A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect main...A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.展开更多
To provide some feasible condition-based maintenance （CBM） decision making methods for civil aeroengine, firstly, the theory of aeroengine CBM decision making is described. The proportional intensity（PI） model is ...To provide some feasible condition-based maintenance （CBM） decision making methods for civil aeroengine, firstly, the theory of aeroengine CBM decision making is described. The proportional intensity（PI） model is established based on the reliability and condition monitoring data. According to the model, the decision making methods are proposed for the optimal preventive maintenance（PM） interval and removal. Then, the time on wing （TOW） is predicted by collecting actual data based on the engine age and operating conditions. Finally, an example of a fleet for CF6-80C2 engines is illustrated. It shows that sufficient engine operation data are the key of accurate decision making. Results indicate that the CBM decision making methods are helpful for engineers in airlines to control engine maintenance actions and TOW, thus decreasing risks and maintenance costs.展开更多
The reliability of the on-wing aircraft Auxiliary Power Unit(APU)decides the cost and the comfort of flight to a large degree.The most important function of APU is to help start main engines by providing compressed ai...The reliability of the on-wing aircraft Auxiliary Power Unit(APU)decides the cost and the comfort of flight to a large degree.The most important function of APU is to help start main engines by providing compressed air.Especially on the condition of sudden shutdown in the air,APU can offer additional thrust for landing.Therefore,its condition monitoring has drawn much attention from the academic and industrial field.Among the on-wing sensing data which can reflect its condition,Exhaust Gas Temperature(EGT)is one of the most important parameters.To ensure the reliability of EGT,one kind of data-driven anomaly detection framework for EGT sensing data is proposed based on the Gaussian Process Regression and Kernel Principal Component Analysis.The situations of one-dimensional and two-dimensional input data for EGT anomaly detection are considered,respectively.The cross-validation experiments are carried out by utilizing the real condition data of APU,which are provided by China Southern Airlines Company Limited Shenyang Maintenance Base.The anomalous stuck condition of EGT sensing data is also detected.Experimental results show that the proposed EGT sensing data anomaly detection method can achieve better performance of false positive ratio,false negative ratio and accuracy.展开更多
The exploration of component states for optimizing maintenance schedules in complex systems has garnered significant interest from researchers.However,current literature usually overlooks the critical aspects of syste...The exploration of component states for optimizing maintenance schedules in complex systems has garnered significant interest from researchers.However,current literature usually overlooks the critical aspects of system flexibility and reconfigurability.Judicious implementation of system reconfiguration can effectively mitigate system downtime and enhance production continuity.This study proposes a dynamic condition-based maintenance policy considering reconfiguration for reconfigurable systems.A double-layer decision rule was constructed for the devices and systems.To achieve the best overall maintenance effect of the system,the remaining useful life probability distribution and recommended maintenance time of each device were used to optimize the concurrent maintenance time window of the devices and determine whether to reconfigure them.A comprehensive maintenance efficiency index was introduced that simultaneously considered the maintenance cost rate,reliability,and availability of the system to characterize the overall maintenance effect.The reconfiguration cost was included in the maintenance cost.The proposed policy was tested through numerical experiments and compared with different-level policies.The results show that the proposed policy can significantly reduce the downtime and maintenance costs and improve the overall system reliability and availability.展开更多
Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take ...Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues.Hence,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue.Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions computing.The simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their lifespan.Compared with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.展开更多
Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading...Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.展开更多
The evolution of maintenance management is briefly introduced in this paper, from corrective maintenance to preventive maintenance. First, a range of condition monitoring and fault diagnosis techniques developed in di...The evolution of maintenance management is briefly introduced in this paper, from corrective maintenance to preventive maintenance. First, a range of condition monitoring and fault diagnosis techniques developed in different industries are surveyed; Second, many methods of condition monitoring are presented; Third, mathematical methods used in condition monitoring are given; Then the merits and shortcomings are discussed. Efficient maintenance policies are of fundamental importance in system engineering because of their fallbacks into the safety and economics of plant operation. Applying condition-based maintenance to a system can reduce the cost and extend the availability of facilities. With the advent of personal computers as fast and cost effective machines for data acquisition and processing of multiple signals some shortcomings mentioned in condition monitoring could be solved or reduced to some extent. These PCs can be a solution as a condition monitoring based maintenance system.展开更多
The present work adopted Reliability Centered Maintenance (RCM) methodology to evaluate marginal oilfield Early Production Facility (EPF) system to properly understand its functional failures and to develop an efficie...The present work adopted Reliability Centered Maintenance (RCM) methodology to evaluate marginal oilfield Early Production Facility (EPF) system to properly understand its functional failures and to develop an efficient maintenance strategy for the system. The outcome of the RCM conducted for a typical EPF within the Niger Delta zone of Nigeria provides an indication of equipment whose failure can significantly affect operations at the production facility. These include the steam generation unit and the wellhead choke assembly, using a risk-based failure Criticality Analysis. Failure Mode and Effect Analysis (FMEA) was conducted for the identified critical equipment on a component basis. Each component of the equipment was analyzed to identify the failure modes, causes and the effect of the failure. The outcome of the FMEA analysis aided the development of a robust maintenance management strategy, which is based on an optimized mix of corrective, preventive and condition-based monitoring maintenance for the marginal oilfield EPF.展开更多
The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis a...The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis and prognosis, and maintenance optimization. Relevant academic research and industrial applications are identified and summarized. The state of art, capabilities,and constraints of condition-based maintenance are analyzed. The presented research demonstrates that the intelligent-based approach has become a promising solution for condition recognition, and an integrated data platform for offshore wind farms is significant to optimize the maintenance activities.展开更多
At present, condition monitoring and fault diagnosis technology and their application in engineering have been widely studied. Relatively little attention has been paid to condition-based maintenance decision-making f...At present, condition monitoring and fault diagnosis technology and their application in engineering have been widely studied. Relatively little attention has been paid to condition-based maintenance decision-making for equipment. In this paper,based on the decision-making policy in traditional condition-based maintenance,the connotation of condition-based maintenance for equipment was defined, and its characteristics were analyzed.Working contents of condition-based maintenance for equipment were provided,which were divided into three stages. The influence factors in condition-based maintenance for equipment were analyzed. The key links of equipment maintenance contents and decision-making process were proposed. The condition-based maintenance decision-making policy presented in this paper can provide a practical reference for equipment maintenance.展开更多
With the further development of service-oriented,performance-based contracting(PBC)has been widely adopted in industry and manufacturing.However,maintenance optimization problems under PBC have not received enough att...With the further development of service-oriented,performance-based contracting(PBC)has been widely adopted in industry and manufacturing.However,maintenance optimization problems under PBC have not received enough attention.To further extend the scope of PBC’s application in the field of maintenance optimization,we investigate the condition-based maintenance(CBM)optimization for gamma deteriorating systems under PBC.Considering the repairable single-component system subject to the gamma degradation process,this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC.In the proposed CBM model,the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate.Then,a particle swarm algorithm(PSO)and related solution procedure are presented to solve the multiple decision variables in our proposed model.In the end,a numerical example is provided so as to demonstrate the superiority of the presented model.By comparing the proposed policy with the conventional ones,the superiority of our proposed policy is proved,which can bring more profits to providers and improve performance.Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy.A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.展开更多
In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Co...In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Considering the structure of multi-component systems,the maintenance strategy is determined according to the importance of the components.The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements.First,multi-component models are grouped.Then,a failure probability model of multi-component systems is established.The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.Second,the component importance indicator is introduced into the grouping model,and the optimization model,which aimed at a maximum economic profit,is established.A genetic algorithm is used to solve the non-deterministic polynomial(NP)-complete problem in the optimization model,and the optimal grouping is obtained through the initial grouping determined by random allocation.An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy,and the influence of the system structure and the parameters on the maintenance strategy is discussed.展开更多
Condition based maintenance(CBM) is one of the solutions to machinery maintenance requirements. Latest approaches to CBM aim at reducing human engagement in the real-time fault detection and decision making. Machine l...Condition based maintenance(CBM) is one of the solutions to machinery maintenance requirements. Latest approaches to CBM aim at reducing human engagement in the real-time fault detection and decision making. Machine learning techniques like fuzzy-logic-based systems, neural networks, and support vector machines help to reduce human involvement. Most of these techniques provide fault information with 100% confidence. It is undeniably apparent that this area has a vast application scope. To facilitate future exploration, this review is presented describing the centrifugal pump faults, the signals they generate, their CBM based diagnostic schemes, and case studies for blockage and cavitation fault detection in centrifugal pump(CP) by performing the experiment on test rig. The classification accuracy is above 98% for fault detection. This review gives a head-start to new researchers in this field and identifies the un-touched areas pertaining to CP fault diagnosis.展开更多
Aiming at digital relay protection system, a novel hidden failure Markov reliability model is presented for a single main protection and double main protection systems according to hidden failure and protection functi...Aiming at digital relay protection system, a novel hidden failure Markov reliability model is presented for a single main protection and double main protection systems according to hidden failure and protection function under Condition-Based Maintenance (CBM) circumstance and reliability indices such as probability of protection system hidden failure state are calculated. Impacts of different parameters (containing impacts of human errors) to hidden failure state probability and the optimal measures to improve reliability by variable parameter method are also analyzed. It’s demonstrated here that: Compared to a single main protection, double main protection system has an increased hidden failure probability, thus the real good state probability decreases, two main protections’ reliability must be improved at the same time, so configuration of the whole protection system for the component being protected can’t be complicated. Through improving means of on-line self-checking and monitoring system in digital protection system and human reliability, the real application of CBM can decrease hidden failure state probability. Only through this way can we assure that the protection systems work in good state. It has a certain reference value to protection system reliability engineering.展开更多
In the past few decades,high-speed trains have witnessed tremendous and vigorous development with the appearance of the oil crisis and industrialization,which became a significant trend in the transportation industry ...In the past few decades,high-speed trains have witnessed tremendous and vigorous development with the appearance of the oil crisis and industrialization,which became a significant trend in the transportation industry the world over.With the increase of high-speed railway mileage,the amount of high-speed train has grown sharply,the service life of the trains has increased gradually and the components of the vehicle traction system have become worn and aged as a result.Therefore,advanced maintenance technology and its application are key factors to reduce maintenance cost,human resource input and ensure safe,stable and reliable operation of trains.This paper summarizes and discusses the development,application mode,maintenance management and maintenance technology of high-speed railways of the major countries in the world,especially discusses the condition-based maintenance and the key technology of the traction electrical system,and offers the prospect of research direction and the development of traction maintenance technology.展开更多
The volume of rail traffic was increased by 5 % from 2006 to 2010, in Sweden, due to increased goods and passenger traffic. This increased traffic, in turn, has led to a more rapid degradation of the railway track, wh...The volume of rail traffic was increased by 5 % from 2006 to 2010, in Sweden, due to increased goods and passenger traffic. This increased traffic, in turn, has led to a more rapid degradation of the railway track, which has resulted in higher maintenance costs. In general, degradation affects comfort, safety, and track quality, as well as, reliability, availability, speed, and overall railway performance. This case study investigated the needs of railway stakeholders responsible for analysing the track state and what information is necessary to make good maintenance decisions. The goal is to improve the railway track per- formance by ensuring increased availability, reliability, and safety, along with a decreased maintenance cost. Inter- views of eight experts were undertaken to learn of general areas in need of improvement, and a quantitative analysis of condition monitoring data was conducted to find more specific information. The results show that by implement- ing a long-term maintenance strategy and by conducting preventive maintenance actions maintenance costs would be reduced. In addition to that, problems with measured data, missing data, and incorrect location data resulted in increased and unnecessary maintenance tasks. The conclusions show that proactive solutions are needed to reach the desired goals of improved safety, improved availability, and improved reliability. This also includes thedevelopment of a visualisation tool and a life cycle cost model for maintenance strategies.展开更多
Condition-based maintenance(CBM)detects early signs of failure and dictates when maintenance should be performed based on the actual condition of a system.In this paper,we first review some of the recent research on C...Condition-based maintenance(CBM)detects early signs of failure and dictates when maintenance should be performed based on the actual condition of a system.In this paper,we first review some of the recent research on CBM under various physical structures and signal data.Then,we summarize several kinds of prognostic models that use monitoring information to estimate the reliability of complex systems or products.Monitoring information also facilitates operational decisions in production planning,spare parts management,reliability improvement,and prognostics and health management.Finally,we suggest some research opportunities for the reliability and operations management communities to fill the research gap between these two fields.展开更多
A monitoring and comparison experiment with two types of sensors on a turbojet engine is carried out. Compared with a probe-typed sensor,which is designed successfully before,signals are collected to verify the validi...A monitoring and comparison experiment with two types of sensors on a turbojet engine is carried out. Compared with a probe-typed sensor,which is designed successfully before,signals are collected to verify the validity and better feasibility of the circular sensor.According to the signals monitored over 131h,the typical signals of 125—129 phases are analyzed.The results show that the unusual exhaust particles are carbon depositions from fuel spray nozzle.Therefore,with the electrostatic sensor,early warning can be provided for initial fault condition, as well as real-time reference for the condition-based maintenance.展开更多
A proactive approach is constructed to cope with the integrated problem of batch production and maintenance in a deteriorating system. The condition of the system is modeled by a proportional hazards model(PHM) which ...A proactive approach is constructed to cope with the integrated problem of batch production and maintenance in a deteriorating system. The condition of the system is modeled by a proportional hazards model(PHM) which considers both system deterioration state and usage. The deterioration state of system is uncertain and is only observed between batches. An integration model for optimizing production plan and conditionbased maintenance(CBM) policy is proposed, in which the maintenance threshold and production quantity are proactively decided simultaneously. To obtain a robust solution with minimal cost over the planning horizon, a simulation-based iterative algorithm is developed to solve the complicated non-linear model. Numerical results show that the performance of the developed approach is satisfactory under uncertainty.展开更多
基金supported by the National watural Science Foundation of China (60904002)
文摘A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.
基金the National Natural Science Foundation of China(60672164)the National High Technology Research and Development Program of China(863Program)(2006AA04Z427)~~
文摘To provide some feasible condition-based maintenance （CBM） decision making methods for civil aeroengine, firstly, the theory of aeroengine CBM decision making is described. The proportional intensity（PI） model is established based on the reliability and condition monitoring data. According to the model, the decision making methods are proposed for the optimal preventive maintenance（PM） interval and removal. Then, the time on wing （TOW） is predicted by collecting actual data based on the engine age and operating conditions. Finally, an example of a fleet for CF6-80C2 engines is illustrated. It shows that sufficient engine operation data are the key of accurate decision making. Results indicate that the CBM decision making methods are helpful for engineers in airlines to control engine maintenance actions and TOW, thus decreasing risks and maintenance costs.
基金partially supported by the National Natural Science Foundation of China(No.61803121)China Postdoctoral Science Foundation(No.2019M651277).
文摘The reliability of the on-wing aircraft Auxiliary Power Unit(APU)decides the cost and the comfort of flight to a large degree.The most important function of APU is to help start main engines by providing compressed air.Especially on the condition of sudden shutdown in the air,APU can offer additional thrust for landing.Therefore,its condition monitoring has drawn much attention from the academic and industrial field.Among the on-wing sensing data which can reflect its condition,Exhaust Gas Temperature(EGT)is one of the most important parameters.To ensure the reliability of EGT,one kind of data-driven anomaly detection framework for EGT sensing data is proposed based on the Gaussian Process Regression and Kernel Principal Component Analysis.The situations of one-dimensional and two-dimensional input data for EGT anomaly detection are considered,respectively.The cross-validation experiments are carried out by utilizing the real condition data of APU,which are provided by China Southern Airlines Company Limited Shenyang Maintenance Base.The anomalous stuck condition of EGT sensing data is also detected.Experimental results show that the proposed EGT sensing data anomaly detection method can achieve better performance of false positive ratio,false negative ratio and accuracy.
基金supported by the National Key R&D Program of China(Grant No.2022YFE0114100)the National Key R&D Program of China(Grant No.2017YFE0101400).
文摘The exploration of component states for optimizing maintenance schedules in complex systems has garnered significant interest from researchers.However,current literature usually overlooks the critical aspects of system flexibility and reconfigurability.Judicious implementation of system reconfiguration can effectively mitigate system downtime and enhance production continuity.This study proposes a dynamic condition-based maintenance policy considering reconfiguration for reconfigurable systems.A double-layer decision rule was constructed for the devices and systems.To achieve the best overall maintenance effect of the system,the remaining useful life probability distribution and recommended maintenance time of each device were used to optimize the concurrent maintenance time window of the devices and determine whether to reconfigure them.A comprehensive maintenance efficiency index was introduced that simultaneously considered the maintenance cost rate,reliability,and availability of the system to characterize the overall maintenance effect.The reconfiguration cost was included in the maintenance cost.The proposed policy was tested through numerical experiments and compared with different-level policies.The results show that the proposed policy can significantly reduce the downtime and maintenance costs and improve the overall system reliability and availability.
基金supported by Basic Science Research Program through the National Natural Science Foundation of China(Grant No.61867003)Key Project of Science and Technology Research and Development Plan of China Railway Co.,Ltd.(N2022X009).
文摘Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues.Hence,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue.Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions computing.The simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their lifespan.Compared with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.
基金supported by the National Natural Science Foundation of China(61873122)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.
基金supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, StateEducation Ministry.
文摘The evolution of maintenance management is briefly introduced in this paper, from corrective maintenance to preventive maintenance. First, a range of condition monitoring and fault diagnosis techniques developed in different industries are surveyed; Second, many methods of condition monitoring are presented; Third, mathematical methods used in condition monitoring are given; Then the merits and shortcomings are discussed. Efficient maintenance policies are of fundamental importance in system engineering because of their fallbacks into the safety and economics of plant operation. Applying condition-based maintenance to a system can reduce the cost and extend the availability of facilities. With the advent of personal computers as fast and cost effective machines for data acquisition and processing of multiple signals some shortcomings mentioned in condition monitoring could be solved or reduced to some extent. These PCs can be a solution as a condition monitoring based maintenance system.
文摘The present work adopted Reliability Centered Maintenance (RCM) methodology to evaluate marginal oilfield Early Production Facility (EPF) system to properly understand its functional failures and to develop an efficient maintenance strategy for the system. The outcome of the RCM conducted for a typical EPF within the Niger Delta zone of Nigeria provides an indication of equipment whose failure can significantly affect operations at the production facility. These include the steam generation unit and the wellhead choke assembly, using a risk-based failure Criticality Analysis. Failure Mode and Effect Analysis (FMEA) was conducted for the identified critical equipment on a component basis. Each component of the equipment was analyzed to identify the failure modes, causes and the effect of the failure. The outcome of the FMEA analysis aided the development of a robust maintenance management strategy, which is based on an optimized mix of corrective, preventive and condition-based monitoring maintenance for the marginal oilfield EPF.
基金performed within the project ARCWIND-adaptation and implementation of floating wind energy conversion technology for the Atlantic region-which is co-financed by the European Regional Development Fund through the Interreg Atlantic Area Program under contract EAPA 344/2016
文摘The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis and prognosis, and maintenance optimization. Relevant academic research and industrial applications are identified and summarized. The state of art, capabilities,and constraints of condition-based maintenance are analyzed. The presented research demonstrates that the intelligent-based approach has become a promising solution for condition recognition, and an integrated data platform for offshore wind farms is significant to optimize the maintenance activities.
文摘At present, condition monitoring and fault diagnosis technology and their application in engineering have been widely studied. Relatively little attention has been paid to condition-based maintenance decision-making for equipment. In this paper,based on the decision-making policy in traditional condition-based maintenance,the connotation of condition-based maintenance for equipment was defined, and its characteristics were analyzed.Working contents of condition-based maintenance for equipment were provided,which were divided into three stages. The influence factors in condition-based maintenance for equipment were analyzed. The key links of equipment maintenance contents and decision-making process were proposed. The condition-based maintenance decision-making policy presented in this paper can provide a practical reference for equipment maintenance.
文摘With the further development of service-oriented,performance-based contracting(PBC)has been widely adopted in industry and manufacturing.However,maintenance optimization problems under PBC have not received enough attention.To further extend the scope of PBC’s application in the field of maintenance optimization,we investigate the condition-based maintenance(CBM)optimization for gamma deteriorating systems under PBC.Considering the repairable single-component system subject to the gamma degradation process,this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC.In the proposed CBM model,the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate.Then,a particle swarm algorithm(PSO)and related solution procedure are presented to solve the multiple decision variables in our proposed model.In the end,a numerical example is provided so as to demonstrate the superiority of the presented model.By comparing the proposed policy with the conventional ones,the superiority of our proposed policy is proved,which can bring more profits to providers and improve performance.Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy.A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.
基金supported by the National Natural Science Foundation of China under Grant No.12172100.
文摘In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Considering the structure of multi-component systems,the maintenance strategy is determined according to the importance of the components.The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements.First,multi-component models are grouped.Then,a failure probability model of multi-component systems is established.The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.Second,the component importance indicator is introduced into the grouping model,and the optimization model,which aimed at a maximum economic profit,is established.A genetic algorithm is used to solve the non-deterministic polynomial(NP)-complete problem in the optimization model,and the optimal grouping is obtained through the initial grouping determined by random allocation.An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy,and the influence of the system structure and the parameters on the maintenance strategy is discussed.
文摘Condition based maintenance(CBM) is one of the solutions to machinery maintenance requirements. Latest approaches to CBM aim at reducing human engagement in the real-time fault detection and decision making. Machine learning techniques like fuzzy-logic-based systems, neural networks, and support vector machines help to reduce human involvement. Most of these techniques provide fault information with 100% confidence. It is undeniably apparent that this area has a vast application scope. To facilitate future exploration, this review is presented describing the centrifugal pump faults, the signals they generate, their CBM based diagnostic schemes, and case studies for blockage and cavitation fault detection in centrifugal pump(CP) by performing the experiment on test rig. The classification accuracy is above 98% for fault detection. This review gives a head-start to new researchers in this field and identifies the un-touched areas pertaining to CP fault diagnosis.
文摘Aiming at digital relay protection system, a novel hidden failure Markov reliability model is presented for a single main protection and double main protection systems according to hidden failure and protection function under Condition-Based Maintenance (CBM) circumstance and reliability indices such as probability of protection system hidden failure state are calculated. Impacts of different parameters (containing impacts of human errors) to hidden failure state probability and the optimal measures to improve reliability by variable parameter method are also analyzed. It’s demonstrated here that: Compared to a single main protection, double main protection system has an increased hidden failure probability, thus the real good state probability decreases, two main protections’ reliability must be improved at the same time, so configuration of the whole protection system for the component being protected can’t be complicated. Through improving means of on-line self-checking and monitoring system in digital protection system and human reliability, the real application of CBM can decrease hidden failure state probability. Only through this way can we assure that the protection systems work in good state. It has a certain reference value to protection system reliability engineering.
文摘In the past few decades,high-speed trains have witnessed tremendous and vigorous development with the appearance of the oil crisis and industrialization,which became a significant trend in the transportation industry the world over.With the increase of high-speed railway mileage,the amount of high-speed train has grown sharply,the service life of the trains has increased gradually and the components of the vehicle traction system have become worn and aged as a result.Therefore,advanced maintenance technology and its application are key factors to reduce maintenance cost,human resource input and ensure safe,stable and reliable operation of trains.This paper summarizes and discusses the development,application mode,maintenance management and maintenance technology of high-speed railways of the major countries in the world,especially discusses the condition-based maintenance and the key technology of the traction electrical system,and offers the prospect of research direction and the development of traction maintenance technology.
文摘The volume of rail traffic was increased by 5 % from 2006 to 2010, in Sweden, due to increased goods and passenger traffic. This increased traffic, in turn, has led to a more rapid degradation of the railway track, which has resulted in higher maintenance costs. In general, degradation affects comfort, safety, and track quality, as well as, reliability, availability, speed, and overall railway performance. This case study investigated the needs of railway stakeholders responsible for analysing the track state and what information is necessary to make good maintenance decisions. The goal is to improve the railway track per- formance by ensuring increased availability, reliability, and safety, along with a decreased maintenance cost. Inter- views of eight experts were undertaken to learn of general areas in need of improvement, and a quantitative analysis of condition monitoring data was conducted to find more specific information. The results show that by implement- ing a long-term maintenance strategy and by conducting preventive maintenance actions maintenance costs would be reduced. In addition to that, problems with measured data, missing data, and incorrect location data resulted in increased and unnecessary maintenance tasks. The conclusions show that proactive solutions are needed to reach the desired goals of improved safety, improved availability, and improved reliability. This also includes thedevelopment of a visualisation tool and a life cycle cost model for maintenance strategies.
基金This work is supported by National Natural Science Foundation of China under grants 71531010 and 71831006.
文摘Condition-based maintenance(CBM)detects early signs of failure and dictates when maintenance should be performed based on the actual condition of a system.In this paper,we first review some of the recent research on CBM under various physical structures and signal data.Then,we summarize several kinds of prognostic models that use monitoring information to estimate the reliability of complex systems or products.Monitoring information also facilitates operational decisions in production planning,spare parts management,reliability improvement,and prognostics and health management.Finally,we suggest some research opportunities for the reliability and operations management communities to fill the research gap between these two fields.
基金Supported by the National Natural Science Foundation of China(60939003,61079013)the Natural Science Fund Project in Jiangsu Province(BK2011737)the Fundamental Research Funds for the Central Universities(NS2012059)
文摘A monitoring and comparison experiment with two types of sensors on a turbojet engine is carried out. Compared with a probe-typed sensor,which is designed successfully before,signals are collected to verify the validity and better feasibility of the circular sensor.According to the signals monitored over 131h,the typical signals of 125—129 phases are analyzed.The results show that the unusual exhaust particles are carbon depositions from fuel spray nozzle.Therefore,with the electrostatic sensor,early warning can be provided for initial fault condition, as well as real-time reference for the condition-based maintenance.
基金the National Natural Science Foundation of China(Nos.61473211 and 71171130)
文摘A proactive approach is constructed to cope with the integrated problem of batch production and maintenance in a deteriorating system. The condition of the system is modeled by a proportional hazards model(PHM) which considers both system deterioration state and usage. The deterioration state of system is uncertain and is only observed between batches. An integration model for optimizing production plan and conditionbased maintenance(CBM) policy is proposed, in which the maintenance threshold and production quantity are proactively decided simultaneously. To obtain a robust solution with minimal cost over the planning horizon, a simulation-based iterative algorithm is developed to solve the complicated non-linear model. Numerical results show that the performance of the developed approach is satisfactory under uncertainty.
