Research on Carbon Emission for Preventive Maintenance of Wind Turbine Gearbox Based on Stochastic Differential Equation

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.

Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions

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.

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.

基于CBM的共用信息系统装备维修保障体系分析与架构设计

随着信息化和数字化技术的不断发展,企业和组织之间信息共享和协作的迫切需求驱使着共用信息系统的产生。企业和组织可以通过共用信息系统装备实现资源的共享和互通,避免信息孤岛和资源浪费,提高信息协同和决策效率。然而环境、人为等因素会导致共用信息系统装备出现故障,使系统无法正常工作。虽然已有相应的装备维修体系,但针对共用信息系统的装备维修方法落后,架构老旧且维修可扩展性低。为解决该问题,以基于状态的维修理论(CBM)为基石,结合模糊理论、灰色模型以及现有共用信息系统维修体系,分析基于CBM的共用信息系统维修保障体系所需功能和流程,构建基于CBM的全新共用信息系统装备维修架构。所提出架构优化了传统装备维修保障模式,为维修管理工作提供了科学的参考依据。

CBM标准化研究现状及发展趋势

基于状态的维护(CBM)是一种新的设备维护模式,建立CBM方式的设备维护系统是一个复杂的系统工程,为规范相关软硬件产品的研制开发、提高不同厂商产品的可互换性与可互操作性,IEEE、ISO、OSA-CBM、MIMOSA等组织相继制定了一些标准,对CBM技术的发展起到了很好的促进作用。本文介绍了国际上CBM标准化研究的现状及相关成果,分析了CBM标准化研究的发展趋势,介绍了作者在CBM研究方面的成果,并对我国CBM标准化研究工作提出了建议。

军队装备维修工程CBM综述

军队维修体制从传统的定期维修、预防性维修向以可靠性维修（reliability centered maintenance，RCM）为指导的状态维修（condition based maintenance，CBM）和设备健康状态管理（equipment health management，EHM）方式过渡，是军队维修工程信息化、智能化管理进程中的必经之路。介绍了状态维修的基本概念及层次结构，对其国内外应用现状及主要应用价值进行了分析，阐述了CBM在我军维修工程中的实施对策及对三级维修体制的影响。

基于CBM策略的航空发动机在翼寿命预测研究

为了给航空公司制定航空发动机拆换计划提供科学合理的依据,基于视情维修方式,对航空发动机的在翼寿命进行了研究。首先,根据发动机历史拆换记录,基于比例危险-比例优势模型建立了发动机维修决策控制限的数学模型。然后,利用基于最小二乘支持向量机的时间序列预测方法对发动机状态参数进行了趋势预测,进而结合维修决策控制限模型便可得到发动机在翼寿命的预测结果。最后通过实例验证了该方法的有效性和实用价值。

基于CBM的航空装备保障费用动态分析

目前航空装备的保障普遍存在保障费用高和装备可用度低的问题。针对视情维修(Condition-based Maintenance,简称CBM)在新一代航空装备中的应用,以保证航空装备的战备完好性,降低维修保障费用为目标,应用系统动力学原理,建立基于视情维修的航空装备保障费用的动态反馈结构模型。仿真结果表明,将视情维修方法应用到航空装备保障,可有效降低保障费用,提高战备完好率。

基于OM与CBM的医疗设备维修决策研究

本文基于医院医疗设备工作对象的特殊性与维修人力资源的匮乏性,针对医疗设备维修的时效性、可靠性和安全性三个要素,从理论上比较了机会维修策略(OM)与视情维修策略(CBM)的优缺点,结合"P—F"曲线,分析医疗设备维修的故障类型、现场要求和维修难度,对医疗设备的维修策略选择进行了研究和探讨,以期达到医疗设备维修的最优化。

基于SOAP的CBM系统通信模型设计与实现

基于状态的维护(CBM)是一种新的设备维护方式,它综合运用多种技术通过对设备工作状态的实时监测来对设备健康状况进行评估并诊断和预测设备未来的有效工作寿命及可能发生的故障。OSA-CBM研究小组制定了一套完整的实现CBM系统的标准框架,该框架根据不同的功能将CBM系统划分成7个模块,每个模块可以作为一个单独的子系统独立开发,独立运行,模块间通过通信实现数据的交换。传统的通信方式存在很多不足,如异构环境中通信实现的复杂性、难以通过防火墙的阻塞等。参照OSA-CBM标准,设计并实现了基于SOAP的CBM系统通信模型。SOAP技术的应用使CBM模块能更好地协同工作,增强了系统的开放性和兼容性,改善了以往模块间单一系统、单一厂商、单一网络的实现机制,弥补了在Internet异构环境中通信困难的不足。

军用装备CBM应用研究

本文在介绍CBM基本原理和应用关键技术的基础上，结合我军现行维修管理体制，采用总体目标驱动，分层逐步实施的思路，设计了军用装备CBM应用流程，明确了组织机构与人员分工，探讨了军用装备CBM应用流程的功能实现，为军用装备采用基于状态的维修方式建立基础，从而提高装备维修效率与效益。

基于逆高斯退化过程的面向任务系统CBM优化模型

针对现有单调退化系统视情维修(condition-based maintenance, CBM)优化模型中不完全维修影响考虑单一,且未同时融入可用度约束的问题,提出一种考虑不完全维修双重影响与可用度约束的单调退化系统CBM优化模型。首先,基于具有随机漂移系数的逆高斯过程,建立系统退化模型并得到相关概率分布;其次,描述任务背景下系统演化过程,建立不完全维修后的剩余损伤模型,提出随机漂移系数更新公式;然后,结合可用度约束给出系统维修或在3种时机更换的概率公式,并建立CBM优化模型;最后,通过数值实验对模型进行对比和敏感性分析,验证了该模型的可行性和应用价值。

CBM在车辆维修中关键技术研究

运用CBM理论与RCM分析方法相结合的思路,探讨了CBM在车辆中的应用,采用规范化管理的有关理论,规范了车辆CBM的具体实施;结合CBM基本构成,应用相关理论与分析方法,分析了车辆CBM应用的三个关键技术,并对关键技术和方法进行了比较深入系统的研究,进而解决了CBM在车辆应用的基础问题。

SOAP技术在OSA-CBM系统中的应用

基于状态的维护(CBM)是一种新的设备维护方式,国际上的研究小组正致力于CBM系统开发标准的制定,提出了一种开放式体系结构OSA-CBM。本文探讨了SOAP技术在开放式CBM系统中的应用,设计了基于SOAP的CBM系统通信模型,并给出了实现该通信模型的具体方法和步骤。

CBMS在公路桥梁养护管理中的作用

CBMS具有综合性、数据的全面性、操作的实用性特点,是公路管理信息化的基础工作。通过对CBMS基础数据库的作用、内容的分析,对CBMS的评价决策结果及数据输出和系统查询功能进行了论述,对公路桥梁养护有重要意义。

基于CBM的通用特种车辆维修保障系统设计

针对现行军用特种车辆维修保障管理模式效率低,信息化程度不高的问题,论文设计了基于CBM的特种车辆维修保障管理系统结构,对特种车辆的CBM进行功能需求分析,并对特种车辆维修保障业务流程进行分析,提出了由数据采集层、状态监测层、数据传输层和数据处理与应用层四层组成的特种车辆维修保障管理系统结构,设计各子系统功能,阐述系统实现的关键技术,优化特种车辆维修保障模式,为维修管理工作的科学决策提供参考依据。

CBMS在高速公路桥涵养护管理中的应用经验

结合工程实例,对CBMS系统概念及工作模式展开分析,介绍了CBMS系统运作过程中的问题,从业内数据采集工作、外业数据采集模块、数据输入环节等方面,提出了CBMS系统桥涵养护管理的优化措施,旨在提升公路桥涵的整体养护管理效益。

A condition-based maintenance policy for reconfigurable multi-device systems

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.

滚动轴承多目标维修决策优化研究

为体现合理的维修时机在决定轴承使用效率与经济效益方面的重要作用,以滚动轴承为研究对象,基于威布尔比例风险模型,分别建立单一可用度决策模型,单一维修费用决策模型,综合利用可用度、维修费用、可靠性指标建立的模糊多目标规划维修决策模型,用层次分析法中的比例标度对模糊多目标规划模型约束条件进行改进,实现对滚动轴承的维修决策的优化,对比3种模型的计算结果。通过试验数据验证表明,改进的模糊多目标优化决策模型比单一目标模型更具优越性。