Pub Date : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612908
Liu Liu, Z. Xiaofeng, Liao Xing
The SAR antenna system is a core component of the Qilu-1 microsatellite payload. The successful unfolding of the feed source and reflecting surface is the basic prerequisite for the normal operation of the payload. The temperature of the joints connected with them as the primary unfolding criterion are directly related to the success or failure of the antenna system. Therefore, thermal design and thermal reliability analysis are needed. In this paper, the thermal control of the feed source joint is designed and the circuit reliability is analyzed. The key parameters that affect the temperature of the reflecting surface joint are considered and the predicted temperature is simulated. The predicted temperature uncertainty of the reflecting surface joint is calculated, the optimal unfolding stage and thermal reliability are analyzed. The unfolding process of the antenna system is designed and the response times are tested or simulated. Finally, the antenna system unfolded successfully as expected in the orbit. This paper can be used as a reference for the thermal design and reliability analysis of other small SAR antenna systems.
{"title":"Thermal Design and Thermal Reliability Analysis of SAR Antenna System Unfolding","authors":"Liu Liu, Z. Xiaofeng, Liao Xing","doi":"10.1109/PHM-Nanjing52125.2021.9612908","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612908","url":null,"abstract":"The SAR antenna system is a core component of the Qilu-1 microsatellite payload. The successful unfolding of the feed source and reflecting surface is the basic prerequisite for the normal operation of the payload. The temperature of the joints connected with them as the primary unfolding criterion are directly related to the success or failure of the antenna system. Therefore, thermal design and thermal reliability analysis are needed. In this paper, the thermal control of the feed source joint is designed and the circuit reliability is analyzed. The key parameters that affect the temperature of the reflecting surface joint are considered and the predicted temperature is simulated. The predicted temperature uncertainty of the reflecting surface joint is calculated, the optimal unfolding stage and thermal reliability are analyzed. The unfolding process of the antenna system is designed and the response times are tested or simulated. Finally, the antenna system unfolded successfully as expected in the orbit. This paper can be used as a reference for the thermal design and reliability analysis of other small SAR antenna systems.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128737448","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612657
H. Yang, Z. Qi
In order to understand the application of reliability technology in the railway system, the application situation in several subsystems such as the power distribution system, power automation system, traction power supply system, dispatching and command system of the railway system is analyzed, and the above subsystems are summarized. The new progress and development law of the application of reliability technology in the middle of the world, and the possible development trend of the application of reliability technology in the railway system is prospected.
{"title":"Application of Reliability Technology in Railway System","authors":"H. Yang, Z. Qi","doi":"10.1109/PHM-Nanjing52125.2021.9612657","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612657","url":null,"abstract":"In order to understand the application of reliability technology in the railway system, the application situation in several subsystems such as the power distribution system, power automation system, traction power supply system, dispatching and command system of the railway system is analyzed, and the above subsystems are summarized. The new progress and development law of the application of reliability technology in the middle of the world, and the possible development trend of the application of reliability technology in the railway system is prospected.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127176145","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9613079
Xinkai Feng, Lihua Yang, Bo Yu, Kai Wang
This paper presents an analytical investigation of the oil film static and dynamic characteristics on journal inclination tilting pad thrust bearings. A three degree-of-freedom mathematic model for is used to calculate lubricated characteristics of oil film. Then, a systematical study to investigate the effect of journal inclination and elastic deformation on the static and dynamic characteristics for thrust bearing is presented. The study on the resistance of pressure and temperature with journal inclination bearing has great significance to ensure the stability and safety of thrust bearing.
{"title":"Study on Static and Dynamic Characteristics of Tilting Pad Thrust Bearings with Journal Inclination","authors":"Xinkai Feng, Lihua Yang, Bo Yu, Kai Wang","doi":"10.1109/PHM-Nanjing52125.2021.9613079","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613079","url":null,"abstract":"This paper presents an analytical investigation of the oil film static and dynamic characteristics on journal inclination tilting pad thrust bearings. A three degree-of-freedom mathematic model for is used to calculate lubricated characteristics of oil film. Then, a systematical study to investigate the effect of journal inclination and elastic deformation on the static and dynamic characteristics for thrust bearing is presented. The study on the resistance of pressure and temperature with journal inclination bearing has great significance to ensure the stability and safety of thrust bearing.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127261359","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612962
Cai Zhongyi, Wang Zezhou, Zhang Liang
The traditional prediction methods of the remaining useful lifetime (RUL) for the product require a large amount of historical data as support. But for the expensive aviation product, the degradation experiments with large sample sizes are unacceptable. Aiming at this problem, an adaptive RUL prediction method for the single aviation product based on the proportional degradation model is proposed. Firstly, a nonlinear Wiener degradation model with a proportional process is built. Then, based on the small sample or single sample degradation data, the degradation state update method based on the EM-KF is proposed. Finally, using the aviation product performance degradation data to verify the effectiveness of the method.
{"title":"An adaptive prediction method of remaining useful lifetime for the aviation product based on the proportional degradation model","authors":"Cai Zhongyi, Wang Zezhou, Zhang Liang","doi":"10.1109/PHM-Nanjing52125.2021.9612962","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612962","url":null,"abstract":"The traditional prediction methods of the remaining useful lifetime (RUL) for the product require a large amount of historical data as support. But for the expensive aviation product, the degradation experiments with large sample sizes are unacceptable. Aiming at this problem, an adaptive RUL prediction method for the single aviation product based on the proportional degradation model is proposed. Firstly, a nonlinear Wiener degradation model with a proportional process is built. Then, based on the small sample or single sample degradation data, the degradation state update method based on the EM-KF is proposed. Finally, using the aviation product performance degradation data to verify the effectiveness of the method.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128946568","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9613048
Siyi Chen, Yuchen Li, Qifang Liu, Q. Hu
The Lifetime Delayed Degradation Process (LDDP) provides an explanation framework for sequential hard and soft failure modes. In this typical industrial product failure mode, the corresponding degradation phenomenon is presented as the product begins to degrade after a period of operation. For example, the process of crack propagation is a degradation process with a stochastic delay. Based on the LDDP method, we propose the Bayesian-LDDP model. Different from the LDDP method, which is based on the joint likelihood function for statistical inference, the Bayesian-LDDP method combines the prior distribution with the joint likelihood function to infer the posterior distribution of the parameters. Based on the posterior distribution, the Bayesian estimation and further reliability inferences can be derived. In this paper, the Bayesian-LDDP model is applied to the crack inspection data of a transport aircraft. Besides, inferences are provided under different combinations of the lifetime model and the degradation model. In terms of calculation, the Gibbs sampling algorithm is adopted for the Bayesian estimation of parameters. Furthermore, the best model that fits the set of data is chosen according to the DIC criterion. In addition, MCMC convergence diagnosis on the model is performed in this study, and further inference based on the posterior distribution is also implemented by using WINBUGS, including the confidence interval estimation of each parameter and the remaining useful life of the cracks.
{"title":"Bayesian Analysis for Lifetime Delayed Degradation Process","authors":"Siyi Chen, Yuchen Li, Qifang Liu, Q. Hu","doi":"10.1109/PHM-Nanjing52125.2021.9613048","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613048","url":null,"abstract":"The Lifetime Delayed Degradation Process (LDDP) provides an explanation framework for sequential hard and soft failure modes. In this typical industrial product failure mode, the corresponding degradation phenomenon is presented as the product begins to degrade after a period of operation. For example, the process of crack propagation is a degradation process with a stochastic delay. Based on the LDDP method, we propose the Bayesian-LDDP model. Different from the LDDP method, which is based on the joint likelihood function for statistical inference, the Bayesian-LDDP method combines the prior distribution with the joint likelihood function to infer the posterior distribution of the parameters. Based on the posterior distribution, the Bayesian estimation and further reliability inferences can be derived. In this paper, the Bayesian-LDDP model is applied to the crack inspection data of a transport aircraft. Besides, inferences are provided under different combinations of the lifetime model and the degradation model. In terms of calculation, the Gibbs sampling algorithm is adopted for the Bayesian estimation of parameters. Furthermore, the best model that fits the set of data is chosen according to the DIC criterion. In addition, MCMC convergence diagnosis on the model is performed in this study, and further inference based on the posterior distribution is also implemented by using WINBUGS, including the confidence interval estimation of each parameter and the remaining useful life of the cracks.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131057367","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9613040
Jiyang Zhang, Yang Chang, Jianxiao Zou, Shicai Fan
As an indispensable part of process monitoring, the fault diagnosis has become a hot topic in both research and industry. Due to the large-scale monitoring data collected in industrial processes, data-driven methods based on deep learning have been widely used in fault diagnosis. Among these methods, Temporal Convolutional Networks (TCN), which has parallel architectures and larger receptive fields, does not suffer from gradient problems and has shown better performance than Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in fault diagnosis. However, the generic TCN architecture pays equal attention to different monitoring variables and might degrade the fault diagnosis accuracy when some important parts of input data need to be emphasized. Hence, we propose a novel TCN-based fault diagnosis framework, called Attention Mechanism Enhanced Temporal Convolutional Network (AME-TCN). Attention mechanism is good at distinguishing the importance of different monitoring variables and could enhance the performance of TCN for fault diagnosis by weighting each variable to highlight more diagnosis-related parts. For performance validation, AME-TCN model was applied for Tennessee Eastman (TE) process. Experimental results indicated that AME-TCN method not only outperformed than traditional CNN and RNN models, but also enhanced the fault diagnosis ability of TCN.
{"title":"AME-TCN: Attention Mechanism Enhanced Temporal Convolutional Network for Fault Diagnosis in Industrial Processes","authors":"Jiyang Zhang, Yang Chang, Jianxiao Zou, Shicai Fan","doi":"10.1109/PHM-Nanjing52125.2021.9613040","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613040","url":null,"abstract":"As an indispensable part of process monitoring, the fault diagnosis has become a hot topic in both research and industry. Due to the large-scale monitoring data collected in industrial processes, data-driven methods based on deep learning have been widely used in fault diagnosis. Among these methods, Temporal Convolutional Networks (TCN), which has parallel architectures and larger receptive fields, does not suffer from gradient problems and has shown better performance than Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in fault diagnosis. However, the generic TCN architecture pays equal attention to different monitoring variables and might degrade the fault diagnosis accuracy when some important parts of input data need to be emphasized. Hence, we propose a novel TCN-based fault diagnosis framework, called Attention Mechanism Enhanced Temporal Convolutional Network (AME-TCN). Attention mechanism is good at distinguishing the importance of different monitoring variables and could enhance the performance of TCN for fault diagnosis by weighting each variable to highlight more diagnosis-related parts. For performance validation, AME-TCN model was applied for Tennessee Eastman (TE) process. Experimental results indicated that AME-TCN method not only outperformed than traditional CNN and RNN models, but also enhanced the fault diagnosis ability of TCN.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130545308","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612969
Yang Wei-xin, Chen Ya-nong, Hou Ming, L. Shun-ming
A new method based on analyzing Elastic Supporter dynamic stress signals used to diagnose the rotor system faults in small and medium-sized aero-engine is proposed. Firstly, singular value decomposition (SVD) was used to de-noise the elastic supporter dynamic stress signals, and the theory of the difference energy entropy of singular values was achieved. This method was used for determining the proper number of useful singular value and compared with the singular value sequence and the difference spectrum of singular value. Secondly, the de-noised dynamic stress signals were decomposed into a finite number of IMFs by EMD, and in order to remove the fictitious IMFs, the spectral ratio method was utilized to judge the fictitious IMFs. Finally, the fault frequency of the rotor system can be identified accurately by its frequency spectrum. Practical application shows that this method is efficient to recognize the rotor system faults of the Aero-engine.
{"title":"An analytical method for the Elastic Supporter Dynamic Stress Signals applied to Aero-engine fault diagnosis","authors":"Yang Wei-xin, Chen Ya-nong, Hou Ming, L. Shun-ming","doi":"10.1109/PHM-Nanjing52125.2021.9612969","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612969","url":null,"abstract":"A new method based on analyzing Elastic Supporter dynamic stress signals used to diagnose the rotor system faults in small and medium-sized aero-engine is proposed. Firstly, singular value decomposition (SVD) was used to de-noise the elastic supporter dynamic stress signals, and the theory of the difference energy entropy of singular values was achieved. This method was used for determining the proper number of useful singular value and compared with the singular value sequence and the difference spectrum of singular value. Secondly, the de-noised dynamic stress signals were decomposed into a finite number of IMFs by EMD, and in order to remove the fictitious IMFs, the spectral ratio method was utilized to judge the fictitious IMFs. Finally, the fault frequency of the rotor system can be identified accurately by its frequency spectrum. Practical application shows that this method is efficient to recognize the rotor system faults of the Aero-engine.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132962035","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612872
Jing Ma, Hongquan Wen, M. E, Zengqiang Jiang, Qi Li
Real-time and accurate fault diagnosis can provide early warning of system failure and support decision-making of maintenance and replacement processes, enhancing reliability of the dynamic system and reducing costs for maintenance. Deep belief networks, as one of the deep learning methods, can extract features from monitoring data and establish nonlinear relationship between extracted features and comprehensive system conditions. It has potentials for fault diagnosis. In this paper, a complete fault diagnosis framework starting from FFT(Fast Fourier Transform) to health condition prediction is proposed. Bearing vibration data is employed to verify the proposed approach. The results show that the proposed model has high and stable prediction accuracy. These results demonstrate the effectiveness, stability, and robustness of the fault diagnosis framework based on deep belief networks.
{"title":"An Improved Fault Diagnosis Framework Based on Deep Belief Networks","authors":"Jing Ma, Hongquan Wen, M. E, Zengqiang Jiang, Qi Li","doi":"10.1109/PHM-Nanjing52125.2021.9612872","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612872","url":null,"abstract":"Real-time and accurate fault diagnosis can provide early warning of system failure and support decision-making of maintenance and replacement processes, enhancing reliability of the dynamic system and reducing costs for maintenance. Deep belief networks, as one of the deep learning methods, can extract features from monitoring data and establish nonlinear relationship between extracted features and comprehensive system conditions. It has potentials for fault diagnosis. In this paper, a complete fault diagnosis framework starting from FFT(Fast Fourier Transform) to health condition prediction is proposed. Bearing vibration data is employed to verify the proposed approach. The results show that the proposed model has high and stable prediction accuracy. These results demonstrate the effectiveness, stability, and robustness of the fault diagnosis framework based on deep belief networks.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130797254","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9613109
Bo Deng, Jingchao Li, Haijun Wang, Cheng Cong, Yulong Ying, Bin Zhang
Since each entropy feature has some defects in feature extraction, it appears that it is impossible to use one entropy feature to completely extract the time-frequency features of rolling bearing failure. Starting from the information entropy fusion theory, using nonlinear dynamic parameter entropy as a feature, a rolling bearing fault diagnosis method based on local mean decomposition (LMD) entropy feature fusion is proposed. First, use LMD to decompose the original fault signal to obtain multiple PF components, calculate the kurtosis value and correlation coefficient of each PF component, and choose the appropriate PF component to reconstruct the signal. Then, the approximate entropy and singular spectrum entropy of the reconstructed signal after LMD decomposition are calculated respectively, and the entropy feature fusion is performed to obtain complementary rolling bearing fault features. Finally, the fused entropy features are used for fault diagnosis through the Random Forest (Random Forest) algorithm. The simulation results show that the accuracy of the method reaches 98.3%. The study of this method can provide an effective theoretical basis for the fault diagnosis of rolling bearings in rotating machinery.
{"title":"Rolling Bearing Fault Diagnosis Method Based On LMD Entropy Feature Fusion","authors":"Bo Deng, Jingchao Li, Haijun Wang, Cheng Cong, Yulong Ying, Bin Zhang","doi":"10.1109/PHM-Nanjing52125.2021.9613109","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613109","url":null,"abstract":"Since each entropy feature has some defects in feature extraction, it appears that it is impossible to use one entropy feature to completely extract the time-frequency features of rolling bearing failure. Starting from the information entropy fusion theory, using nonlinear dynamic parameter entropy as a feature, a rolling bearing fault diagnosis method based on local mean decomposition (LMD) entropy feature fusion is proposed. First, use LMD to decompose the original fault signal to obtain multiple PF components, calculate the kurtosis value and correlation coefficient of each PF component, and choose the appropriate PF component to reconstruct the signal. Then, the approximate entropy and singular spectrum entropy of the reconstructed signal after LMD decomposition are calculated respectively, and the entropy feature fusion is performed to obtain complementary rolling bearing fault features. Finally, the fused entropy features are used for fault diagnosis through the Random Forest (Random Forest) algorithm. The simulation results show that the accuracy of the method reaches 98.3%. The study of this method can provide an effective theoretical basis for the fault diagnosis of rolling bearings in rotating machinery.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130946634","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 : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612996
Wen Wen
The training goal of application-oriented universities is to cultivate high-quality application-oriented talents with strong social adaptability and competitiveness. It is required that the cultivation of various majors should be closely combined with local characteristics and highlight the improvement of students’ application ability. Based on the above background, this paper puts forward the ability oriented modular talent training program, taking architecture as an example. Starting from the purpose of Application-oriented Colleges and universities, this paper uses the teaching achievements of colleges and universities to reform the existing curriculum structure system, analyzes and explains the problems existing in the current talent training mode of architecture major in Colleges and universities, and constructs a modular teaching system oriented by ability output, combined with the training mode of application-oriented talents, guided by professional ability, and adheres to the principle of integrating theory with practice Based on the principle of combining engineering certification, a complete modular architecture teaching system is constructed. In order to provide reference for the talent training mode of domestic application-oriented universities, it should formulate and explore the idea and talent training scheme of modular reform of Architecture Specialty in line with the orientation of the University.
{"title":"Ability Oriented Modular Talent Training Plan – Taking Architecture as An Example","authors":"Wen Wen","doi":"10.1109/PHM-Nanjing52125.2021.9612996","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612996","url":null,"abstract":"The training goal of application-oriented universities is to cultivate high-quality application-oriented talents with strong social adaptability and competitiveness. It is required that the cultivation of various majors should be closely combined with local characteristics and highlight the improvement of students’ application ability. Based on the above background, this paper puts forward the ability oriented modular talent training program, taking architecture as an example. Starting from the purpose of Application-oriented Colleges and universities, this paper uses the teaching achievements of colleges and universities to reform the existing curriculum structure system, analyzes and explains the problems existing in the current talent training mode of architecture major in Colleges and universities, and constructs a modular teaching system oriented by ability output, combined with the training mode of application-oriented talents, guided by professional ability, and adheres to the principle of integrating theory with practice Based on the principle of combining engineering certification, a complete modular architecture teaching system is constructed. In order to provide reference for the talent training mode of domestic application-oriented universities, it should formulate and explore the idea and talent training scheme of modular reform of Architecture Specialty in line with the orientation of the University.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130228013","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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