Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050047
Ming-Ming Zhu, Lei Yang, Zheng Lei, Yong Wang
As the active mechanism of the main reflector system for a Five Hundred Meter Aperture Spherical Radio Telescope (FAST), the reliable operation of 2225 hydraulic actuators is the basis of normal observation for the telescope. The purpose of this research is to find the right fault search strategy for these hydraulic actuators. According to the characteristics of hydraulic systems, this study proposes a fault search strategy analysis method based on fuzzy fault tree theory. Considering the maintenance factors of hydraulic actuators, such as the searching cost, the failure probability and the degree of influence, the optimal search strategy model for fault diagnosing of hydraulic actuators is established. The multi objective optimization decision theory and sequential decision theory are also applied in this model. Finally, the fault search order for FAST hydraulic actuators is calculated. The top three fault search components are motor, controller and hydraulic control check valve. The calculated results are in agreement with the reliability test results and Failure Mode Effects and Criticality Analysis (FMECA) of hydraulic actuators. This study has guiding significance for the maintenance of the hydraulic actuators for FAST.
{"title":"Fuzzy fault tree theory-based fault search strategy research for FAST hydraulic actuators","authors":"Ming-Ming Zhu, Lei Yang, Zheng Lei, Yong Wang","doi":"10.1109/ICRMS.2016.8050047","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050047","url":null,"abstract":"As the active mechanism of the main reflector system for a Five Hundred Meter Aperture Spherical Radio Telescope (FAST), the reliable operation of 2225 hydraulic actuators is the basis of normal observation for the telescope. The purpose of this research is to find the right fault search strategy for these hydraulic actuators. According to the characteristics of hydraulic systems, this study proposes a fault search strategy analysis method based on fuzzy fault tree theory. Considering the maintenance factors of hydraulic actuators, such as the searching cost, the failure probability and the degree of influence, the optimal search strategy model for fault diagnosing of hydraulic actuators is established. The multi objective optimization decision theory and sequential decision theory are also applied in this model. Finally, the fault search order for FAST hydraulic actuators is calculated. The top three fault search components are motor, controller and hydraulic control check valve. The calculated results are in agreement with the reliability test results and Failure Mode Effects and Criticality Analysis (FMECA) of hydraulic actuators. This study has guiding significance for the maintenance of the hydraulic actuators for FAST.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121346717","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050066
Dalin Shen, Xiaohong Bao, T. Zhao, Pengtao Zhao
Integrated Modular Avionics, which has replaced traditional federal architecture, is now widely used in the aircraft. Robust partitioning is adopted by new architecture to cope with the failure propagation due to resource sharing. However, if the activity of allocating applications to partitions doesn't consider the common cause failure and coupling relations among avionic functions, it can intensify the failure propagation. At present, a lot of researches take into account the application software's functionality and criticality in the software configuration activities, but not include other factors which are also indispensable. In this paper, we proposed a partitioning method from the safety perspective. Firstly, we identified the process of allocating applications to partitions from the partitioning configuration activities referred to Do-297 and built the partitioned system model. Three safety factors which should be satisfied by the process were introduced. Then, we presented the safety constraints based on the safety factors. Finally, we proposed the partitioning strategy on the basic of safety constraints and partitioned system model. This partitioning strategy will be the theoretical basis for the scientific partitioning method in future and ensure the implementation of robust partitioning in Integrated Modular Avionics.
{"title":"Partitioning strategy based on safety in integrated modular avionics","authors":"Dalin Shen, Xiaohong Bao, T. Zhao, Pengtao Zhao","doi":"10.1109/ICRMS.2016.8050066","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050066","url":null,"abstract":"Integrated Modular Avionics, which has replaced traditional federal architecture, is now widely used in the aircraft. Robust partitioning is adopted by new architecture to cope with the failure propagation due to resource sharing. However, if the activity of allocating applications to partitions doesn't consider the common cause failure and coupling relations among avionic functions, it can intensify the failure propagation. At present, a lot of researches take into account the application software's functionality and criticality in the software configuration activities, but not include other factors which are also indispensable. In this paper, we proposed a partitioning method from the safety perspective. Firstly, we identified the process of allocating applications to partitions from the partitioning configuration activities referred to Do-297 and built the partitioned system model. Three safety factors which should be satisfied by the process were introduced. Then, we presented the safety constraints based on the safety factors. Finally, we proposed the partitioning strategy on the basic of safety constraints and partitioned system model. This partitioning strategy will be the theoretical basis for the scientific partitioning method in future and ensure the implementation of robust partitioning in Integrated Modular Avionics.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126674736","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 turret system is one of the key functional components of the CNC lathe. Therefore it is important that the reliability of the turret system is optimised. In this paper, an imperfect preventive maintenance strategy, based on the Weibull distribution, for the turret system of the CNC lathe is proposed. The restoration and failure intensity increase factors are consistent with a uniform distribution. However, the cost of preventive maintenance increases with the preventive maintenance frequency being increased. Then maintenance time should also be considered. A flexible preventive maintenance model is described in this paper. The aim is to minimize the total maintenance cost overall. The preventive maintenance interval of the model was calculated using the limited reliability value, in order to find the optimal flexible preventive maintenance strategy. Finally, the optimal preventive maintenance results under different cost parameters are discussed.
{"title":"Research on imperfect preventive maintenance strategy for turret system of the CNC lathe","authors":"Fei Chen, Heng Zhang, Binbin Xu, Xiaojuan Chen, Zhaojun Yang, Yifeng Ye, Qunya Xie","doi":"10.1109/ICRMS.2016.8050075","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050075","url":null,"abstract":"The turret system is one of the key functional components of the CNC lathe. Therefore it is important that the reliability of the turret system is optimised. In this paper, an imperfect preventive maintenance strategy, based on the Weibull distribution, for the turret system of the CNC lathe is proposed. The restoration and failure intensity increase factors are consistent with a uniform distribution. However, the cost of preventive maintenance increases with the preventive maintenance frequency being increased. Then maintenance time should also be considered. A flexible preventive maintenance model is described in this paper. The aim is to minimize the total maintenance cost overall. The preventive maintenance interval of the model was calculated using the limited reliability value, in order to find the optimal flexible preventive maintenance strategy. Finally, the optimal preventive maintenance results under different cost parameters are discussed.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115303963","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050069
X. Ye, Yigang Lin, Rao Fu, Bokai Zheng, G. Zhai
The storage reliability of electromechanical products such as relays and contactors, which are widely used in the aerospace and military fields, will directly affect the performance of the systems in which they are used. For the existing problem of storage reliability assessment for small samples of aerospace relays and other electromechanical products produced on a small scale, a particle filter and Bayesian theory based storage reliability evaluation method is proposed. Firstly, with the application of a particle filter, the distribution of the degradation model parameters is estimated by combining the initial distribution of degradation parameters with actual degradation data to predict the distribution of the degradation data for each test time. Secondly, we consider the predicted distribution to be prior information, then calculate the prior estimation of degradation data distribution hyper-parameters within the constraints of reliability distribution function information entropy maximization. Then we fuse the tested degradation data from the samples with the Bayesian formula to compute the posterior estimation of the hyper-parameters. After that, we obtain the interval estimation of storage reliability by solving a non-central t distribution. Finally, a specific aerospace electromagnetic relay was taken as an example to illustrate the method in detail and verify the effectiveness of the proposed method.
{"title":"Storage reliability assessment for electromechanical components with small sampling based on prior information prediction","authors":"X. Ye, Yigang Lin, Rao Fu, Bokai Zheng, G. Zhai","doi":"10.1109/ICRMS.2016.8050069","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050069","url":null,"abstract":"The storage reliability of electromechanical products such as relays and contactors, which are widely used in the aerospace and military fields, will directly affect the performance of the systems in which they are used. For the existing problem of storage reliability assessment for small samples of aerospace relays and other electromechanical products produced on a small scale, a particle filter and Bayesian theory based storage reliability evaluation method is proposed. Firstly, with the application of a particle filter, the distribution of the degradation model parameters is estimated by combining the initial distribution of degradation parameters with actual degradation data to predict the distribution of the degradation data for each test time. Secondly, we consider the predicted distribution to be prior information, then calculate the prior estimation of degradation data distribution hyper-parameters within the constraints of reliability distribution function information entropy maximization. Then we fuse the tested degradation data from the samples with the Bayesian formula to compute the posterior estimation of the hyper-parameters. After that, we obtain the interval estimation of storage reliability by solving a non-central t distribution. Finally, a specific aerospace electromagnetic relay was taken as an example to illustrate the method in detail and verify the effectiveness of the proposed method.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130627269","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050059
Dao Zhong, Jing Feng, Quan Sun, Zhengqiang Pan, N. Yang
Field data is often used as the basis for the prediction of an airplanes maintenance request. In the traditional methods, maintenance request predictions are mainly obtained immediately using data. However, uncertainty analysis during the failure detection is ignored, which makes maintenance request inaccurate. To overcome the above problems, a novel approach is proposed in this paper: a multivariate damage model is established to obtain the degree of airplane damage, which is used as an indicator for maintenance request predictions. On the basis of the degree of damage, uncertainty analysis can be effectively described using a stochastic process and the Markov process. The transition probability and transition time corresponding to the potential detection rate and date of maintenance, which are used to determine the distribution of maintenance requests. Experiments are implemented based on field data of a certain type of airplane. Results confirm that the proposed method performs well in the predictions of maintenance requests.
{"title":"Maintenance request prediction for airplanes based on multivariate damage model","authors":"Dao Zhong, Jing Feng, Quan Sun, Zhengqiang Pan, N. Yang","doi":"10.1109/ICRMS.2016.8050059","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050059","url":null,"abstract":"Field data is often used as the basis for the prediction of an airplanes maintenance request. In the traditional methods, maintenance request predictions are mainly obtained immediately using data. However, uncertainty analysis during the failure detection is ignored, which makes maintenance request inaccurate. To overcome the above problems, a novel approach is proposed in this paper: a multivariate damage model is established to obtain the degree of airplane damage, which is used as an indicator for maintenance request predictions. On the basis of the degree of damage, uncertainty analysis can be effectively described using a stochastic process and the Markov process. The transition probability and transition time corresponding to the potential detection rate and date of maintenance, which are used to determine the distribution of maintenance requests. Experiments are implemented based on field data of a certain type of airplane. Results confirm that the proposed method performs well in the predictions of maintenance requests.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130672227","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050129
Haitao Zhao, Hui Yang, Xiao Xiong
The remaining life prediction of the satellite is of great significance in the operation of the satellite and the maintenance strategy of the constellation. The existing life prediction methods only consider the propellant consumption, thus a new dynamic life prediction method considering not only consumption but also random failure and degradation is proposed in this paper. Firstly, the failure characteristics of the satellite are analyzed, and then the satellite life model is established which contains three kinds of mechanisms including random failure, degradation and consumption. Secondly, according to current satellite operation data and Monte Carlo simulation model, the satellite remaining life is obtained through the comparison of the different lifetime determined by each mechanism. Finally, in a case study, the remaining life of 5 satellites on orbit is analyzed. The analysis results show that this new method is more accurate and credible.
{"title":"Satellite lifetime prediction with random failure","authors":"Haitao Zhao, Hui Yang, Xiao Xiong","doi":"10.1109/ICRMS.2016.8050129","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050129","url":null,"abstract":"The remaining life prediction of the satellite is of great significance in the operation of the satellite and the maintenance strategy of the constellation. The existing life prediction methods only consider the propellant consumption, thus a new dynamic life prediction method considering not only consumption but also random failure and degradation is proposed in this paper. Firstly, the failure characteristics of the satellite are analyzed, and then the satellite life model is established which contains three kinds of mechanisms including random failure, degradation and consumption. Secondly, according to current satellite operation data and Monte Carlo simulation model, the satellite remaining life is obtained through the comparison of the different lifetime determined by each mechanism. Finally, in a case study, the remaining life of 5 satellites on orbit is analyzed. The analysis results show that this new method is more accurate and credible.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131843190","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050088
Rongbin Han, Shihai Wang
Although integrated modular avionics (IMA) provides many advantages such as the reduced weight and higher efficiency for system operations, safety problems with correlations of system states come up due to its resource sharing mechanism. Correlations of system states contribute to the fault propagation in IMA systems. In other words, when a shared resource goes into an error state, components which have access to that resource may work in a failed state. Additionally, this process is dynamic during the system running. Model-based method is an adequate approach to analyzing system safety dynamically with correlations of system states. Architecture Analysis and Design Language (AADL) has advantage to model for embedded systems. However, it is quite limited to employ AADL dynamically for analyzing system safety. This paper seeks to translate the AADL models into improved colored GSPN models, which have advantage to simulate with system run-time properties such as time and event occurrence probabilities as well as other properties of system components. Furthermore, the paper focuses on this transformation process without any loss of key modeling elements including those properties mentioned above. Based on this work, subsequent analysis can be conducted. A case study is provided for indicating the application of these transformation rules.
{"title":"Transformation rules from AADL to improved colored GSPN for integrated modular avionics","authors":"Rongbin Han, Shihai Wang","doi":"10.1109/ICRMS.2016.8050088","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050088","url":null,"abstract":"Although integrated modular avionics (IMA) provides many advantages such as the reduced weight and higher efficiency for system operations, safety problems with correlations of system states come up due to its resource sharing mechanism. Correlations of system states contribute to the fault propagation in IMA systems. In other words, when a shared resource goes into an error state, components which have access to that resource may work in a failed state. Additionally, this process is dynamic during the system running. Model-based method is an adequate approach to analyzing system safety dynamically with correlations of system states. Architecture Analysis and Design Language (AADL) has advantage to model for embedded systems. However, it is quite limited to employ AADL dynamically for analyzing system safety. This paper seeks to translate the AADL models into improved colored GSPN models, which have advantage to simulate with system run-time properties such as time and event occurrence probabilities as well as other properties of system components. Furthermore, the paper focuses on this transformation process without any loss of key modeling elements including those properties mentioned above. Based on this work, subsequent analysis can be conducted. A case study is provided for indicating the application of these transformation rules.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131274585","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050042
Hongsheng Pan, Anwei Sheng, Zhuojian Wang, Xinmin Han
The accurate estimation of Mean Time Between Failures (MTBF) may be necessary under small sample size conditions and can be difficult. This article proposes combinations of two methods to calculate the cumulative probability using hierarchical Bayesian estimation and the mean rank order method, and two approaches to estimate parameters of the Weibull distribution using the ε-support vector regression (ε-SVR) and least square method. The relative error of these methods against a simulation are used to measure the accuracy of the parameter estimation where, according to the definition of MTBF, the expectation of the Weibull distribution is taken as the estimated value of MTBF. The article suggests approaches for further research in the reliability of aviation equipment.
{"title":"Analysis of MTBF evaluation methods for small sample sizes","authors":"Hongsheng Pan, Anwei Sheng, Zhuojian Wang, Xinmin Han","doi":"10.1109/ICRMS.2016.8050042","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050042","url":null,"abstract":"The accurate estimation of Mean Time Between Failures (MTBF) may be necessary under small sample size conditions and can be difficult. This article proposes combinations of two methods to calculate the cumulative probability using hierarchical Bayesian estimation and the mean rank order method, and two approaches to estimate parameters of the Weibull distribution using the ε-support vector regression (ε-SVR) and least square method. The relative error of these methods against a simulation are used to measure the accuracy of the parameter estimation where, according to the definition of MTBF, the expectation of the Weibull distribution is taken as the estimated value of MTBF. The article suggests approaches for further research in the reliability of aviation equipment.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122069717","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050152
R. Jiang
The mean cumulative function (MCF) characterizes the failure behavior of a repairable system. Typical model for modeling failure process is the power-law model. It is only applicable for the situations where the empirical MCF is concave or convex. In practical applications, the empirical MCF can be S-shaped. The intensity function associated with an S-shaped MCF is unimodal. The unimodal failure intensity results from interaction between aging and maintenance improvement. In the literature, few models are available for representing the failure process with unimodal failure intensity. In this paper, we present such a model. The model has three parameters and its expression is relatively simple. A regression method is developed to help determine whether the model is appropriate for modeling a given set of data and obtain the initial estimates of the model parameters. The maximum likelihood method is used to obtain the final parameter estimates. Two real-world examples are included to illustrate the appropriateness and usefulness of the proposed model and the parameter estimation method.
{"title":"A new NHPP model for modeling failure process with S-shaped mean cumulative function","authors":"R. Jiang","doi":"10.1109/ICRMS.2016.8050152","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050152","url":null,"abstract":"The mean cumulative function (MCF) characterizes the failure behavior of a repairable system. Typical model for modeling failure process is the power-law model. It is only applicable for the situations where the empirical MCF is concave or convex. In practical applications, the empirical MCF can be S-shaped. The intensity function associated with an S-shaped MCF is unimodal. The unimodal failure intensity results from interaction between aging and maintenance improvement. In the literature, few models are available for representing the failure process with unimodal failure intensity. In this paper, we present such a model. The model has three parameters and its expression is relatively simple. A regression method is developed to help determine whether the model is appropriate for modeling a given set of data and obtain the initial estimates of the model parameters. The maximum likelihood method is used to obtain the final parameter estimates. Two real-world examples are included to illustrate the appropriateness and usefulness of the proposed model and the parameter estimation method.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124014818","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 : 2016-10-01DOI: 10.1109/ICRMS.2016.8050053
Baoyu Li, Lei Cheng, Leigang Zhang, Yao Wang, Xiongqing Yu
For structural system with multiple failure modes extensively present in engineering practice, two regional mode importance measures are proposed on the basis of the existing mode importance measures, i.e., the regional mode importance measure based on failure probability and the regional mode importance measure based on sample mean of output response. Compared with the existing global mode importance measures, the proposed regional importance measures can not only provide the inter-mode importance information, but also reflect the effects of different regions of input variables on the importance of a single mode or a group of modes, thus providing useful information to improve and optimize the reliability model. Numerical and engineering examples are used to demonstrate the feasibility and rationality of the proposed indices.
{"title":"Regional importance analysis under multiple failure modes","authors":"Baoyu Li, Lei Cheng, Leigang Zhang, Yao Wang, Xiongqing Yu","doi":"10.1109/ICRMS.2016.8050053","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050053","url":null,"abstract":"For structural system with multiple failure modes extensively present in engineering practice, two regional mode importance measures are proposed on the basis of the existing mode importance measures, i.e., the regional mode importance measure based on failure probability and the regional mode importance measure based on sample mean of output response. Compared with the existing global mode importance measures, the proposed regional importance measures can not only provide the inter-mode importance information, but also reflect the effects of different regions of input variables on the importance of a single mode or a group of modes, thus providing useful information to improve and optimize the reliability model. Numerical and engineering examples are used to demonstrate the feasibility and rationality of the proposed indices.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115450292","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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