Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of predic...Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.展开更多
The subsea all-electric Christmas tree(XT) is a key equipment in subsea production systems.Once it fails,the marine environment will be seriously polluted.Therefore,strict reliability analysis and measures to improve ...The subsea all-electric Christmas tree(XT) is a key equipment in subsea production systems.Once it fails,the marine environment will be seriously polluted.Therefore,strict reliability analysis and measures to improve reliability must be performed before a subsea all-electric XT is launched;such measures are crucial to subsea safe production.A fault-tolerant control system was developed in this paper to improve the reliability of XT.A dual-factor degradation model for electrical control system components was proposed to improve the evaluation accuracy,and the reliability of the control system was analyzed based on the Markov model.The influences of the common cause failure and the failure rate in key components on the reliability and availability of the control system were studied.The impacts of mean time to repair and incomplete repair strategy on the availability of the control system were also investigated.Research results show the key factors that affect system reliability,and a specific method to improve the reliability and availability of the control system was given.This reliability analysis method for the control system could be applied to general all-electric subsea control systems to guide their safe production.展开更多
The tubing hanger is an important component of the subsea Christmas tree, experiencing big temperature difference which will lead to very high thermal stresses. On the basis of API 17D/ISO 13628-4 and ASME VIII-1, and...The tubing hanger is an important component of the subsea Christmas tree, experiencing big temperature difference which will lead to very high thermal stresses. On the basis of API 17D/ISO 13628-4 and ASME VIII-1, and by comprehensively considering the erosion of oil and the gravity load of the tubing, a calculation model is established by regarding design pressure and thermal stress, and the method for designing the tubing hanger of the horizontal Christmas tree under big temperature difference condition is developed from the fourth strength theory. The proposed theory for strength design of the tubing hanger in big temperature difference is verified by numerical results from ABAQUS.展开更多
Set high on the great round table stands the lighted Christmas tree.shining its good cheer around the room①. It towers② above the children’sheads as they gaze up at it with admiring eyes. Sitting on the very top of...Set high on the great round table stands the lighted Christmas tree.shining its good cheer around the room①. It towers② above the children’sheads as they gaze up at it with admiring eyes. Sitting on the very top ofthe tree is a silver star surrounded by tiny lights. All the branches arehung with silver bells, tinsel and sparkling lights. Around the base展开更多
The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,f...The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,fault tree analysis(FTA)method,based on static logic and static failure mechanism is no longer applicable for dynamic systems reliability analysis.Dynamic fault tree(DFT)analysis method can solve this problem effectively.In this method,DFT first should be pretreated to get a simplified fault tree(FT);then the FT was modularized to get the independent static subtrees and dynamic subtrees.Binary decision diagram(BDD)analysis method was used to analyze static subtrees,while an approximation algorithm was used to deal with dynamic subtrees.When the scale of each subtree is smaller than the system scale,the analysis efficiency can be improved significantly.At last,the usefulness of this DFT analysis method was proved by applying it to analyzing the reliability of electrical system.展开更多
Tool wear is inevitable in daily machining process since metal cutting process involves the chip rubbing the tool surface after it has been cut by the tool edge.Tool wear dominantly influences the deterioration of sur...Tool wear is inevitable in daily machining process since metal cutting process involves the chip rubbing the tool surface after it has been cut by the tool edge.Tool wear dominantly influences the deterioration of surface finish,geometric and dimensional tolerances of the workpiece.Moreover,for complete utilization of cutting tools and reduction of machine downtime during the machining process,it becomes necessary to understand the develop-ment of tool wear and predict its status before happening.In this study,tool condition monitoring system was used to monitor the behavior of a single point cutting tool to predict flank wear.A uniaxial accelerometer was attached to a single point cutting tool under study.The accelerometer acquires vibrational signals during turning operation on a lathe machine.The acquired signals were then used to extract statistical features such as standard error,variance,skewness,etc.The substantial features were recognized to reduce the utilization of computing resources.They were used to classify the signals as good and three different measures of flank wear by a decision tree algorithm.Frequency domain features were also extracted and shown to be less effective in classification in comparison to statistical features.REPTree(Reduced Error Pruning Tree)algorithm was used in this study.REPTree decision tree algorithm achieved a maximum classification accuracy of 72.77%for all signals combined.When spindle speed and feed rate are considered as the variables the accuracy is about 86.25%.When spindle speed is the only variable parameter the accuracy is about 82.71%.When depth of cut,feed rate and speed of the spindle are considered as variable parameters,the accuracy of the decision tree is around 93.51%.This study demonstrates the performance of REPTree classifier in tool condition monitoring.It can be utilized for tool wear identification and thus improve surface finish,dimensional accuracy of the work piece and reduce machine down-time.Any additional research on the work may involve analysis of different classifier algorithms which could potentially predict tool wear with greater accuracy.展开更多
基金financially supported by the National Key Research and Development Program of China(Grant No.2022YFC3004802)the National Natural Science Foundation of China(Grant Nos.52171287,52325107)+3 种基金High Tech Ship Research Project of Ministry of Industry and Information Technology(Grant Nos.2023GXB01-05-004-03,GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province(Grant No.ZR2022JQ25)the Taishan Scholars Project(Grant No.tsqn201909063)the sub project of the major special project of CNOOC Development Technology,“Research on the Integrated Technology of Intrinsic Safety of Offshore Oil Facilities”(Phase I),“Research on Dynamic Quantitative Analysis and Control Technology of Risks in Offshore Production Equipment”(Grant No.HFKJ-2D2X-AQ-2021-03)。
文摘Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China under Grant No.61703224。
文摘The subsea all-electric Christmas tree(XT) is a key equipment in subsea production systems.Once it fails,the marine environment will be seriously polluted.Therefore,strict reliability analysis and measures to improve reliability must be performed before a subsea all-electric XT is launched;such measures are crucial to subsea safe production.A fault-tolerant control system was developed in this paper to improve the reliability of XT.A dual-factor degradation model for electrical control system components was proposed to improve the evaluation accuracy,and the reliability of the control system was analyzed based on the Markov model.The influences of the common cause failure and the failure rate in key components on the reliability and availability of the control system were studied.The impacts of mean time to repair and incomplete repair strategy on the availability of the control system were also investigated.Research results show the key factors that affect system reliability,and a specific method to improve the reliability and availability of the control system was given.This reliability analysis method for the control system could be applied to general all-electric subsea control systems to guide their safe production.
基金financially supported by the National Science and Technology Major Project of China(Grant No.2011ZX05026-003-02)the National High Technology Research and Development Program of China(863 Program,Grant No.2012AA09A205)
文摘The tubing hanger is an important component of the subsea Christmas tree, experiencing big temperature difference which will lead to very high thermal stresses. On the basis of API 17D/ISO 13628-4 and ASME VIII-1, and by comprehensively considering the erosion of oil and the gravity load of the tubing, a calculation model is established by regarding design pressure and thermal stress, and the method for designing the tubing hanger of the horizontal Christmas tree under big temperature difference condition is developed from the fourth strength theory. The proposed theory for strength design of the tubing hanger in big temperature difference is verified by numerical results from ABAQUS.
文摘Set high on the great round table stands the lighted Christmas tree.shining its good cheer around the room①. It towers② above the children’sheads as they gaze up at it with admiring eyes. Sitting on the very top ofthe tree is a silver star surrounded by tiny lights. All the branches arehung with silver bells, tinsel and sparkling lights. Around the base
文摘The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,fault tree analysis(FTA)method,based on static logic and static failure mechanism is no longer applicable for dynamic systems reliability analysis.Dynamic fault tree(DFT)analysis method can solve this problem effectively.In this method,DFT first should be pretreated to get a simplified fault tree(FT);then the FT was modularized to get the independent static subtrees and dynamic subtrees.Binary decision diagram(BDD)analysis method was used to analyze static subtrees,while an approximation algorithm was used to deal with dynamic subtrees.When the scale of each subtree is smaller than the system scale,the analysis efficiency can be improved significantly.At last,the usefulness of this DFT analysis method was proved by applying it to analyzing the reliability of electrical system.
文摘Tool wear is inevitable in daily machining process since metal cutting process involves the chip rubbing the tool surface after it has been cut by the tool edge.Tool wear dominantly influences the deterioration of surface finish,geometric and dimensional tolerances of the workpiece.Moreover,for complete utilization of cutting tools and reduction of machine downtime during the machining process,it becomes necessary to understand the develop-ment of tool wear and predict its status before happening.In this study,tool condition monitoring system was used to monitor the behavior of a single point cutting tool to predict flank wear.A uniaxial accelerometer was attached to a single point cutting tool under study.The accelerometer acquires vibrational signals during turning operation on a lathe machine.The acquired signals were then used to extract statistical features such as standard error,variance,skewness,etc.The substantial features were recognized to reduce the utilization of computing resources.They were used to classify the signals as good and three different measures of flank wear by a decision tree algorithm.Frequency domain features were also extracted and shown to be less effective in classification in comparison to statistical features.REPTree(Reduced Error Pruning Tree)algorithm was used in this study.REPTree decision tree algorithm achieved a maximum classification accuracy of 72.77%for all signals combined.When spindle speed and feed rate are considered as the variables the accuracy is about 86.25%.When spindle speed is the only variable parameter the accuracy is about 82.71%.When depth of cut,feed rate and speed of the spindle are considered as variable parameters,the accuracy of the decision tree is around 93.51%.This study demonstrates the performance of REPTree classifier in tool condition monitoring.It can be utilized for tool wear identification and thus improve surface finish,dimensional accuracy of the work piece and reduce machine down-time.Any additional research on the work may involve analysis of different classifier algorithms which could potentially predict tool wear with greater accuracy.
