Reasonable Maintenance Strategy Research Articles

Research on imperfect condition-based maintenance strategy based on accelerated degradation process

To address the situation that the degraded system cannot be repaired as new and the degradation is accelerated after repair in engineering practice, an imperfect condition-based maintenance model is proposed based on the Gamma process by introducing the maintenance improvement factor and the accelerated degradation factor. The maintenance improvement factor describes the recovery degree of the degradation amount after imperfect maintenance, then gives a quantitative representation method of the system maintenance improvement effect and the determination method of the maximum number of imperfect maintenance. The accelerated degradation factor is combined with the geometric process to describe the accelerated degradation process of the system after imperfect maintenance. The Monte Carlo method is used to determine the optimal number of imperfect preventive maintenance decisions. Through the demonstration of calculation examples, the influence of accelerated degradation factor and maintenance improvement factor on the long-term operation maintenance rate and the optimal number of imperfect maintenance is analyzed. The results show that the model can more comprehensively describe the degradation and maintenance process of degraded systems, and it can effectively reduce maintenance cost ratio under long-term operation. It provides a certain theoretical support for formulating an economical and reasonable maintenance strategy that is more in line with the actual degradation and maintenance process in engineering practice.

Preventive maintenance optimization for key components of subway train bogie with consideration of failure risk

With the acceleration of urbanization, the number of urban rail transit trains has increased dramatically, and the economy and safety of subway trains have become important standards. As an essential subsystem of the subway train, the bogie has a long maintenance process and serious failure consequences. So, it is essential to formulate a reasonable maintenance strategy to ensure its operation. To solve the above problems, a preventive maintenance (PM) strategy for key components of train bogie is established with consideration of failure risk in this paper. Firstly, the failure risk factors of the bogie components are scored and weighted, and the failure risk cost model and PM cost model are established. Next, a Weibull distribution parameter estimation method for bogie components based on the improved beluga whale optimization algorithm (IBWO) is proposed, providing a theoretical basis for PM decision-making optimization. Then, the Lévy flight is introduced into particle swarm optimization to enhance the optimization performance of the model and obtain the optimal solution. Finally, the bogie key components of Nanning Metro line 1 are selected as a case study. The results show that the IBWO algorithm has strong applicability and feasibility, and can accurately calculate the Weibull parameter values of the bogie key components. Compared with the PM plan without considering the failure risk, the proposed method is more economical and safer, which can provide necessary theoretical support for the maintenance decision optimization of urban rail transit train components.

RUL prediction for AECs of power electronic systems based on machine learning and error compensation

Aluminum electrolytic capacitor (AEC) is one of the most pivotal components that affect the reliability of power electronic systems. The electrolyte evaporation and dielectric degradation are the two main reasons for the parametric degradation of AEC. Remaining useful life (RUL) prediction for AEC is beneficial for obtaining the health state in advance and making reasonable maintenance strategies before the system suffers shutdown malfunction, which can increase the reliability and safety. In this paper, a hybrid machine learning (ML) model with GRU and PSO-SVR is proposed to realize the RUL prediction of AEC. The GRU is used for the recursive multi-step prediction of AEC to model the times series of AEC, SVR optimized by PSO for hyper-parameters is applied for error compensation caused by recursive GRU. Finally, the proposed model is validated by two kinds of data sets with accelerated degradation experiments. Compared with the other methods, the results show that the proposed scheme can obtain greater prediction performance index of RUL under different prediction time points, which can support the technology of health management for power electronic system.

Classification of the wind turbine components based on importance degrees: A three-way decision perspective

The bad working environment and various complex influencing factors lead to the high failure rate of a wind turbine. It is necessary to decide on a reasonable maintenance strategy for wind turbines. The classification of wind turbine components based on their importance degrees can identify the components which have an important impact on the reliability and maintenance of wind turbines. However, the traditional multi-criteria decision-making method can only provide the importance ranking of components, rather than the importance classification of components. The emergence of the three-way decision (TWD) method makes up for this deficiency. Then we classify the importance degrees of components by the TWD method. Firstly, the decision-theoretic rough sets are introduced into the uncertain linguistic setting to construct uncertain linguistic decision-theoretic rough sets. Secondly, the weights of experts are attained based on the consistency degree of loss functions. Thirdly, conditional probability is attained by the evaluation based on distance from the average solution method. And the classification of wind turbine components is derived based on the minimum-loss principle. Finally, a case study about the classification of the wind turbine components based on importance degrees is employed to certify the practicability of our designed method. The proposed model extends both the theory and practice of TWD and offers a classification helpful to make maintenance strategies for reducing the risk of component failure.

Multistep prediction of remaining useful life of proton exchange membrane fuel cell based on temporal convolutional network

ABSTRACT Proton-exchange membrane fuel cells (PEMFCs), as potential energy converters with broad application prospects, have low durability owing to several factors that make it difficult to quantify the degradation of PEMFC components. The accurate prediction of the remaining useful life (RUL) can help users understand the degradation status of PEMFCs and adopt reasonable maintenance strategies to improve durability. This paper proposes an RUL prediction framework based on a temporal convolutional network (TCN). First, an equivalent circuit model of the PEMFC is established, and complex nonlinear least squares regression is used to fit the model to estimate the polarization resistance. Then, the prediction framework and joint degradation indicator of the TCN are constructed to predict the RUL. The TCN is compared with four models: linear regression, Holt–Winters, seasonal autoregressive integrated moving average, and Prophet. The results show that the TCN performs significantly better in terms of all the predictive metrics, including the root-mean-squared error which is at least 13.43% lower than those of the four models. The RUL prediction accuracy of the TCN is at least 7.76% higher than that of the four models. Except at 800 h, the average RUL accuracy of TCN is 92.20%. This confirms that the TCN (double variables) can accurately predict the RUL of PEMFCs.

Integrated Structural Dependence and Stochastic Dependence for Opportunistic Maintenance of Wind Turbines by Considering Carbon Emissions

Wind turbines have a wide range of applications as the main equipment for wind-power generation because of the rapid development of technology. It is very important to select a reasonable maintenance strategy to reduce the operation and maintenance costs of wind turbines. Traditional maintenance does not consider the environmental benefits. Thus, for the maintenance problems of wind turbines, an opportunistic maintenance strategy that considers structural correlations, random correlations, and carbon emissions is proposed. First, a Weibull distribution is used to describe the deterioration trend of wind turbine subsystems. The failure rates and reliability of wind turbines are described by the random correlations among all subsystems. Meanwhile, two improvement factors are introduced into the failure rate and carbon emission model to describe imperfect maintenance, including the working-age fallback factor and the failure rate increasing factor. Then, the total expected maintenance cost can be described as the objective function for the proposed opportunistic maintenance model, including the maintenance preparation cost, maintenance adjustment cost, shutdown loss cost, and operation cost. The maintenance preparation cost is related to the economic correlation, and the maintenance adjustment cost is described by using the maintenance probabilities under different maintenance activities. The shutdown loss cost is obtained by considering the structural correlation, and the operation cost is related to the energy consumption of wind turbines. Finally, a case study is provided to analyze the performance of the proposed model. The obtained optimal opportunistic maintenance duration can be used to interpret the structural correlation coefficient, random correlation coefficient, and sensitivity of carbon emissions. Compared with preventive maintenance, the proposed model provides better performance for the maintenance problems of wind turbines and can obtain relatively good solutions in a short computation time.

Study on the preventive maintenance of the cabin structure based on the markov chain

In view of the complex structure and the different damage situations of the cabin, the Markov state transition model was established considering the crack propagation at the damaged sites. The state transition probability matrix of related crack propagation was constructed using the equation of linear elastic facture mechanics to simulate the deterioration process of the main structural parts during navigation. Secondly, the maintenance matrix was added to the state transition model, and the distribution probability of the system state was predicted by the periodicity of Markov chain, formulating a reasonable maintenance strategy. Finally, the practicability of the preventive maintenance strategy was verified taking the marine oil FPSO 116 as the example. The maintenance plan formulated according to the calculation results could reduce the damage of the hull theoretically, preventing the occurrence of unexpected deterioration states, prolonging the service life of the hull, and providing a strategic reference for the formulation of the maintenance plans of the hull.

Preventive Maintenance Strategy of Gasifier Refractory Brick Based on State Recognition

In order to ensure the normal and safe operation of gasifier, it is necessary to ensure that the remaining life of refractory brick, the key component of gasifier, is in a healthy range, so it is necessary to formulate a timely and reasonable maintenance strategy for refractory brick. In order to avoid the problem of excessive Maintenance and insufficient Maintenance, CBM (Condition Based Maintenance) related research on gasifier refractory brick. This article first to identify the current state of the gasifier refractory brick, and then based on this state for different refractory brick their preventive maintenance strategy, can largely avoid excessive problem, lack of maintenance and repair in a timely manner to maintain the gasifier refractory reasonably, to extend its service life, guaranteeing the normal safe operation of the gasifier.

Effect of bottleneck-causing clogging on infiltration-runoff of pervious concrete pavement system

A pervious concrete pavement system (PCPS) is susceptible to clogging. In this study, a laboratory study was performed to measure the effects of clogging on the infiltration-runoff process by monitoring the water contents at four vertical locations in PCPSs with varying clogging degrees, exposed to different rainfall intensities. The measurements show that clogging tends to cause an infiltration bottleneck (located between 5 and 15 cm from the PCPS surface), which is the major contributor to the earlier occurrence of runoff. Moreover, bottleneck-causing clogging can change the runoff pattern from stored-full runoff to infiltration excess runoff. After this change, the water storage capacity of the PCPS cannot be fully utilised, and the beneficial effect of the PCPS on hydrology declines greatly. The results obtained are important for improving the understanding of clogging of the entire PCPS, which can help design better PCPSs and develop reasonable maintenance strategies.

Communication Equipment Condition Based Maintenance Decision

In order to develop a scientific and cost reasonable maintenance strategy to solve the current high cost problem of running and maintenance management for communication equipment, introduce the same type set which has the similar running condition with the object set as the reference set and propose a life prediction method for communication equipment. The method solves the similarity factor of life evaluation parameters (running time, times of starting and stopping) in actual and benchmark running condition by using experience running data. In order to accurately calculate the running life of the object set under the actual running conditions and overcome the shortcomings of the traditional artificial statistics, the calculation method of real time and historical life is presented. Then based on the product of the maintenance factor and service factor of running time and the times of starting and stopping, the concept of the key parameters of the decision of condition-based maintenanceequivalent service factor is put forward; According to the relationship between the equivalent service factor in running time and to predict period, four kinds of decision models of condition-based maintenance are established. The historical data of communication equipment running were perioded to predict when given equivalent service factor.

An opportunistic maintenance strategy for offshore wind turbine system considering optimal maintenance intervals of subsystems

Operation and maintenance (O&M) costs account for a large proportion of the total costs for offshore wind energy. Performing a reasonable maintenance strategy is an effective approach to reduce O&M costs and gain more profits. In this paper, an opportunistic maintenance strategy for offshore wind turbine systems considering maintenance intervals of each subsystem is proposed to minimize the total maintenance cost. First, a Non-homogeneous Continuous-Time Markov Process based state transition model is established to study degradation process of subsystems. The influence of maintenance time schedule on the maintenance cost is studied to obtain the optimal maintenance intervals of each subsystems. Then, an opportunistic maintenance model considering economic dependencies between multiple subsystems is proposed to optimize the maintenance strategy by combining maintenance activities of individual subsystems to a grouping maintenance activity. A numerical example is used to indicate the significant effectiveness of the maintenance model. The result shows that the total maintenance cost of an offshore wind turbine system will be reduced by adopting the opportunistic maintenance strategy when compared with conventional preventive maintenance strategy.

State evaluation of relay protection system for state maintenance

Relay protection is the first line of defense for power systems. Its reliable operation is an important guarantee for the safety and stability of power system. At present, Chinese relay protection system has long been implemented with regular planned maintenance and repaired supplemented by after-accident maintenance. This maintenance system has greatly caused the loss and waste of manpower, material resources and financial resources. It is urgently necessary to adopt a reasonable maintenance strategy based on the actual operating state of relay protection. The state maintenance of the relay protection system can formulate the maintenance strategy based on the actual operating state of the relay protection system, which can effectively improve the reliability of the relay protection system. Therefore, this paper studies the state evaluation of the relay protection system for state maintenance. Develop maintenance strategy based on the evaluation results of the current operating state of the protection system. It is of great significance to strengthen the reliability and operation level of the relay protection system and ensure the safe operation of the power grid.

Glucocorticoid, immunosuppressant, hydroxychloroquine monotherapy, or no therapy for maintenance treatment in systemic lupus erythematosus without major organ manifestations.

To study maintenance therapy after achievement of the lowest possible disease activity in systemic lupus erythematosus (SLE) without major organ manifestations. We retrospectively evaluated patients with SLE who visited our hospital from Jan 2015 to Feb 2018 and were taking prednisolone (PSL) < 10mg/day. After excluding those with neuropsychiatric SLE or severe lupus nephritis, patients were divided into four groups according to their maintenance monotherapy treatment, namely, prednisolone (PSL), immunosuppressant (IS), hydroxychloroquine (HCQ), and no drugs. The groups were then compared with regard to cumulative flare rate and changes in SLE Disease Activity Index (SLEDAI). There were 47 patients on PSL, 10 on IS, 5 on HCQ, and 11 on no drugs. Flare rate was higher in the no drug group, and no patients with the IS or HCQ group experienced a flare (p = 0.003). A reduction in SLEDAI was only seen in the IS and HCQ groups (p = 0.05 and p = 0.03, respectively). There were no differences in adverse events among groups during the study period. Our results suggest that the cessation of all drugs is associated with disease flare for SLE patients without major organ manifestations. IS or HCQ monotherapy might be a reasonable maintenance strategy comparing with steroid monotherapy. Key Point • Immunosuppressant or hydroxychloroquine monotherapy appears to be a reasonable maintenance strategy.

Power Transformer Condition Assessment Using Extension Hierarchy and A.J. Klee Method

To achieve a more accurate assessment of the transformer condition is of great significance for the reasonable maintenance strategies. Aiming at the transformer complex fault mechanism and the difficulty of objective assessment, a method of transformer condition assessment based on A. J. Klee method and extension hierarchy is proposed, which transforms transformer multi - parameter synthetic evaluation into single - object decision. First, this paper established the hierarchical index system, and divided the condition grade. A. J. Klee method calculated the weight of the indexes. Extension hierarchy determined the comprehensive evaluation level, and the results compared with the fuzzy analytic hierarchy process (FAHP). The case verified the feasibility of the method applied to the evaluation of transformer status. This mothed provides a new assessment strategy for transformer insulation condition maintenance.

A method for determining equipment to be maintained based on comprehensive risk assessment of power system

With the development of on-line monitoring and condition-based maintenance, the optimization research of condition-based maintenance scheduling is getting more and more important. A reasonable maintenance strategy can save a lot of energy and reduce costs. This paper proposes a method to determine the equipment to be maintained, which is based on the comprehensive risk assessment of power system. First we build a mathematical model of maintenance based on comprehensive risk index. Then non-sequential Monte Carlo simulation and DC power flow optimization model are used to minimize the sum of failure risks and maintenance risks. Finally, the feasibility and validity of the proposed model is analyzed on the IEEE-RTS79 system.

基于全寿命周期成本模型的输变电设备检修策略研究

当前电力设备检修策略制定过程中未考虑全寿命周期成本(Life Cycle Cost, LCC)因素，存在着检修策略无法实现经济效益最大化的问题。本文以定期检修和状态维修为例，基于全寿命周期成本模型修正了常用的输变电设备检修策略。在保证系统安全稳定运行的前提下，制定出合理的检修策略，同时实现经济性的目标，具有工程实用性。 The factor of LCC (Life Cycle Cost) is not considered in the present process of making maintenance strategy for power equipment, which leads to the failure of the maintenance strategy to maximize the economic benefits. In this paper, these common maintenance strategies for transmission and transformation equipment are corrected based on the LCC model considering time based mainte-nances and condition based maintenance. On the premise of ensuring the safe and stable operation of the system, some reasonable maintenance strategies of highly valuable in engineering are formulated, and the economic goal is realized.

System Reliability Evaluation Based on Convex Combination Considering Operation and Maintenance Strategy

The approaches to the system reliability evaluation with respect to the cases, where the components are independent or the components have interactive relationships within the system, were proposed in this paper. Starting from the higher requirements on system operational safety and economy, the reliability focused optimal models of multiobjective maintenance strategies were built. For safety-critical systems, the pessimistic maintenance strategies are usually taken, and, in these cases, the system reliability evaluation has also to be tackled pessimistically. For safety-uncritical systems, the optimistic maintenance strategies were usually taken, and, in these circumstances, the system reliability evaluation had also to be tackled optimistically, respectively. Besides, the reasonable maintenance strategies and their corresponding reliability evaluation can be obtained through the convex combination of the above two cases. With a high-speed train system as the example background, the proposed method is verified by combining the actual failure data with the maintenance data. Results demonstrate that the proposed study can provide a new system reliability calculation method and solution to select and optimize the multiobjective operational strategies with the considerations of system safety and economical requirements. The theoretical basis is also provided for scientifically estimating the reliability of a high-speed train system and formulating reasonable maintenance strategies.

The Software Design of Intelligent Diagnosis System for Partial Discharge Fault of GIS

The correct identification of GIS partial discharge type is essential for assessing the insulation status of GIS and developing a reasonable maintenance strategy. After the analysis of the intelligent diagnosis system design, the software architecture of host and remote computer is given by this article. Site host computer completes the data preprocessing and the remote host computer completes the function of real-time observation, data storage and inquiry, spectrum analysis and pattern recognition. The test shows that the software can complete the intelligent recognition of partial discharge.

Cost Modeling and Simulation for Mining Mechanical Equipment Undergoing Maintenance

Based on the time-to-failure density function of parts, the maintenance cost model of mining mechanical equipment is established and simulated. The influence factors of time-to-failure density function on the maintenance costs are analysed and the dynamic changing regularity is investigated, which is significant to establish reasonable maintenance strategies, improve the efficiency of equipment operation, reduce the costs and optimize the design of mechanical equipment parts.

효율적 유지보수를 위한 도시철도 전동차 브레이크의 시스템 신뢰도 최적화

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.