A method based on multi-sensor data fusion for fault detection of planetary gearboxes.
A method based on multi-sensor data fusion for fault detection of planetary gearboxes.
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基于多传感器数据融合的行星齿轮箱故障检测方法
DOI：
10.3390/s120202005
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Kong D
中科院分区：
文献类型：
--
作者：
Lei Y;Lin J;He Z;Kong D
与定轴齿轮箱相比，行星齿轮箱的故障检测与诊断研究相对较少。与定轴齿轮箱不同，行星齿轮箱表现出独特的行为，这使得适用于定轴齿轮箱的故障诊断方法失效。事实上，对于像行星齿轮箱这样复杂的系统，安装在不同位置的多个传感器提供了关于系统健康状况的补充信息。在此基础上，提出了一种基于多传感器数据融合的故障检测方法。在该方法中，行星齿轮箱开发的两个功能被用来表征齿轮健康状况，并利用自适应神经模糊推理系统（ANFIS）融合来自不同传感器的所有功能。为了验证该方法的有效性，在行星齿轮箱试验台上进行了实验，在该试验台上安装了多个加速度计进行数据采集。与基于单个传感器的故障检测方法的比较表明，该方法在行星齿轮箱故障检测中具有更高的准确性。
Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS) is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults.
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