Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021192
Yang Zhang, Hang Yao, Jianjun Qi, P. Jiang, B. Guo
Lithium-ion batteries have been growing in popularity for portable electronics, electric vehicles, aerospace and military devices due to many excellent characteristics. The prognostics and health management of lithium-ion batteries are significant. In this paper, a novel mixture model of multi-kernel relevance vector machines with dynamic weights (DW-MMKRVM) is proposed to estimate the real-time capacity of lithium-ion batteries based on indirect health indicators. Weights of each sub-model in DW-MMKRVM keep updating during sequential, online data collection and model training. Experiments illustrate the proposed approach can produce more robust and accurate capacity estimation, which is critical for prognostics and health management of lithium-ion batteries. Comparison results also show that the proposed DW-MMKRVM with more sub-models can increase the estimation accuracy.
{"title":"Real-Time Capacity Estimation of Lithium-ion Batteries Using a Novel Ensemble of Multi-Kernel Relevance Vector Machines","authors":"Yang Zhang, Hang Yao, Jianjun Qi, P. Jiang, B. Guo","doi":"10.1109/QR2MSE46217.2019.9021192","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021192","url":null,"abstract":"Lithium-ion batteries have been growing in popularity for portable electronics, electric vehicles, aerospace and military devices due to many excellent characteristics. The prognostics and health management of lithium-ion batteries are significant. In this paper, a novel mixture model of multi-kernel relevance vector machines with dynamic weights (DW-MMKRVM) is proposed to estimate the real-time capacity of lithium-ion batteries based on indirect health indicators. Weights of each sub-model in DW-MMKRVM keep updating during sequential, online data collection and model training. Experiments illustrate the proposed approach can produce more robust and accurate capacity estimation, which is critical for prognostics and health management of lithium-ion batteries. Comparison results also show that the proposed DW-MMKRVM with more sub-models can increase the estimation accuracy.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"18 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116752871","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021134
Hong-Hua Sun, Xudong Chen, Qing-yang Li, Chunwei Li
Axis are usually hollow or solid cylindrical members. According to different needs, complex geometric elements such as holes, grooves, splines and steps will be designed on the axis. These parts often lead to stress concentration and high local stress, and multiaxial fatigue will be caused by multi-direction stress or strain in the process of processing. Taking the spindle of a bearing ring inner grinder as the research object, the working mechanism of the inner grinder, the feeding mode of the spindle and the workpiece are analyzed. The fatigue life prediction model of the spindle is determined by the critical plane method, and the number of stress cycles and fatigue damage of the spindle under four technological processes are also determined. In view of the fact that the inner grinder of bearing rings will change the size of workpiece irregularly, the influence of bearing rings of different sizes on the fatigue life of the spindle is simulated and analyzed. The maximum stress cycle times of the spindle are calculated, and the scatter plot is drawn. Finally, the relationship curve and function relationship between the inner diameter of bearing rings and the fatigue life of the spindle are obtained by the least square curve fitting method combined with the MATLAB curve fitting toolbox.
{"title":"Multiaxial Fatigue Life Prediction Based on Critical Plane Method","authors":"Hong-Hua Sun, Xudong Chen, Qing-yang Li, Chunwei Li","doi":"10.1109/QR2MSE46217.2019.9021134","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021134","url":null,"abstract":"Axis are usually hollow or solid cylindrical members. According to different needs, complex geometric elements such as holes, grooves, splines and steps will be designed on the axis. These parts often lead to stress concentration and high local stress, and multiaxial fatigue will be caused by multi-direction stress or strain in the process of processing. Taking the spindle of a bearing ring inner grinder as the research object, the working mechanism of the inner grinder, the feeding mode of the spindle and the workpiece are analyzed. The fatigue life prediction model of the spindle is determined by the critical plane method, and the number of stress cycles and fatigue damage of the spindle under four technological processes are also determined. In view of the fact that the inner grinder of bearing rings will change the size of workpiece irregularly, the influence of bearing rings of different sizes on the fatigue life of the spindle is simulated and analyzed. The maximum stress cycle times of the spindle are calculated, and the scatter plot is drawn. Finally, the relationship curve and function relationship between the inner diameter of bearing rings and the fatigue life of the spindle are obtained by the least square curve fitting method combined with the MATLAB curve fitting toolbox.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124986440","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021211
Hang Yao, X. Jia, Z. Cheng, B. Guo
Residual life prediction using monitoring data is an important method in reliability engineering. However, in the current performance degradation study, the selection of performance degradation characteristics is usually selected based on expert experience. In this study, a method using grey correlation analysis is applied to select the performance degradation characteristics as the health index of products. Further, the selected characteristics are analyzed with the linear Wiener process model. And the model parameters are estimated using the MCMC (Markov Chain Monte Carlo) method in the view of Bayes theory. Finally, a numerical example concerning the remaining life estimation of a certain satellite product is presented.
{"title":"Residual Life Prediction Using Grey Correlation Analysis of Feature Selection","authors":"Hang Yao, X. Jia, Z. Cheng, B. Guo","doi":"10.1109/QR2MSE46217.2019.9021211","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021211","url":null,"abstract":"Residual life prediction using monitoring data is an important method in reliability engineering. However, in the current performance degradation study, the selection of performance degradation characteristics is usually selected based on expert experience. In this study, a method using grey correlation analysis is applied to select the performance degradation characteristics as the health index of products. Further, the selected characteristics are analyzed with the linear Wiener process model. And the model parameters are estimated using the MCMC (Markov Chain Monte Carlo) method in the view of Bayes theory. Finally, a numerical example concerning the remaining life estimation of a certain satellite product is presented.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131573241","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021193
Yanhua Cao, Yong Li, Chun-liang Chen, Yiran Guo
The working time of combat equipment’s engine, such as the diesel engine of armored vehicle, reflects its technical condition to a great degree. However, the identical use time under different external usage environments may reflect different technical conditions of equipment. But the residual life can be indirectly estimated more accurately by calculating equipment’s equivalent use time. Empirically speaking, the same values of degradation parameters usually reflect the same technical conditions of the equipment when it even worked under different external environments. The service life of the same type of equipment under the same usage environments is similar. In this paper, the determination principle and measurement method of the technical parameters is put forward firstly. Then, the neural network’s advantages in prediction field are put forward and the method of regression prediction with neural network is chosen to estimate the equivalent working time of diesel engine of armored vehicle. The standard external usage environments are specified so as to change the ordinary working time into its equivalent. Taking a certain type of armored equipment diesel engine as an example, the prediction model is built based on several degradation parameters. Then the model is tested and verified by actual usage data. The calculation results indicate that the estimation method is scientific and practical. Two problems are finally proposed to discuss for further improvement.
{"title":"Research on Estimation of Equivalent Working Time for Armored Vehicle Engine Based on Degradation Data","authors":"Yanhua Cao, Yong Li, Chun-liang Chen, Yiran Guo","doi":"10.1109/QR2MSE46217.2019.9021193","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021193","url":null,"abstract":"The working time of combat equipment’s engine, such as the diesel engine of armored vehicle, reflects its technical condition to a great degree. However, the identical use time under different external usage environments may reflect different technical conditions of equipment. But the residual life can be indirectly estimated more accurately by calculating equipment’s equivalent use time. Empirically speaking, the same values of degradation parameters usually reflect the same technical conditions of the equipment when it even worked under different external environments. The service life of the same type of equipment under the same usage environments is similar. In this paper, the determination principle and measurement method of the technical parameters is put forward firstly. Then, the neural network’s advantages in prediction field are put forward and the method of regression prediction with neural network is chosen to estimate the equivalent working time of diesel engine of armored vehicle. The standard external usage environments are specified so as to change the ordinary working time into its equivalent. Taking a certain type of armored equipment diesel engine as an example, the prediction model is built based on several degradation parameters. Then the model is tested and verified by actual usage data. The calculation results indicate that the estimation method is scientific and practical. Two problems are finally proposed to discuss for further improvement.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134097426","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021259
Jiantao Li, Yue Wang, Huanan Cui, Dayu Zhang, Hongqi Zhang, Song Zhang, He Wang
There are extensive applications of accelerated degradation test in predicting the lifetime distribution of highly reliable products. The precision of the estimation can be improved by optimizing the experimental design of the accelerated degradation test. However, the complexity of the analytical method prevents the optimization algorithm from extensive application. In this work, a two-step method, based on Monte Carlo simulation and multi-objective genetic algorithm, is presented to optimize the accelerated degradation test, where the degradation rate follows a lognormal distribution. Then, a numerical example is provided to illustrate the method. The result of simulation and sensitivity analysis shows the optimized sample allocation ratio is closely related to the random measurement error.
{"title":"Optimal Design of-the Accelerated Degradation Experiment by Monte Carlo Method and Genetic Algorithm","authors":"Jiantao Li, Yue Wang, Huanan Cui, Dayu Zhang, Hongqi Zhang, Song Zhang, He Wang","doi":"10.1109/QR2MSE46217.2019.9021259","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021259","url":null,"abstract":"There are extensive applications of accelerated degradation test in predicting the lifetime distribution of highly reliable products. The precision of the estimation can be improved by optimizing the experimental design of the accelerated degradation test. However, the complexity of the analytical method prevents the optimization algorithm from extensive application. In this work, a two-step method, based on Monte Carlo simulation and multi-objective genetic algorithm, is presented to optimize the accelerated degradation test, where the degradation rate follows a lognormal distribution. Then, a numerical example is provided to illustrate the method. The result of simulation and sensitivity analysis shows the optimized sample allocation ratio is closely related to the random measurement error.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115203435","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}
Accurate reliability evaluation method play a vital role in production scheduling and equipment science maintenance decisions. However, with the advent of Industry 4.0, the structure and function of modern industrial systems have become more complex. The traditional reliability evaluation method cannot accurately describe the operating state of the production system because it cannot accurately reflect the multistate characteristics. To solve this phenomenon, a novel operational reliability evaluation method for production systems was proposed. Firstly, according to the multistate characteristics of the production system, the new concept of operational reliability is proposed. Secondly, based on the operating characteristics of the production system, a multistate production network that comprehensively analyzes the machine performance state, task execution state and product quality state is proposed, to reduce the complexity of the operation. Third, an operational reliability evaluation process for multistate production systems is proposed based on multistate production network and Markov model. Finally, the effectiveness of the proposed method is demonstrated using the case of the ferrite phase shifting unit production system.
{"title":"Operational Reliability Evaluation Method of Production Systems Based on Multistate Production Network","authors":"Xiaodong Wang, Jin-Cheng Wang, Tiejun Ma, Hangong Wang, Zhaojun Hao","doi":"10.1109/QR2MSE46217.2019.9021125","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021125","url":null,"abstract":"Accurate reliability evaluation method play a vital role in production scheduling and equipment science maintenance decisions. However, with the advent of Industry 4.0, the structure and function of modern industrial systems have become more complex. The traditional reliability evaluation method cannot accurately describe the operating state of the production system because it cannot accurately reflect the multistate characteristics. To solve this phenomenon, a novel operational reliability evaluation method for production systems was proposed. Firstly, according to the multistate characteristics of the production system, the new concept of operational reliability is proposed. Secondly, based on the operating characteristics of the production system, a multistate production network that comprehensively analyzes the machine performance state, task execution state and product quality state is proposed, to reduce the complexity of the operation. Third, an operational reliability evaluation process for multistate production systems is proposed based on multistate production network and Markov model. Finally, the effectiveness of the proposed method is demonstrated using the case of the ferrite phase shifting unit production system.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123184640","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021241
Khaldoon Hijazin, Tieling Zhang
The internet of things (IoT) has become an important technology in our life. It is considered as an enhancing feature which could improve the quality of communications if it is applied in the right way. However, if the IoT is not well designed or designed with complicated models, it will result in not easy application so that technicians and engineers will avoid using it. In this paper, a model of IoT utilized in manufacturing industry is illustrated to show the importance of its application. It shows how the IoT is applied in its simplest form through developing a production system in a food factory. One manufacturing line is studied, which is a teacake manufacturing line in a factory in Jordan. After analyzing the production data of the production system and considering the minimum resources required for the production, a model is introduced with programming to show how a proper design of the IoT can help reduce the cost of the production with appropriate human resource planning and reduced cycle time in producing each batch of the Sambo teacakes. Finally, this paper indicates that IoT is a critical technology in manufacturing, which could help the industry to make the entire strategy in order to build and maintain a sustainable and competitive position in the market.
{"title":"The Application of IoT Technology to a Manufacturing Process: Case Study","authors":"Khaldoon Hijazin, Tieling Zhang","doi":"10.1109/QR2MSE46217.2019.9021241","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021241","url":null,"abstract":"The internet of things (IoT) has become an important technology in our life. It is considered as an enhancing feature which could improve the quality of communications if it is applied in the right way. However, if the IoT is not well designed or designed with complicated models, it will result in not easy application so that technicians and engineers will avoid using it. In this paper, a model of IoT utilized in manufacturing industry is illustrated to show the importance of its application. It shows how the IoT is applied in its simplest form through developing a production system in a food factory. One manufacturing line is studied, which is a teacake manufacturing line in a factory in Jordan. After analyzing the production data of the production system and considering the minimum resources required for the production, a model is introduced with programming to show how a proper design of the IoT can help reduce the cost of the production with appropriate human resource planning and reduced cycle time in producing each batch of the Sambo teacakes. Finally, this paper indicates that IoT is a critical technology in manufacturing, which could help the industry to make the entire strategy in order to build and maintain a sustainable and competitive position in the market.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123339592","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021157
Juan Du, Haibin Li
Rosenblatt transformation is a general method for transforming a group of non-normal random variables into a group of equivalent independent normal random variables. However, this method is not suitable for the problem of unknown joint distribution function. In view of the above problems, the joint distribution function is constructed by the Copula function in this paper, and the transformation problem of correlation non-normal variables to independent normal variables is solved. Firstly, the Copula function is used to construct the joint distribution function of correlation variables. It includes the solution of Copula function correlation parameters and the selection of correlation structure types between variables. Secondly, the Copula function is introduced into Rosenblatt transformation to obtain the conditional distribution function of variables,. The correlation variables can be transformed into independent variables. Finally, the structural reliability problem with correlation random variables is analyzed. The feasibility of the proposed method is verified by the specific examples.
{"title":"A Rosenblatt Transformation Method Based on Copula Function for Solving Structural Reliability","authors":"Juan Du, Haibin Li","doi":"10.1109/QR2MSE46217.2019.9021157","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021157","url":null,"abstract":"Rosenblatt transformation is a general method for transforming a group of non-normal random variables into a group of equivalent independent normal random variables. However, this method is not suitable for the problem of unknown joint distribution function. In view of the above problems, the joint distribution function is constructed by the Copula function in this paper, and the transformation problem of correlation non-normal variables to independent normal variables is solved. Firstly, the Copula function is used to construct the joint distribution function of correlation variables. It includes the solution of Copula function correlation parameters and the selection of correlation structure types between variables. Secondly, the Copula function is introduced into Rosenblatt transformation to obtain the conditional distribution function of variables,. The correlation variables can be transformed into independent variables. Finally, the structural reliability problem with correlation random variables is analyzed. The feasibility of the proposed method is verified by the specific examples.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"204 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113953245","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}
For the purpose of monitoring the mechanical equipment in real time, it is of significant potential to collect and transmit mechanical vibration signal through the use of wireless technology. Subjected to the limitation of the narrow bandwidth of the wireless transmission, coupled with the high sampling frequency required by the mechanical vibration signal, it is deemed as quite essential to carry out the on-chip feature extraction or data compression on the sensor node prior to transmitting. The current paper provides a summary of the existing research status from the aspects of sensor node design, on-chip feature extraction and data compression and reconstruction of mechanical vibration signal. Thereafter, we not only summarize but also forecast the research in this field. The current paper is expected to be possibly used as a reference for subsequent research.
{"title":"Wireless Acquisition and Transmission of Mechanical Vibration Signal: A Review","authors":"Yunfei Ma, Xisheng Jia, Guanglong Wang, Huajun Bai, Chiming Guo, Xudong Zhao","doi":"10.1109/QR2MSE46217.2019.9021138","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021138","url":null,"abstract":"For the purpose of monitoring the mechanical equipment in real time, it is of significant potential to collect and transmit mechanical vibration signal through the use of wireless technology. Subjected to the limitation of the narrow bandwidth of the wireless transmission, coupled with the high sampling frequency required by the mechanical vibration signal, it is deemed as quite essential to carry out the on-chip feature extraction or data compression on the sensor node prior to transmitting. The current paper provides a summary of the existing research status from the aspects of sensor node design, on-chip feature extraction and data compression and reconstruction of mechanical vibration signal. Thereafter, we not only summarize but also forecast the research in this field. The current paper is expected to be possibly used as a reference for subsequent research.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125144971","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 : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021219
Zhi-gang Liu, Zhongxiang Ma, C. Pei, Gengjin Sui, Zhen Ji
Aiming at the Salix sawing process because of the unreasonable parameters caused by the cutting effect is poor, saw severe wear and due to the high-speed rotation of the safety problem of high energy consumption, the use of indoor cutting test bench simulation of field work in low speed circumstances. Based on Box-Behnken central combination test method, a multivariate mathematical regression model was established by taking the sawing speed, feed speed and the number of saw blade teeth as the influencing factors, and the sawing power and the sawing surface quality score as the objective function. The results show that the notable order of sawing power influence is sawing speed, feed speed and number of saw blade teeth; the notable order of sawing surface quality score is feed speed, sawing speed and number of saw blade teeth; the optimal combination of working parameters is sawing speed 850 r/min, feed speed 15 mm/s and number of teeth 100 T. Under this combination, sawing power and sawing surface quality score are 156.6W and 81 points. The reliability of the mathematical model is described by probability and data statistics. The relative error of reliability test is used as the evaluation index. The optimized parameter combination is basically accurate, and the established mathematical model meets the reliability requirements.
{"title":"Sawing Test Analysis and Reliability Verification of Salix","authors":"Zhi-gang Liu, Zhongxiang Ma, C. Pei, Gengjin Sui, Zhen Ji","doi":"10.1109/QR2MSE46217.2019.9021219","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021219","url":null,"abstract":"Aiming at the Salix sawing process because of the unreasonable parameters caused by the cutting effect is poor, saw severe wear and due to the high-speed rotation of the safety problem of high energy consumption, the use of indoor cutting test bench simulation of field work in low speed circumstances. Based on Box-Behnken central combination test method, a multivariate mathematical regression model was established by taking the sawing speed, feed speed and the number of saw blade teeth as the influencing factors, and the sawing power and the sawing surface quality score as the objective function. The results show that the notable order of sawing power influence is sawing speed, feed speed and number of saw blade teeth; the notable order of sawing surface quality score is feed speed, sawing speed and number of saw blade teeth; the optimal combination of working parameters is sawing speed 850 r/min, feed speed 15 mm/s and number of teeth 100 T. Under this combination, sawing power and sawing surface quality score are 156.6W and 81 points. The reliability of the mathematical model is described by probability and data statistics. The relative error of reliability test is used as the evaluation index. The optimized parameter combination is basically accurate, and the established mathematical model meets the reliability requirements.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123763454","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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