气缸润滑油对二冲程低速船用柴油机振动特性影响的实验研究

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Gang Wu, Guodong Jiang, Changsheng Chen, Guohe Jiang, Xigang Pu, Bi-we Chen
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引用次数: 0

摘要

摘要 二冲程低速柴油发动机因其良好的性能和燃油经济性而广泛应用于大型船舶。然而,有关润滑油对二冲程低速柴油机振动影响的研究却很少。本研究采用频域、时频域、快速傅里叶变换 (FFT) 和短时傅里叶变换 (STFT) 方法,研究了三种不同润滑油对低速发动机振动特性的影响。结果表明,基于振动信号可成功实现对低速船用发动机气缸套磨损的非侵入式状态监测。FFT 和 STFT 方法都能实时在线捕捉气缸内的燃烧信息,STFT 方法还能提供更全面的可视化结果信息。通过对振动信号进行在线状态监测,发现中等粘度和中等碱含量的气缸润滑油具有最佳的磨损保护性能。这一结果与气缸润滑特性的元素分析结果以及对发动机运行 300 小时后从气缸中取出的活塞测量数据的分析结果一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Experimental Study of the Effects of Cylinder Lubricating Oils on the Vibration Characteristics of a Two-Stroke Low-Speed Marine Diesel Engine
Abstract Two-stroke, low-speed diesel engines are widely used in large ships due to their good performance and fuel economy. However, there have been few studies of the effects of lubricating oils on the vibration of two-stroke, low-speed diesel engines. In this work, the effects of three different lubricating oils on the vibration characteristics of a low-speed engine are investigated, using the frequency domain, time-frequency domain, fast Fourier transform (FFT) and short-time Fourier transform (STFT) methods. The results show that non-invasive condition monitoring of the wear to a cylinder liner in a low-speed marine engine can be successfully achieved based on vibration signals. Both the FFT and STFT methods are capable of capturing information about combustion in the cylinder online in real time, and the STFT method also provides the ability to visualise the results with more comprehensive information. From the online condition monitoring of vibration signals, cylinder lubricants with medium viscosity and medium alkali content are found to have the best wear protection properties. This result is consistent with those of an elemental analysis of cylinder lubrication properties and an analysis of the data measured from a piston lifted from the cylinder after 300 h of engine operation.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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