基于声场图像分析的印刷机轴承故障诊断方法

目的针对印刷机墨辊轴承的故障信息获取及诊断难等问题,提出一种基于声场图像分析的故障诊断与定位方法。方法首先,构建声音测试系统并划分检测对象的空间区域,逐一采集信号并依据对应空间位置关系进行重构与组合;其次,将一段时间内的信号能量进行叠加,同时依据空间位置关系形成叠加状态的声场图像信息;然后,引入二维经验模式分解(BEMD)分析空间域图像信息,消除环境噪声干扰并得到声场图像的高频信息。结果对不同位置、不同种类的墨路系统故障轴承进行特征分析与比对,利用IBIMF分量及统计特征实现了轴承内、外圈故障的诊断,利用无量纲特征实现了不同故障位置的有效定位,并通过实验验证了方法的有效性。结论所提出故障诊断方法发挥了非接触测量优势,同时具有较强故障表征能力,适用于同类复杂机械系统。

Fault Diagnosis Method of Printing Press Bearings Based on Image Analysis of Sound Field

The work aims to propose a fault diagnosis and locating method based on image analysis of sound field with respect to the difficulty in acquiring and diagnosing fault information of ink roller bearing in printing press. Firstly, the sound test system was constructed and the space area of detected object was divided. The signals were acquired one by one for reconstruction and combination according to the corresponding spatial location relationship. Then, the signal energy in a period of time was superimposed and the sound field image information in the superposition state was formed based on the spatial location relationship. Next, bidimensional empirical mode decomposition (BEMD) was introduced to analyze the spatial domain image information and get the high-frequency information through the elimination of ambient noise interference. Feature analysis and comparison of fault bearings for the ink roller system at different positions and of different kinds were carried out. The diagnosis of faults in inner and outer rings of the bearing was realized by means of IBIMF component and statistical characteristics. The effective locating of different fault positions was achieved through dimensionless characteristics and the effectiveness of the method was verified by experiments. The proposed fault diagnosis method makes the most of non-contact measurement and has a strong ability to characterize the faults, which is suitable for similar complex mechanical systems.