期刊名：Machines

期刊链接：https://www.mdpi.com/journal/machines

机械维护是机械设备使用过程中不可或缺的一部分，对于保证机械设备的性能和安全至关重要。这份“机械维护”方向的文献清单，希望能带你了解“机械维护”方向的研究进展！

1.

英文标题：Exploratory Analysis of SCADA Data from Wind Turbines Using the K-Means Clustering Algorithm for Predictive Maintenance Purposes

中文标题：基于k均值聚类算法的风电机组SCADA数据预测性维护探索性分析

文章链接：https://www.mdpi.com/2075-1702/11/2/270

MDPI引用格式：Rodriguez, P.C.; Marti-Puig, P.; Caiafa, C.F.; Serra-Serra, M.; Cusidó, J.; Solé-Casals, J. Exploratory Analysis of SCADA Data from Wind Turbines Using the K-Means Clustering Algorithm for Predictive Maintenance Purposes. Machines 2023, 11, 270. https://doi.org/10.3390/machines11020270

2.

英文标题 Balanced K-Star: An Explainable Machine Learning Method for Internet-of-Things-Enabled Predictive Maintenance in Manufacturing

中文标题 平衡K-Star：一种可解释的机器学习方法，用于制造业中物联网支持的预测性维护

文章链接：https://www.mdpi.com/2075-1702/11/3/322

MDPI引用格式 Ghasemkhani, B.; Aktas, O.; Birant, D. Balanced K-Star: An Explainable Machine Learning Method for Internet-of-Things-Enabled Predictive Maintenance in Manufacturing. Machines 2023, 11, 322. https://doi.org/10.3390/machines11030322

3.

Grouping Preventive Maintenance Strategy of Flexible Manufacturing Systems and Its Optimization Based on Reliability and Cost

基于可靠性和成本的柔性制造系统成组预防性维修策略及其优化

https://www.mdpi.com/2075-1702/11/1/74

Pei, Y.; Liu, Z.; Xu, J.; Qi, B.; Cheng, Q. Grouping Preventive Maintenance Strategy of Flexible Manufacturing Systems and Its Optimization Based on Reliability and Cost. Machines 2023, 11, 74. https://doi.org/10.3390/machines11010074

4.

Building a Digital Twin Powered Intelligent Predictive Maintenance System for Industrial AC Machines

工业交流机械数字双动力智能预测性维护系统的构建

https://www.mdpi.com/2075-1702/11/8/796

Singh, R.R.; Bhatti, G.; Kalel, D.; Vairavasundaram, I.; Alsaif, F. Building a Digital Twin Powered Intelligent Predictive Maintenance System for Industrial AC Machines. Machines 2023, 11, 796. https://doi.org/10.3390/machines11080796

5.

Optimizing Predictive Maintenance Decisions: Use of Non-Arbitrary Multi-Covariate Bands in a Novel Condition Assessment under a Machine Learning Approach

优化预测性维护决策：在机器学习方法下的新条件评估中使用非任意多协变量带

https://www.mdpi.com/2075-1702/11/4/418

Godoy, D.R.; Álvarez, V.; López-Campos, M. Optimizing Predictive Maintenance Decisions: Use of Non-Arbitrary Multi-Covariate Bands in a Novel Condition Assessment under a Machine Learning Approach. Machines 2023, 11, 418. https://doi.org/10.3390/machines11040418

6.

Data-Driven Predictive Maintenance Policy Based on Dynamic Probability Distribution Prediction of Remaining Useful Life

基于动态概率分布预测剩余使用寿命的数据驱动预测性维护策略

https://www.mdpi.com/2075-1702/11/10/923

Xie, S.; Xue, F.; Zhang, W.; Zhu, J. Data-Driven Predictive Maintenance Policy Based on Dynamic Probability Distribution Prediction of Remaining Useful Life. Machines 2023, 11, 923.

7.

Adopting New Machine Learning Approaches on Cox’s Partial Likelihood Parameter Estimation for Predictive Maintenance Decisions

基于Cox偏似然参数估计的机器学习方法在预测性维修决策中的应用

https://www.mdpi.com/2075-1702/12/1/60

Godoy, D.R.; Álvarez, V.; Mena, R.; Viveros, P.; Kristjanpoller, F. Adopting New Machine Learning Approaches on Cox’s Partial Likelihood Parameter Estimation for Predictive Maintenance Decisions. Machines 2024, 12, 60. https://doi.org/10.3390/machines12010060

8.

Hybrid Method with Parallel-Factor Theory, a Support Vector Machine, and Particle Filter Optimization for Intelligent Machinery Failure Identification

基于并行因子理论、支持向量机和粒子滤波优化的智能机械故障识别混合方法

https://www.mdpi.com/2075-1702/11/8/837

Li, S.; Chen, H.; Chen, Y.; Xiong, Y.; Song, Z. Hybrid Method with Parallel-Factor Theory, a Support Vector Machine, and Particle Filter Optimization for Intelligent Machinery Failure Identification. Machines 2023, 11, 837. https://doi.org/10.3390/machines11080837

9. A Multi-Information Fusion ViT Model and Its Application to the Fault Diagnosis of Bearing with Small Data Samples

多信息融合ViT模型及其在小数据样本轴承故障诊断中的应用

https://www.mdpi.com/2075-1702/11/2/277

Xu, Z.; Tang, X.; Wang, Z. A Multi-Information Fusion ViT Model and Its Application to the Fault Diagnosis of Bearing with Small Data Samples. Machines 2023, 11, 277. https://doi.org/10.3390/machines11020277

10.

A New Methodological Framework for Optimizing Predictive Maintenance Using Machine Learning Combined with Product Quality Parameters

基于机器学习和产品质量参数的预测性维护优化方法框架

https://www.mdpi.com/2075-1702/12/7/443

Riccio, C.; Menanno, M.; Zennaro, I.; Savino, M.M. A New Methodological Framework for Optimizing Predictive Maintenance Using Machine Learning Combined with Product Quality Parameters. Machines 2024, 12, 443. https://doi.org/10.3390/machines12070443

11.

Digital Ergonomics—The Reliability of the Human Factor and Its Impact on the Maintenance of Aircraft Brakes and Wheels

数字工效学——人为因素的可靠性及其对飞机制动器和车轮维护的影响数字工效学-人为因素的可靠性及其对飞机制动器和车轮维护的影响

https://www.mdpi.com/2075-1702/12/3/203

Hovanec, M.; Korba, P.; Al-Rabeei, S.; Vencel, M.; Racek, B. Digital Ergonomics—The Reliability of the Human Factor and Its Impact on the Maintenance of Aircraft Brakes and Wheels. Machines 2024, 12, 203. https://doi.org/10.3390/machines12030203

12

Systems Reliability and Data Driven Analysis for Marine Machinery Maintenance Planning and Decision Making

船舶机械维修计划与决策的系统可靠性与数据驱动分析

https://www.mdpi.com/2075-1702/12/5/294

Daya, A.A.; Lazakis, I. Systems Reliability and Data Driven Analysis for Marine Machinery Maintenance Planning and Decision Making. Machines 2024, 12, 294. https://doi.org/10.3390/machines12050294

13.

A Review of Prognostic and Health Management (PHM) Methods and Limitations for Marine Diesel Engines: New Research Directions

船用柴油机预测与健康管理 (PHM) 方法及局限性综述：新的研究方向

https://www.mdpi.com/2075-1702/11/7/695

Gharib, H.; Kovács, G. A Review of Prognostic and Health Management (PHM) Methods and Limitations for Marine Diesel Engines: New Research Directions. Machines 2023, 11, 695. https://doi.org/10.3390/machines11070695

14.

Compound Uncertainty Quantification and Aggregation for Reliability Assessment in Industrial Maintenance

工业维修可靠性评估的复合不确定性量化与聚合

https://www.mdpi.com/2075-1702/11/5/560

Grenyer, A.; Erkoyuncu, J.A.; Addepalli, S.; Zhao, Y. Compound Uncertainty Quantification and Aggregation for Reliability Assessment in Industrial Maintenance. Machines 2023, 11, 560. https://doi.org/10.3390/machines11050560

15.

Implementation and Possibilities of Fuzzy Logic for Optimal Operation and Maintenance of Marine Diesel Engines

模糊逻辑在船用柴油机优化运维中的实现与可能性

https://www.mdpi.com/2075-1702/12/6/425

Gharib, H.; Kovács, G. Implementation and Possibilities of Fuzzy Logic for Optimal Operation and Maintenance of Marine Diesel Engines. Machines 2024, 12, 425. https://doi.org/10.3390/machines12060425

Machines 期刊介绍

主编：Antonio J. Marques Cardoso, University of Beira Interior, Portugal

主要发表机械设备故障诊断和预测、机械设计、机电一体化、机器人、叶轮机械、控制及自动化、电机和驱动器、先进制造等领域的最新学术成果。