基于振动信号的柴油机气阀漏气故障诊断研究

Fault Diagnosis Study of Leaking Gas of Valves Based on Vibration Signal

分析了柴油机缸头振动机理,运用小波包对振动信号进行了分析和讨论,提取出相应的特征向量,然后将振动样本特征向量作为神经网络的输入参数,以故障类别作为输出参数,经过训练的神经网络可以利用测量的振动信号来判断柴油机气阀的故障状态。实例证明该方法有效可行。

Analysis the elements of vibration on diesel cylinder lip, and discuss the vibration signal using wave let packets to achieve the relevant characteristic vectors. The model of neural networks is built, its input parameters include the relevant characteristic vectors, and the outputs represent the faults. At last, use the ex periment data to train it. The neural network can be used to classify the faults of the valves according to the input vibration signal. Experimentation shows that the method is very effective.