scholarly journals Optimal group maintenance decision for a wind farm based on condition‐based maintenance

Wind Energy ◽  
2021 ◽  
Author(s):  
Jinhe Wang ◽  
Xiaohong Zhang ◽  
Jianchao Zeng
Keyword(s):  
Wind Farm ◽  
Condition Based Maintenance ◽  
Maintenance Decision

A Dynamic Reliability-Centered Maintenance Analysis Method for Natural Gas Compressor Station Based on Diagnostic and Prognostic Technology

2015 ◽  
Vol 138 (6) ◽  
Author(s):  
Dengji Zhou ◽  
Huisheng Zhang ◽  
Yi-Guang Li ◽  
Shilie Weng
Keyword(s):  
Natural Gas ◽  
Preventive Maintenance ◽  
Condition Based Maintenance ◽  
Equipment Management ◽  
Analysis Method ◽  
Dynamic Reliability ◽  
Maintenance Schedule ◽  
Reliability Centered Maintenance ◽  
Maintenance Decision ◽  
Maintenance Model

The availability requirement of natural gas compressors is high. Thus, current maintenance architecture, combined periodical maintenance and simple condition based maintenance, should be improved. In this paper, a new maintenance method, dynamic reliability-centered maintenance (DRCM), is proposed for equipment management. It aims at expanding the application of reliability-centered maintenance (RCM) in maintenance schedule making to preventive maintenance decision-making online and seems suitable for maintenance of natural gas compressor stations. A decision diagram and a maintenance model are developed for DRCM. Then, three application cases of DRCM for actual natural gas compressor stations are shown to validate this new method.

On the Use of Mean Residual Life as a Condition Index for Condition-Based Maintenance Decision-Making

2014 ◽  
Vol 44 (7) ◽  
pp. 877-893 ◽  
Author(s):  
Khac Tuan Huynh ◽  
Inmaculada Torres Castro ◽  
Anne Barros ◽  
Christophe Berenguer
Keyword(s):  
Decision Making ◽  
Residual Life ◽  
Condition Index ◽  
Condition Based Maintenance ◽  
Mean Residual Life ◽  
Maintenance Decision

scholarly journals Research on Multi-Attribute Decision-Making in Condition-Based Maintenance for Power Transformers Based on Cloud and Kernel Vector Space Models

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5948
Author(s):  
Renxi Gong ◽  
Siqiang Li ◽  
Weiyu Peng
Keyword(s):  
Decision Making ◽  
Vector Space ◽  
Assessment System ◽  
Condition Based Maintenance ◽  
Power Transformers ◽  
Maintenance Strategy ◽  
Cloud Models ◽  
Optimal Maintenance ◽  
Maintenance Decision ◽  
Vector Space Models

Decision-making for the condition-based maintenance (CBM) of power transformers is critical to their sustainable operation. Existing research exhibits significant shortcomings; neither group decision-making nor maintenance intention is considered, which does not satisfy the needs of smart grids. Thus, a multivariate assessment system, which includes the consideration of technology, cost-effectiveness, and security, should be created, taking into account current research findings. In order to address the uncertainty of maintenance strategy selection, this paper proposes a maintenance decision-making model composed of cloud and vector space models. The optimal maintenance strategy is selected in a multivariate assessment system. Cloud models allow for the expression of natural language evaluation information and are used to transform qualitative concepts into quantitative expressions. The subjective and objective weights of the evaluation index are derived from the analytic hierarchy process and the grey relational analysis method, respectively. The kernel vector space model is then used to select the best maintenance strategy through the close degree calculation. Finally, an optimal maintenance strategy is determined. A comparison and analysis of three different representative maintenance strategies resulted in the following findings: The proposed model is effective; it provides a new decision-making method for power transformer maintenance decision-making; it is simple, practical, and easy to combine with the traditional state assessment method, and thus should play a role in transformer fault diagnosis.

scholarly journals Optimal Condition-Based Maintenance Strategy for Multi-Component Systems under Degradation Failures

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4346
Author(s):  
Kui Wang ◽  
Chao Deng ◽  
Lili Ding
Keyword(s):  
Critical Level ◽  
Condition Based Maintenance ◽  
Maintenance Strategy ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Optimal Monitoring ◽  
Long Run ◽  
Component Systems ◽  
Maintenance Decision ◽  
The Impact

This paper proposes a condition-based maintenance strategy for multi-component systems under degradation failures. The maintenance decision is based on the minimum long-run average cost rate (LACR) and the maximum residual useful lifetime (RUL), respectively. The aim of this paper is to determine the optimal monitoring interval and critical level for multi-component systems under different optimization objectives. A preventive maintenance (PM) is triggered when the degradation of component exceeds the corresponding critical level. Afterwards, the paper discusses the relationship between the critical level and the monitoring interval with regards to the LACR and RUL. Methods are also proposed to determine the optimal monitoring interval and the critical level under two decision models. Finally, the impact of maintenance decision variables on the LACR and RUL is discussed through a case study. A comparison with conventional maintenance policy shows an outstanding performance of the new model.

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