Basic Concept and Theoretical Study of Condition-based Maintenance for Power Transmission System

状态检修背景下,为解决电网运行整体与输变电设备个体之间的矛盾和冲突,在已有研究成果基础上,提出电网状态检修的概念,在输变电设备状态检修决策过程中,给出电网故障风险和电网检修风险的定义以及相应的量化表达式。依据设备状态预测,以电网故障风险和电网检修风险的和最小为目标,将设备检修、运行以及电网整体性能在概率引导下相互牵制,形成电网状态检修的数学模型,并给出相应的解决方法。最后,为验证该理论研究的可行性,分别以可靠性测试系统RBTS-BUS6和IEEE-RTS79系统为例,对各种情况进行分析,体现了预期的效果,并期望为电网检修与运行协调决策理论的深入研究提供必要的理论基础。

Condition-based maintenance policy for gamma deteriorating systems

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.

Condition-Based Maintenance Decision-Making for Equipment

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.

Joint optimization of sampling interval and control for condition-based maintenance using availability maximization criterion

Most of the maintenance optimization models in condition-based maintenance(CBM) consider the cost-optimal criterion, but few papers have dealt with availability maximization for maintenance applications. A novel optimal Bayesian control approach is presented for maintenance decision making. The system deterioration evolves as a three-state continuous time hidden semi-Markov process. Considering the optimal maintenance policy, the multivariate Bayesian control scheme based on the hidden semi-Markov model(HSMM) is developed, the objective is to maximize the long-run expected average availability per unit time. The proposed approach can optimize the sampling interval and control limit jointly. A case study using Markov chain Monte Carlo(MCMC)simulation is provided and a comparison with the Bayesian control scheme based on hidden Markov model(HMM), the age-based replacement policy, Hotelling’s T2, multivariate exponentially weihted moving average(MEWMA) and multivariate cumulative sum(MCUSUM) control charts is given, which illustrates the effectiveness of the proposed method.

Overview of the Importance of Intelligent Approaches on Machinery Faults Diagnosis and Prediction Based on Prognostic and Health Management/Condition-Based Maintenance

Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.

Maintenance and Condition-Based Maintenance

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.

Condition-Based Diagnostic Approach for Predicting the Maintenance Requirements of Machinery

Wise maintenance-procedures are essential for achieving high industrial productivities and low energy expenditure. A major part of the energy used in any production process is expended during the maintenance of the employed equipment. To ensure plant reliability and equipment availability, a condition-based maintenance policy has been developed in this investigation. In particular, this project explored the use of vibration parameters in the diagnosis of equipment failure. A computer-based diagnostic tool employing an artificial neural-network (ANN) was developed to analyse the ensuing machinery faults, their causes and consequences. For various categories of this type of machinery, a vibration-severity chart (ISO 12372 / BS 4675: 1971) appropriately colour coded according to defined mechanical faults, was used in training of the ANN. The model was validated using data obtained from a centrifugal pump on full load and fed into the program written in Visual Basic. The results revealed that, for centrifugal pumps within 15 to 300kw power range, vibration-velocity amplitude of between 0.9 and 2.7mm/s was within acceptable limits. When the values rose to between 2.8 and 7.0mm/s, closer monitoring and improved understanding of the equipment condition was needed. The evolved diagnostic and prognostic model is applicable for other rotary equipment that is used within the same power limits.

Overview of Condition-Based Maintenance Decision-Making Optimization Modeling of Multi-component System

Overview about three key contents of condition-based maintenance decision-making of a multi-component system is analyzed based on maintenance optimization and modeling. The component deterioration model, the correlation between the degraded components and the system configuration are analyzed separately in the deterioration model of multi-component system.For the maintenance polices,the opportunistic maintenance( OM)policy and the grouping maintenance( GM) policy are analyzed and summarized in combination with the condition-based maintenance( CBM) modeling of multi-component system. It is put forward that CBM modeling of multi-component system should be further researched based on the inspection interval and the maintenance threshold of multi-component system in availability.

Analysis of Condition-Based Maintenance for High-Valtage Electric Power

The development process of high-voltage electric power equipment maintenance was introduced. It is pointed out that the trend of high-voltage electric power equipment maintenance is so called condition-based maintenance. With the development of computer technology and sensors, on-line monitoring of high-voltage electric power equipment has developed rapidly. By introducing the main principle of Schering bridge to measure tanδ, the way of on-line monitoring of high-voltage electric power equipment was explained. Difference methods of on-line monitoring of insulation parameters for 35 kV substation were discussed. Finally, the shortcomings as well as its tendency of on-line monitoring were analyzed.

Development of Maintenance Management Strategy Based on Reliability Centered Maintenance for Marginal Oilfield Production Facilities

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.

SOMS: A Subway Operation and Maintenance System Based on Planned Maintenance Model with Train State

This paper aims to propose a modeling framework for subway operation and maintenance system (SOMS), which analyzes the train condition data based on both train sensor network data and basis train maintenance plan. The system is formulated into five function modules, and the research problem is to determine one auxiliary maintains plan, including the time allocation and frequency of maintenance. The case of Guangzhou metro is conducted to illustrate the applicability of SOMS, and the results reveal a number of interesting insights into subway maintenance system, i.e., the worksheet can reduce duplication of redundant maintenance work, the repair cost, and the damage caused by frequent disassembly.

Remaining useful life estimation based on Wiener degradation processes with random failure threshold

Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.

Proactive Approach for Production and Condition-Based Maintenance Integration Problem in a Deteriorating System

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.

Modeling on Spare Parts Inventory Control Under Condition Based Maintenance Strategy

In order to optimize the spare parts inventory, we present a decision-making model under condition based maintenance policy for a single equipment system subjected to continuous and random deterioration. Firstly,a probability model of the spare parts support is established, according to the requirement of a predetermined probability of stockout. It can determine the optimal spare parts stock level. Secondly, the spare parts ordering decision is made according to the equipment deterioration level, and it can optimize the spare parts ordering. The objectives of this model are to minimize the spare parts inventory, and the expected total operating cost. Thirdly,a numerical example is given to illustrate this model. The results prove that the optimal preventive maintenance threshold obtained from the proposed model can satisfy the spare parts support requirements.

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

With the continuous expansion of power distribution grid, the number of distribution equipments has become larger and larger. In order to make sure that all the equipments can operate reliably, a large amount of maintenance tasks should be conducted. Therefore, maintenance scheduling of distribution network is an important content, which has significant influence on reliability and economy of distribution network operation. This paper proposes a new model for maintenance scheduling which considers load loss, grid active power loss and system risk as objective functions. On this basis, Differential Evolution algorithm is adopted to optimize equipment maintenance time and load transfer path. Finally, the general distribution network of 33 nodes is taken for example which shows the maintenance scheduling model’s effectiveness and validity.

Machinery and Equipment Maintenance Strategy and Choice

The advantages, disadvantages and characteristics of various maintenance strategies for modern mechanical equipment are analyzed. Combined with the system structure and functional characteristics of engineering equipment,it puts forward the selection method of maintenance strategies for different types of equipment and failure modes. The view of this article is that the comprehensive maintenance strategy, which is based on condition based maintenance(CBM) and combines various maintenance strategies. This will become the main development direction of engineering equipment maintenance.

Study on the Methods of Equipment Maintenance Management

This thesis discusses the importance of equipment maintenance management, then introduces the development tendency of equipment maintenance management. In the end it analyses and studies the design of a computerized maintenance management system, which offers an integration technique.

Optimal Maintenance Modeling for Systems with Multiple Non-Identical Units Using Extended DSSP Method

In the optimal maintenance modeling, all possible maintenance activities and their corresponding probabilities play a key role in modeling. For a system with multiple non-identical units, its maintenance requirements are very complicated, and it is time-consuming, even omission may occur when enumerating them with various combinations of units and even with different maintenance actions for them. Deterioration state space partition (DSSP) method is an efficient approach to analyze all possible maintenance requirements at each maintenance decision point and deduce their corresponding probabilities for maintenance modeling of multi-unit systems. In this paper, an extended DSSP method is developed for systems with multiple non-identical units considering opportunistic, preventive and corrective maintenance activities for each unit. In this method, different maintenance types are distinguished in each maintenance requirement. A new representation of the possible maintenance requirements and their corresponding probabilities is derived according to the partition results based on the joint probability density function of the maintained system deterioration state. Furthermore, focusing on a two-unit system with a non-periodical inspected condition-based opportunistic preventive-maintenance strategy;a long-term average cost model is established using the proposed method to determine its optimal maintenance parameters jointly, in which “hard failure” and non-negligible maintenance time are considered. Numerical experiments indicate that the extended DSSP method is valid for opportunistic maintenance modeling of multi-unit systems.

计及劣化状态和随机故障的光伏发电系统视情维修模型以及最优检修策略

针对现有光伏发电系统维修策略研究中通常仅考虑劣化状态导致维修决策不合理等问题,提出了一种计及劣化状态和随机故障的光伏发电系统视情维修模型及最优检修策略。首先,以离散状态下的Markov过程为基础,将随机故障对维修策略的影响引入到光伏发电系统视情维修建模中,建立光伏发电系统计及劣化状态和随机故障状态的视情维修模型,定期检测光伏发电系统的状态。当系统状态超过预防性维修阈值时进行不完全维修;出现随机故障时进行最小维修;达到故障状态时进行更换。然后,以光伏发电系统长期稳定运行的最小总成本率为目标,采用一种改进的黏菌优化算法求取光伏发电系统最佳检测周期和预防性维修阈值。最后,以某光伏发电系统为例,通过对模型参数的灵敏度分析和传统不考虑随机故障维修模型的对比研究,验证了所提模型及策略的有效性和可行性。

正态型寿命分布设备的可用性分析

设备可用性的解析计算方法具有过程直接、结果准确的优点,但其建模过程复杂,目前研究相对较少,而多采用随机过程或仿真的方法进行分析。针对寿命服从正态分布的设备,考虑预防性维修与视情维修情形,推导出设备使用可用度与瞬时可用度的解析求解方法,模拟设备的工作与维修过程,构建了设备使用可用度与瞬可时用度的仿真分析方法。采用不同寿命分布参数的设备进行算例验证,结果表明两种方法具有较好的一致性,可为正态型寿命分布设备的预防性维修与视情维修方案评价与优化提供技术途径。