基于人工智能的农用拖拉机发动机故障快速诊断研究

为了达到拖拉机发动机不解体故障诊断的目的,提高诊断效率,利用发动机缸盖的振动信号的采集原理,提出了一种基于神经网络的人工智能故障检测方法,并构建了拖拉机发动机振动信号采集系统。基于人工智能的拖拉机发动机故障诊断系统,综合运用信号采集技术、信号处理技术、数据库技术、神经网络技术和人工智能专家系统,实现了和数据库及具有强大信号分析的处理功能,提高了系统的诊断实时性和诊断精度。最后,采用田间试验方法,对拖拉机故障快速诊断系统进行了试验验证。试验结果表明:采用人工智能诊断方法不仅可以有效提高系统的准确率,而且诊断系统的响应更加迅速,并且曝晒、震动、灰尘等恶劣的现场环境中仍能保持正常工作的稳定性。

Research on Rapid Diagnosis of Agricultural Tractor Engine Based on Artificial Intelligence

In order to achieve the purpose of fault diagnosis of tractor engine disintegration, improve the efficiency of diagnosis, the acquisition principle of cylinder head vibration signal, it presented an artificial intelligent fault detection method based on neural network, and constructed a tractor engine vibration signal acquisition system.It comprehensively use of signal acquisition technology, signal processing technology, database technology, neural network technology and artificial intelligence expert system based on artificial intelligence, and realized the database with powerful function of processing signal, which improve the accuracy of diagnosis and diagnosis of real-time system.Finally, by using the method of field experiment, it has done the experimental verification of the tractor fast fault diagnosis system.The experimental results show that the accuracy can not only effectively improve the system by using artificial intelligent diagnosis method and diagnosis system, but also response more rapidly, and the scene environment dynamic exposure, shock resistance and dust in the harsh, which still can keep the normal work.