service of status monitoring data are completed, which verifies the correctness and feasibility of the above design method.
{"title":"Research on model mapping method between MODBUS and IEC61850","authors":"Zheng Peng, Weiyun Mao, Yaqi Zhang, Xiangyi Xu","doi":"10.1117/12.2671815","DOIUrl":"https://doi.org/10.1117/12.2671815","url":null,"abstract":"In view of the existence of a large number of conventional state monitoring devices in power transmission and transformation equipment, the use of state monitoring communication gateway is an effective method to solve the problem that conventional state monitoring devices are connected to the power transmission and transformation property management platform. Based on the analysis of Modbus and IEC61850 models, the model mapping method of Modbus and IEC61850 is proposed, including the mapping between IEC61850 object reference and MODBUS address, the mapping between public data type and MODBUS parameter type, and the mapping between abstract communication service and Modbus protocol data unit. The data model of Modbus is built by object-oriented technology. According to the principle of hierarchical semantic equivalence, the mapping relationship of information and service models among Modbus, IEC61850 and MMS is established. Based on the established mapping model, the design of Modbus and IEC 61850-8-1 conversion module and the reading and writing service of status monitoring data are completed, which verifies the correctness and feasibility of the above design method.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127571355","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 respect to the 16 characteristics of the workers, the objective of this study is to investigate how employee turnover can be classified using various machine learning algorithms (Support Vector Classification, Decision Tree Classifier, AdaBoost Classifier, Random Forest Classifier, Extra Trees Classifier, Logistic Regression and Gradient Boosting Classifiers). The information comes from the Employee Turnover dataset by E. Babushkin. Seven distinct classification models were developed and contrasted, including naive Bayes, random forest, logistic regression, support vector machines, and XGBoost. Numerous experiments validate the effectiveness of machine learning model. Among all the models, we find that the random forest model achieves the best results, which can be furtherly utilized in real-world prediction.
{"title":"Employee turnover prediction using machine learning models","authors":"Chenyu Liao","doi":"10.1117/12.2672733","DOIUrl":"https://doi.org/10.1117/12.2672733","url":null,"abstract":"With respect to the 16 characteristics of the workers, the objective of this study is to investigate how employee turnover can be classified using various machine learning algorithms (Support Vector Classification, Decision Tree Classifier, AdaBoost Classifier, Random Forest Classifier, Extra Trees Classifier, Logistic Regression and Gradient Boosting Classifiers). The information comes from the Employee Turnover dataset by E. Babushkin. Seven distinct classification models were developed and contrasted, including naive Bayes, random forest, logistic regression, support vector machines, and XGBoost. Numerous experiments validate the effectiveness of machine learning model. Among all the models, we find that the random forest model achieves the best results, which can be furtherly utilized in real-world prediction.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123893046","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}
Yancui Wang, Lili Yang, Xinying Zhao, Ning Zhang, Caiyun Wang, Baomin Wang
To ensure the reliable operation and efficient maintenance of the air conditioning ventilation system of Fuxing EMU and reduce the cost of the whole life cycle, RAMS was designed for the ventilation system in the conceptual design stage. According to the structural composition and technical characteristics of the air conditioning ventilation system, the risk analysis model of the air conditioning ventilation system is established, and the design of the safety, reliability, maintainability, and availability of the air conditioning system is completed one by one. This design result can provide strong data support for the optimization design and maintenance plan revision of the air conditioning and ventilation system of the EMU.
{"title":"RAMS design of air conditioning ventilation system of Fuxing EMU","authors":"Yancui Wang, Lili Yang, Xinying Zhao, Ning Zhang, Caiyun Wang, Baomin Wang","doi":"10.1117/12.2671948","DOIUrl":"https://doi.org/10.1117/12.2671948","url":null,"abstract":"To ensure the reliable operation and efficient maintenance of the air conditioning ventilation system of Fuxing EMU and reduce the cost of the whole life cycle, RAMS was designed for the ventilation system in the conceptual design stage. According to the structural composition and technical characteristics of the air conditioning ventilation system, the risk analysis model of the air conditioning ventilation system is established, and the design of the safety, reliability, maintainability, and availability of the air conditioning system is completed one by one. This design result can provide strong data support for the optimization design and maintenance plan revision of the air conditioning and ventilation system of the EMU.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115936549","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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