行星齿轮箱齿轮磨损故障诊断

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (23) : 84-89.

论文

行星齿轮箱齿轮磨损故障诊断

李海平1,2，赵建民2，张鑫2，倪祥龙3

作者信息 +

Fault diagnosis for gear wear of planetary gearbox

LI Haiping1,2， ZHAO Jianmin2, ZHANG Xin2, NI Xianglong3

Author information +

文章历史 +

摘要

为解决行星齿轮箱故障诊断方法专业性要求高、计算过程复杂以及模型训练时间长等问题，提出一种基于PCA-EDT-DBN的行星齿轮箱故障诊断新方法。利用PCA分析多个传感器采集到的振动信号并根据需求取每列信号的前p个主成分，将每列信号的前p个主成分合成一维序列。计算每两列数据前p个主成分之间的欧氏距离得到距离矩阵，将该矩阵按序展开成一维序列。将得到的两个一维序列合成一个一维序列作为样本输入到DBN中对模型进行训练，再有新样本输入到训练好的模型中则可智能地给出分类结果，从而实现对设备的故障诊断。此外，为提高模型诊断准确率，提出利用正交试验对DBN参数进行优化。利用行星齿轮箱齿轮磨损预置故障实验数据验证了该方法的有效性，结果表明该方法诊断准确率高、训练时间短且计算过程简单。

Abstract

To solve problems of planetary gearbox fault diagnosis method having higher professional requirements, complex calculation process and longer model training time, a new fault diagnosis method for planetary gearbox based on PCA-EDT-DBN was proposed.PCA was used to analyze vibration signals acquired with several sensors, select the first p principal components of each column of signals according to requirements, and arrange these p principal components into a one-dimensional (1-D) sequence.Euclidean distances between the first p principal components of each 2 columns data were computed to obtain a distance matrix.This matrix was sequentially expanded into a 1-D sequence.Two 1-D sequences obtained according to the mode mentioned above were synthesized into a 1-D one taken as a sample to be input into DBN for model training.Then, new samples were input into the trained model to output a classification result intelligently, and realize planetary gearbox’s fault diagnosis.Additionally, in order to improve the accuracy of model diagnosis, the orthogonal test method was used to optimize parameters of DBN.The preset fault test data for planetary gearbox teeth wear were used to verify the effectiveness of the proposed method.The results showed that the proposed method has advantages of higher diagnosis accuracy, shorter training time and simpler calculation process.

导出引用

李海平1,2，赵建民2，张鑫2，倪祥龙3. 行星齿轮箱齿轮磨损故障诊断[J]. 振动与冲击, 2019, 38(23): 84-89

LI Haiping1,2， ZHAO Jianmin2, ZHANG Xin2, NI Xianglong3. Fault diagnosis for gear wear of planetary gearbox[J]. Journal of Vibration and Shock, 2019, 38(23): 84-89

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