Figlus Tomasz
Faculty of Transport, The Silesian University of Technology, 8 Krasinskiego Street, 40-019 Katowice, Poland.
Entropy (Basel). 2019 Apr 27;21(5):441. doi: 10.3390/e21050441.
The paper presents a method of processing vibration signals which was designed to detect damage to wheels of gearboxes for means of transport. This method uses entropy calculation, and multi-stage filtering calculated by means of digital filters and the Walsh-Hadamard transform to process signals. The presented method enables the extraction of vibration symptoms, which are symptoms of gear damage, from a complex vibration signal of a gearbox. The combination of multi-stage filtering and entropy enables the elimination of fast-changing vibration impulses, which interfere with the damage diagnosis process, and make it possible to obtain a synthetic signal that provides information about the state of the gearing. The paper demonstrates the usefulness of the developed method in the diagnosis of a gearbox in which two types of gearing damage were simulated: tooth chipping and damage to the working surface of the teeth. The research shows that the application of the proposed method of vibration of signal processing enables observation of the qualitative and quantitative changes in the entropy signal after denoising, which are unambiguous symptoms of the diagnosed damage.
本文提出了一种处理振动信号的方法,该方法旨在检测运输工具变速箱齿轮的损伤。该方法利用熵计算,以及通过数字滤波器和沃尔什 - 哈达玛变换进行的多级滤波来处理信号。所提出的方法能够从变速箱的复杂振动信号中提取出作为齿轮损伤症状的振动特征。多级滤波和熵的结合能够消除干扰损伤诊断过程的快速变化的振动脉冲,并使得能够获得提供有关齿轮传动状态信息的合成信号。本文展示了所开发方法在诊断模拟了两种类型齿轮损伤(齿面剥落和齿工作面损伤)的变速箱中的有效性。研究表明,应用所提出的振动信号处理方法能够观察到去噪后熵信号的定性和定量变化,这些变化是已诊断损伤的明确症状。