以某船WESTFALIA SEPARATOR OSA 20-0136-066型重油分油机在排渣过程中发生的严重振动损坏事故为例,深入分析了故障成因、影响及预防措施。事故调查表明,滚动轴承损坏、分离筒本体螺纹锈蚀装配件松动导致动平衡破坏是主要原因。此外,值...以某船WESTFALIA SEPARATOR OSA 20-0136-066型重油分油机在排渣过程中发生的严重振动损坏事故为例,深入分析了故障成因、影响及预防措施。事故调查表明,滚动轴承损坏、分离筒本体螺纹锈蚀装配件松动导致动平衡破坏是主要原因。此外,值班人员未能及时识别并处理异常振动,进一步加剧了故障。基于此,提出了加强分油机装配工艺控制、优化运行参数监控、定期进行维护保养等措施,强调了动平衡试验的重要性,并建议在电机、齿轮箱等关键部位加装振动检测装置,以提高分油机的运行稳定性和安全性。对于提升船舶分油机的管理水平,保障设备安全运行具有重要指导意义。展开更多
Structural health monitoring (SHM) is a relevant topic for civil systems and involves the monitoring, data processing and interpretation to evaluate the condition of a structure, in order to detect damage. In real str...Structural health monitoring (SHM) is a relevant topic for civil systems and involves the monitoring, data processing and interpretation to evaluate the condition of a structure, in order to detect damage. In real structures, two or more sites or types of damage can be present at the same time. It has been shown that one kind of damaged condition can interfere with the detection of another kind of damage, leading to an incorrect assessment about the structure condition. Identifying combined damage on structures still represents a challenge for condition monitoring, because the reliable identification of a combined damaged condition is a difficult task. Thus, this work presents a fusion of methodologies, where a single wavelet-packet and the empirical mode decomposition (EMD) method are combined with artificial neural networks (ANNs) for the automated and online identification-location of single or multiple-combined damage in a scaled model of a five-bay truss-type structure. Results showed that the proposed methodology is very efficient and reliable for identifying and locating the three kinds of damage, as well as their combinations. Therefore, this methodology could be applied to detection-location of damage in real truss-type structures, which would help to improve the characteristics and life span of real structures.展开更多
文摘以某船WESTFALIA SEPARATOR OSA 20-0136-066型重油分油机在排渣过程中发生的严重振动损坏事故为例,深入分析了故障成因、影响及预防措施。事故调查表明,滚动轴承损坏、分离筒本体螺纹锈蚀装配件松动导致动平衡破坏是主要原因。此外,值班人员未能及时识别并处理异常振动,进一步加剧了故障。基于此,提出了加强分油机装配工艺控制、优化运行参数监控、定期进行维护保养等措施,强调了动平衡试验的重要性,并建议在电机、齿轮箱等关键部位加装振动检测装置,以提高分油机的运行稳定性和安全性。对于提升船舶分油机的管理水平,保障设备安全运行具有重要指导意义。
基金Project (No. PIFI-2012 U. de Gto.) supported by the Secretariat of Public Education (SEP), Mexico
文摘Structural health monitoring (SHM) is a relevant topic for civil systems and involves the monitoring, data processing and interpretation to evaluate the condition of a structure, in order to detect damage. In real structures, two or more sites or types of damage can be present at the same time. It has been shown that one kind of damaged condition can interfere with the detection of another kind of damage, leading to an incorrect assessment about the structure condition. Identifying combined damage on structures still represents a challenge for condition monitoring, because the reliable identification of a combined damaged condition is a difficult task. Thus, this work presents a fusion of methodologies, where a single wavelet-packet and the empirical mode decomposition (EMD) method are combined with artificial neural networks (ANNs) for the automated and online identification-location of single or multiple-combined damage in a scaled model of a five-bay truss-type structure. Results showed that the proposed methodology is very efficient and reliable for identifying and locating the three kinds of damage, as well as their combinations. Therefore, this methodology could be applied to detection-location of damage in real truss-type structures, which would help to improve the characteristics and life span of real structures.
