Pub Date : 2021-10-15DOI: 10.1109/PHM-Nanjing52125.2021.9612778
L. Tang
Based on the previous research results, the application of image recognition technology to the rapid detection of urban road asphalt pavement cracks, a fast detection method of urban road asphalt pavement cracks based on image recognition is proposed. This paper designs an image acquisition device of pavement cracks to collect the images of pavement cracks. The road image is denoised and enhanced. Based on image recognition, fracture classification is carried out. Firstly, boundary tracking is carried out, then small area image processing is carried out, and finally fracture classification is carried out. Different methods are used to measure and calculate the relevant parameters of cracks, to realize the rapid detection of cracks. After testing, the design method can improve the overall visual effect of the image to a certain extent, and achieve a higher crack detection rate, which has a broad application prospect.
{"title":"Fast detection method of urban road asphalt pavement crack based on image recognition","authors":"L. Tang","doi":"10.1109/PHM-Nanjing52125.2021.9612778","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612778","url":null,"abstract":"Based on the previous research results, the application of image recognition technology to the rapid detection of urban road asphalt pavement cracks, a fast detection method of urban road asphalt pavement cracks based on image recognition is proposed. This paper designs an image acquisition device of pavement cracks to collect the images of pavement cracks. The road image is denoised and enhanced. Based on image recognition, fracture classification is carried out. Firstly, boundary tracking is carried out, then small area image processing is carried out, and finally fracture classification is carried out. Different methods are used to measure and calculate the relevant parameters of cracks, to realize the rapid detection of cracks. After testing, the design method can improve the overall visual effect of the image to a certain extent, and achieve a higher crack detection rate, which has a broad application prospect.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"42 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":"132613728","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-Nanjing52125.2021.9613010
Liu Fei
The components of nuclear power plant will age and be damaged as the operation time increases. The maintenance of components has long implemented a maintenance system based on post-repaired and periodic maintenance at present. This maintenance method has some defects. A condition-based maintenance strategy can be achieved if the structural damage can be effectively inspected and detected to determine the appropriate maintenance strategy. This puts forward new monitoring requirements for the operation status of nuclear power plant equipment. The systems of nuclear power plant are complex and the monitoring information is huge. How to effectively inspect and detect damage of components to determine appropriate maintenance strategies is worthy of research. This paper proposes to develop a Prognostics and Health Management (PHM) system to use advanced monitoring methods to monitor the operating status and health of nuclear power plant systems and equipment, to determine whether a fault has occurred through the monitoring data, to use intelligent methods to diagnose faults, and to monitor the future operation of the system and equipment, to predict the status and remaining service life, and make maintenance and operation decisions based on the prediction results to avoid the traditional over-maintenance of ‘timed maintenance’ or the huge losses caused by ‘after-the-fact maintenance’. The PHM system of nuclear power plants includes five parts: data acquisition and processing, condition monitoring, fault diagnosis, life prediction and health management. The PHM system diagnoses the health state of the nuclear power plant, implements a state-based maintenance strategy, and reduces the maintenance cost of nuclear power operation and increase the operation life of nuclear power plant.
{"title":"Research on Prognostics and Health Management System Technology in the Field of Nuclear Power Plant","authors":"Liu Fei","doi":"10.1109/PHM-Nanjing52125.2021.9613010","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613010","url":null,"abstract":"The components of nuclear power plant will age and be damaged as the operation time increases. The maintenance of components has long implemented a maintenance system based on post-repaired and periodic maintenance at present. This maintenance method has some defects. A condition-based maintenance strategy can be achieved if the structural damage can be effectively inspected and detected to determine the appropriate maintenance strategy. This puts forward new monitoring requirements for the operation status of nuclear power plant equipment. The systems of nuclear power plant are complex and the monitoring information is huge. How to effectively inspect and detect damage of components to determine appropriate maintenance strategies is worthy of research. This paper proposes to develop a Prognostics and Health Management (PHM) system to use advanced monitoring methods to monitor the operating status and health of nuclear power plant systems and equipment, to determine whether a fault has occurred through the monitoring data, to use intelligent methods to diagnose faults, and to monitor the future operation of the system and equipment, to predict the status and remaining service life, and make maintenance and operation decisions based on the prediction results to avoid the traditional over-maintenance of ‘timed maintenance’ or the huge losses caused by ‘after-the-fact maintenance’. The PHM system of nuclear power plants includes five parts: data acquisition and processing, condition monitoring, fault diagnosis, life prediction and health management. The PHM system diagnoses the health state of the nuclear power plant, implements a state-based maintenance strategy, and reduces the maintenance cost of nuclear power operation and increase the operation life of nuclear power plant.","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":"126592841","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-Nanjing52125.2021.9612965
Haihong Tang, Peng Chen, Dunwen Zuo, Yi Sheng, Qing-Ping Mei
for comparative experiments between the vibration signal and the current signal, an intelligent fault diagnosis method based on multiclass convolutional neural network (MCNN) has been proposed to investigate the vibration and current signal for identifying those faults in complex rotor system. Firstly, the vibration and current signal, including bearing and structural faults, were recorded simultaneously under steady-state for each operation condition (three kinds of speed). Secondly, the signal processing technique is chosen to solve the problem of modeling noise instances as true underlying relationship for MCNN. Finally, a one-versus-one and a comprehensive MCNN have been trained with both signal at various operating conditions individually and collectively, respectively. And the experimental results revealed that the accuracy of the vibration signal is better than the current signal whether it is structure faults or the external bearing faults. Moreover, the fault diagnosis performance of a one-versus-one or a comprehensive MCNN is investigated for the wide range of MCNN parameters. The experimental results shown that the vibration signal of the bearing with the high-pass filter and envelop has stable accuracy.
{"title":"The Comparative Experiments between the Vibration Signal and the Current signal of Rotor System based on Deep Learning Method","authors":"Haihong Tang, Peng Chen, Dunwen Zuo, Yi Sheng, Qing-Ping Mei","doi":"10.1109/PHM-Nanjing52125.2021.9612965","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612965","url":null,"abstract":"for comparative experiments between the vibration signal and the current signal, an intelligent fault diagnosis method based on multiclass convolutional neural network (MCNN) has been proposed to investigate the vibration and current signal for identifying those faults in complex rotor system. Firstly, the vibration and current signal, including bearing and structural faults, were recorded simultaneously under steady-state for each operation condition (three kinds of speed). Secondly, the signal processing technique is chosen to solve the problem of modeling noise instances as true underlying relationship for MCNN. Finally, a one-versus-one and a comprehensive MCNN have been trained with both signal at various operating conditions individually and collectively, respectively. And the experimental results revealed that the accuracy of the vibration signal is better than the current signal whether it is structure faults or the external bearing faults. Moreover, the fault diagnosis performance of a one-versus-one or a comprehensive MCNN is investigated for the wide range of MCNN parameters. The experimental results shown that the vibration signal of the bearing with the high-pass filter and envelop has stable accuracy.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"35 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":"131224994","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-Nanjing52125.2021.9612964
Yulai Zhao, Q. Han, Yang Liu, Shaohui Du
The variable stator vanes (VSV) is prone to happen joint faults such as wear and stagnation due to complex structure and a large number of kinematic pairs. Based on the circumferential spatial distribution characteristics of the joints around actuation ring, this paper establishes a single-stage ring torsional inertia-spring model that considers nonlinearity caused by joint faults. Refer to a real aero-engine’s VSV structure, the system parameters of the model are obtained by simplifying, and then the motion differential equation of the system is obtained. The torsional vibration response of each vane of the system is obtained by the newmark$-beta$ integral method. This paper also developed a diagnosis methodology based on the nonlinear output frequency response functions (NOFRFs), and established a second-order optimal weighted contribution rate indices Rm. Based on the torsional vibration response of each vane, the corresponding Rm is extracted. The asymmetry characteristic of the Rm around the single-stage actuation ring with fault to the excitation vane is established, and the influence of the excitation intensity and other factors on the asymmetry are analyzed. The results show that the diagnosis methodology proposed in this paper can effectively detect joint faults of VSV in aero-engine.
{"title":"Diagnosis Methodology of Joint Faults in Single-Stage Actuation Ring-Vanes System Based on FRF Characterization","authors":"Yulai Zhao, Q. Han, Yang Liu, Shaohui Du","doi":"10.1109/PHM-Nanjing52125.2021.9612964","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612964","url":null,"abstract":"The variable stator vanes (VSV) is prone to happen joint faults such as wear and stagnation due to complex structure and a large number of kinematic pairs. Based on the circumferential spatial distribution characteristics of the joints around actuation ring, this paper establishes a single-stage ring torsional inertia-spring model that considers nonlinearity caused by joint faults. Refer to a real aero-engine’s VSV structure, the system parameters of the model are obtained by simplifying, and then the motion differential equation of the system is obtained. The torsional vibration response of each vane of the system is obtained by the newmark$-beta$ integral method. This paper also developed a diagnosis methodology based on the nonlinear output frequency response functions (NOFRFs), and established a second-order optimal weighted contribution rate indices Rm. Based on the torsional vibration response of each vane, the corresponding Rm is extracted. The asymmetry characteristic of the Rm around the single-stage actuation ring with fault to the excitation vane is established, and the influence of the excitation intensity and other factors on the asymmetry are analyzed. The results show that the diagnosis methodology proposed in this paper can effectively detect joint faults of VSV in aero-engine.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"44 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":"133173646","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-Nanjing52125.2021.9613097
Xiaoyue Liu, Cong Peng
Modern industrial equipment is developing in the direction of automation and intelligence, and intelligent fault diagnosis based on deep learning (DL) has become a hot topic. Traditional fault diagnosis of rotating machinery is mostly based on the fault data obtained by the accelerometer, which has the problems of sparse vibration information and insignificant vibration characteristics. At the same time, the diagnosis algorithm is mostly based on the assumption that a large amount of labeled samples is available, the training and testing dataset are independent and identically distributed. When the mechanical equipment operates under complex and variable working conditions, the performance of traditional fault diagnosis algorithms will be degenerated. Visual vibration measurement has been gradually applied to the field of mechanical fault diagnosis because it can obtain the full-field vibration information with rich texture characteristics and does not produce mass load effect on the measured object. On this basis, this research proposes a new variable-condition fault diagnosis method based on image dataset, which encodes the full-field time-domain vibration information collected by vision into a gray-scale image sequence to enrich the texture to characterize the fault characteristics, instead of traditional accelerometer data for transfer fault diagnosis. The experimental results show that this method can achieve higher classification and recognition results in the task of fault diagnosis of rotor bearing variable working conditions.
{"title":"A New Variable Conditions Intelligent Fault Diagnosis Method for Rotor-bearing Based on Vibration Image Dataset","authors":"Xiaoyue Liu, Cong Peng","doi":"10.1109/PHM-Nanjing52125.2021.9613097","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613097","url":null,"abstract":"Modern industrial equipment is developing in the direction of automation and intelligence, and intelligent fault diagnosis based on deep learning (DL) has become a hot topic. Traditional fault diagnosis of rotating machinery is mostly based on the fault data obtained by the accelerometer, which has the problems of sparse vibration information and insignificant vibration characteristics. At the same time, the diagnosis algorithm is mostly based on the assumption that a large amount of labeled samples is available, the training and testing dataset are independent and identically distributed. When the mechanical equipment operates under complex and variable working conditions, the performance of traditional fault diagnosis algorithms will be degenerated. Visual vibration measurement has been gradually applied to the field of mechanical fault diagnosis because it can obtain the full-field vibration information with rich texture characteristics and does not produce mass load effect on the measured object. On this basis, this research proposes a new variable-condition fault diagnosis method based on image dataset, which encodes the full-field time-domain vibration information collected by vision into a gray-scale image sequence to enrich the texture to characterize the fault characteristics, instead of traditional accelerometer data for transfer fault diagnosis. The experimental results show that this method can achieve higher classification and recognition results in the task of fault diagnosis of rotor bearing variable working conditions.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"69 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":"133399796","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 reliability model for single internal and external meshing planetary gear transmission mechanism considering load correlation is studied in this paper. Then, the reliability of single internal and external meshing three planetary gear transmission mechanisms is calculated using this method. Finally, in order to verify the engineering applicability and rationality, this method is compared with the Monte Carlo simulation method. The results show the rationality, advantage and applicability of this new method. Meanwhile, the reliability model considering correlation provides a general method for single internal and external meshing planetary gear transmission mechanism.
{"title":"Reliability Model of Single Intemal and Extemal Meshing Planetary Gear Transmission Mechanism Considering Load Correlation","authors":"Shulin Liu, Q. Tang, Shufei Xue, Zhezheng Wang, Peng Chen, X. Yi","doi":"10.1109/PHM-Nanjing52125.2021.9612879","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612879","url":null,"abstract":"The reliability model for single internal and external meshing planetary gear transmission mechanism considering load correlation is studied in this paper. Then, the reliability of single internal and external meshing three planetary gear transmission mechanisms is calculated using this method. Finally, in order to verify the engineering applicability and rationality, this method is compared with the Monte Carlo simulation method. The results show the rationality, advantage and applicability of this new method. Meanwhile, the reliability model considering correlation provides a general method for single internal and external meshing planetary gear transmission mechanism.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"15 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":"132138219","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-Nanjing52125.2021.9613107
Guanxiu Yi, Bo Li, Xuesheng Li, Hengchang Liu
With the continuous development of manufacturing industry, performance degradation prediction is of great significance to improve the performance reliability of equipment. In practical engineering, the source of equipment performance data is complex and time-dependent, and different performance data have different effects on equipment performance degradation prediction, which leads to the limitation of traditional prediction methods. In this paper, a Long-Short Term memory (LSTM) neural network model based on attention mechanism is proposed (Attention-LSTM). This model can effectively predict the long-term performance time series, automatically learn the weight of each performance data, and describe the impact of different performance indicators on the prediction of equipment performance degradation. Taking the “CTC three unit” turbomachinery provided by a company in Sichuan as the research object, and the results show that the Attention-LSTM model can more accurately predict the future performance decline trend of the equipment than other algorithms.
{"title":"Research on Prediction of Turbine Mechanical Performance Degradation Based on Attention LSTM","authors":"Guanxiu Yi, Bo Li, Xuesheng Li, Hengchang Liu","doi":"10.1109/PHM-Nanjing52125.2021.9613107","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613107","url":null,"abstract":"With the continuous development of manufacturing industry, performance degradation prediction is of great significance to improve the performance reliability of equipment. In practical engineering, the source of equipment performance data is complex and time-dependent, and different performance data have different effects on equipment performance degradation prediction, which leads to the limitation of traditional prediction methods. In this paper, a Long-Short Term memory (LSTM) neural network model based on attention mechanism is proposed (Attention-LSTM). This model can effectively predict the long-term performance time series, automatically learn the weight of each performance data, and describe the impact of different performance indicators on the prediction of equipment performance degradation. Taking the “CTC three unit” turbomachinery provided by a company in Sichuan as the research object, and the results show that the Attention-LSTM model can more accurately predict the future performance decline trend of the equipment than other algorithms.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"58 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":"133123175","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}
This paper presents a fault-tolerant control (FTC) scheme for the sensor fault in the transition process of variable cycle engine (VCE) based on an adaptive equilibrium manifold model. Firstly, an adaptive equilibrium manifold model (AEMM) with multiple inputs and multiple outputs is established. Combined with the Kalman filter bank, sensor fault diagnosis is carried out to realize the diagnosis and signal reconstruction of the engine in the case of the single sensor and double sensor fault. On this basis, a sensor FTC scheme in the transient process of VCE is proposed, which uses the rotational speed for the closed-loop control. Finally, a hardware-in-loop (HIL) simulation platform is built based on the idea of distributed control. The FTC scheme of the sensor during the acceleration process of VCE is verified based on this platform. The results show that the fault tolerance scheme can accurately diagnose the fault of the low-pressure speed sensor during the acceleration process. After the fault, the analytic redundancy of the on-board model is used to replace the faulty sensor value to continue the closed-loop control, which ensures the reliability of the acceleration process.
{"title":"Fault-tolerant Control Scheme for the Sensor Fault in the Transition Process of Variable Cycle Engine","authors":"Lingwei Li, Yuan Yuan, Xinglong Zhang, Songwei Wu, Tianhong Zhang","doi":"10.1109/PHM-Nanjing52125.2021.9613054","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9613054","url":null,"abstract":"This paper presents a fault-tolerant control (FTC) scheme for the sensor fault in the transition process of variable cycle engine (VCE) based on an adaptive equilibrium manifold model. Firstly, an adaptive equilibrium manifold model (AEMM) with multiple inputs and multiple outputs is established. Combined with the Kalman filter bank, sensor fault diagnosis is carried out to realize the diagnosis and signal reconstruction of the engine in the case of the single sensor and double sensor fault. On this basis, a sensor FTC scheme in the transient process of VCE is proposed, which uses the rotational speed for the closed-loop control. Finally, a hardware-in-loop (HIL) simulation platform is built based on the idea of distributed control. The FTC scheme of the sensor during the acceleration process of VCE is verified based on this platform. The results show that the fault tolerance scheme can accurately diagnose the fault of the low-pressure speed sensor during the acceleration process. After the fault, the analytic redundancy of the on-board model is used to replace the faulty sensor value to continue the closed-loop control, which ensures the reliability of the acceleration process.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"77 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":"123180880","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-Nanjing52125.2021.9612873
Lu Wei
For the construction safety risk assessment of prefabricated construction projects, the traditional evaluation methods are difficult to ensure the data quality under dynamic changes, which affects the reliability of the evaluation results. Therefore, this paper puts forward the research on the dynamic evaluation method of construction safety risk of prefabricated building engineering. According to the construction environment of the assembly construction project, the risk source is determined by analytic hierarchy process, the evaluation index is selected, and the weight vector of each index is calculated. After the one-time assessment, the variable weight of the weight vector is processed according to the characteristics of dynamic change, the comprehensive weight of the evaluation object is calculated, the evaluation standard cloud is constructed, the comprehensive weight is substituted into the evaluation standard cloud, and the dynamic evaluation of construction safety risk is realized in combination with the evaluation language. The experimental results show that the designed evaluation method has high data quality and can effectively evaluate the construction safety risk of prefabricated construction projects.
{"title":"Research on Dynamic Risk Assessment Method for Construction Safety of Fabricated Construction Projects","authors":"Lu Wei","doi":"10.1109/PHM-Nanjing52125.2021.9612873","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612873","url":null,"abstract":"For the construction safety risk assessment of prefabricated construction projects, the traditional evaluation methods are difficult to ensure the data quality under dynamic changes, which affects the reliability of the evaluation results. Therefore, this paper puts forward the research on the dynamic evaluation method of construction safety risk of prefabricated building engineering. According to the construction environment of the assembly construction project, the risk source is determined by analytic hierarchy process, the evaluation index is selected, and the weight vector of each index is calculated. After the one-time assessment, the variable weight of the weight vector is processed according to the characteristics of dynamic change, the comprehensive weight of the evaluation object is calculated, the evaluation standard cloud is constructed, the comprehensive weight is substituted into the evaluation standard cloud, and the dynamic evaluation of construction safety risk is realized in combination with the evaluation language. The experimental results show that the designed evaluation method has high data quality and can effectively evaluate the construction safety risk of prefabricated construction projects.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"21 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":"127833655","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-Nanjing52125.2021.9612925
Yanyan Zhao, Dandan Wang, Zhiqiang Wan, Yang Liu
This paper describes a single-pressing point Solar Array Restraint and Release System (SARRS) based on thermal knife. Compared with the pyrotechnics SARRS, thermal knife is small impact, no pollution, convenient transport; Compared to the multi-pressing point thermal knife SARRS, a single-pressing point SARRS is simple, high reliability, more suitable for aerospace products, especially suitable for small satellite SARRS. This paper first introduces the composition and working principle of SARRS based on thermal knife and its key components. Secondly, the ground test is carried out on the modal of its emission state and in- orbit state. Finally, the relevant tests were carried out on the release of room temperature and the low temperature.
{"title":"A Single-pressing Point Solar Array Restraint and Release System Based on Thermal Knife","authors":"Yanyan Zhao, Dandan Wang, Zhiqiang Wan, Yang Liu","doi":"10.1109/PHM-Nanjing52125.2021.9612925","DOIUrl":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612925","url":null,"abstract":"This paper describes a single-pressing point Solar Array Restraint and Release System (SARRS) based on thermal knife. Compared with the pyrotechnics SARRS, thermal knife is small impact, no pollution, convenient transport; Compared to the multi-pressing point thermal knife SARRS, a single-pressing point SARRS is simple, high reliability, more suitable for aerospace products, especially suitable for small satellite SARRS. This paper first introduces the composition and working principle of SARRS based on thermal knife and its key components. Secondly, the ground test is carried out on the modal of its emission state and in- orbit state. Finally, the relevant tests were carried out on the release of room temperature and the low temperature.","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":"115233266","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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