摘要
提出了一种基于总体经验模态分解(EEMD)与形态学分形维数的柴油机缸套磨损诊断方法,以某6缸四冲程柴油机为研究对象,测试并分析了柴油机缸套4种状态下机体振动信号的形态学分形维数。研究结果表明:利用含噪振动信号的分形维数来描述缸套磨损状态是不可靠的,实测信号降噪后的形态学分形维数能够清晰地区分柴油机缸套磨损状态。
A novel diagnosis method of diesel engine cylinder liner wear based on ensemble empirical mode decomposition（EEMD） and morphological fractal dimension was proposed. In this method, firstly measured vibration signals were decomposed into a set of intrinsic mode functions （IMFs） by EEMD to separate noise interference from the IMF containing cylinder liner wear characteristic information, and then the morphological fractal dimension of IMF was calculated. Taking a six cylinder four stroke diesel engine for instance, the morphological fractal dimension of vibration signals measured from engine cylinder liner under 4 different states was analyzed. Results indicate that reflecting the system characteristics with the fraetal dimension of vibration signals containing noise is not reliable, the measured signals must be denoised prior to calculation of morphology fractal dimension, thus the cylinder liner wear condition can be identified clearly.
出处
《内燃机工程》
EI
CAS
CSCD
北大核心
2013年第1期71-75,共5页
Chinese Internal Combustion Engine Engineering
基金
国家自然科学基金资助项目(51175057)
中央高校基本科研业务费专项资金资助项目(2009JC14)
关键词
内燃机
柴油机
缸套磨损
分形维数
形态学
总体经验模态分解
IC engine
diesel engine
cylinder linear wear
fractal dimension
morphology
ensemble empirical mode decomposition（EEMD）
