铁谱磨粒多重分形特征研究  

Study on Multi-fractal Features of Ferrographic Wear Particles

作　　者：张云强[1] 张培林[1] 任国全[1] 徐超[1] 王国德[1] 

机构地区：[1]军械工程学院一系,河北石家庄050003

出　　处：《润滑与密封》2012年第5期52-56,共5页Lubrication Engineering

基　　金：国家自然科学基金项目(50705097);清华大学摩擦学国家重点实验室开放基金资助项目(SKLTKF09B06)

摘　　要：为有效描述铁谱磨粒特征,提出用多重分形谱参数表达磨粒形态特征的新方法。选择盒计数法计算磨粒图像的多重分形谱,研究磨粒多重分形谱的有效性,分析磨粒多重分形谱参数的不变性和鲁棒性;确定磨粒图像预处理方法,并对4类典型磨粒的多重分形谱参数进行统计分析。结果表明:将多重分形谱参数应用于磨粒识别,总识别率为82.5%。磨粒具有明显的多重分形特性,可用多重分形谱参数来描述磨粒的形态特征;多重分形谱参数具有平移不变性,但对灰度变化和噪声干扰的鲁棒性较差,在提取多重分形谱参数时,需要对磨粒图像做严格的预处理。To effectively describe the features of ferrographic wear particles, a novel method that utilizes muhi-fractal spectrums parameters to depict features of wear particle images was proposed. The muhi-fractal spectrum of wear particle images was computed by the box counting method to study the validity of multi-fractal spectrums of wear particle images, and the invariance and robustness of muhi-fractal spectrum parameters were analyzed for wear particle images. The pre-pro- cessing steps of wear particle images were designed and the statistical analysis was carried on the muhi-fractal spectrum pa- rameters of 4 types of wear particles. The results show that, when applying the muhi-fractal spectrum parameters for wear particle recognition, the total recognition rate is 82. 5 %. Wear particles have obvious muhi-fractal characteristics and multifractal spectrum parameters can be employed to describe the morphological characters of wear particles. Muhi-fractal spectrum parameters have translational invariance and poor robustness for gray changes and noise pollution, so preprocessing of wear particle images is needed when extracting multi-fractal spectrum parameters.

关 键 词：铁谱技术 磨粒图像 多重分形谱参数 不变性 特征提取 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]