论文部分内容阅读
机电设备 Ｂ Ｉ Ｔ 的突出问题是虚警率高，重要原因之一是 Ｂ Ｉ Ｔ 系统传感器通路故障。本文选取神经网络技术进行传感器通路故障诊断，剖析某大型船舶动力装置机电设备 Ｂ Ｉ Ｔ 系统中传感器通路的故障机理和类型，得到其故障样本数据，经过神经网络学习训练后对实际系统进行故障诊断和识别，实验结果表明该方法简洁、有效，能够有效地诊断故障并识别出故障类型，具有实用价值。
One of the main reasons for the high false alarm rate is that the BIT system sensor path is faulty. In this paper, the neural network technology is used to diagnose the sensor path fault, the fault mechanism and the type of the sensor path in the B I T system of a large marine power plant are analyzed, and the fault sample data are obtained. After neural network learning and training, the fault diagnosis of the actual system The experimental results show that this method is concise and effective, can diagnose faults effectively and identify the types of faults, which is of practical value.