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The Application of Correlation Dimensions of Vibration Signals in Analysis of the Technological State of Diesel Engines

机译:振动信号相关维数在柴油机技术状态分析中的应用

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The fault-free operation of diesel engine in a normal state is a kind of self-excited vibration, but with the change of its technological states in the operation, the vibration will become much more like a random vibration. All the variable information of these technological states is included in the vibration signals of diesel engines, which can be used to judge the different technological states. However, the existence of a lot of noise signals at the same time may affect the accuracy of the judgment. Aiming at this problem, this article puts forward that an ameliorated wavelet packet algorithm can be used to decompose and reconstruct the measured signals before using the fractal theory to make analysis and judgment on them. The experiment shows that, such a method can effectively improve the signal-to-noise ratio, and as a result, can accurately judge the technological states and fault signatures of diesel operation.
机译:柴油机在正常状态下的无故障运行是一种自激振动,但是随着运行过程中技术状态的变化,该振动将变得更像是随机振动。这些技术状态的所有可变信息都包含在柴油机的振动信号中,可用于判断不同的技术状态。但是,同时存在大量噪声信号可能会影响判断的准确性。针对这一问题,本文提出一种改进的小波包算法,可以在利用分形理论对其进行分析和判断之前,对被测信号进行分解和重构。实验表明,该方法可以有效提高信噪比,从而可以准确判断柴油机运行的技术状态和故障特征。

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