Das Oguzhan, Bagci Das Duygu, Birant Derya
National Defence University, Air NCO Higher Vocational School, Department of Aeronautics Sciences, Izmir, Turkey.
Ege University, Ege Vocational School, Department of Computer Programming, Izmir, Turkey.
Heliyon. 2023 Jun 22;9(6):e17584. doi: 10.1016/j.heliyon.2023.e17584. eCollection 2023 Jun.
As the concept of Industry 4.0 is introduced, artificial intelligence-based fault analysis is attracted the corresponding community to develop effective intelligent fault diagnosis and prognosis (IFDP) models for rotating machinery. Hence, various challenges arise regarding model assessment, suitability for real-world applications, fault-specific model development, compound fault existence, domain adaptability, data source, data acquisition, data fusion, algorithm selection, and optimization. It is essential to resolve those challenges for each component of the rotating machinery since each issue of each part has a unique impact on the vital indicators of a machine. Based on these major obstacles, this study proposes a comprehensive review regarding IFDP procedures of rotating machinery by minding all the challenges given above for the first time. In this study, the developed IFDP approaches are reviewed regarding the pursued fault analysis strategies, considered data sources, data types, data fusion techniques, machine learning techniques within the frame of the fault type, and compound faults that occurred in components such as bearings, gear, rotor, stator, shaft, and other parts. The challenges and future directions are presented from the perspective of recent literature and the necessities concerning the IFDP of rotating machinery.
随着工业4.0概念的引入，基于人工智能的故障分析吸引了相关领域开发用于旋转机械的有效智能故障诊断与预测（IFDP）模型。因此，在模型评估、对实际应用的适用性、特定故障模型开发、复合故障存在情况、领域适应性、数据源、数据采集、数据融合、算法选择和优化等方面出现了各种挑战。解决旋转机械各部件的这些挑战至关重要，因为每个部件的每个问题都会对机器的关键指标产生独特影响。基于这些主要障碍，本研究首次考虑到上述所有挑战，对旋转机械的IFDP程序进行了全面综述。在本研究中，针对所采用的故障分析策略、所考虑的数据源、数据类型、数据融合技术、故障类型框架内的机器学习技术以及轴承、齿轮、转子、定子、轴和其他部件中出现的复合故障，对已开发的IFDP方法进行了综述。从近期文献的角度以及旋转机械IFDP的必要性出发，阐述了挑战和未来方向。
