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矿用空压机是煤矿现代化安全生产的重要组成设备,针对目前矿用空压机经常出现的故障,收集了矿用空压机故障征兆和其对应的故障类型,将故障样本数据和模糊神经网络相结合,并根据改进BP神经网络确定网络的输入和输出向量,对矿用空压机进行组合式故障诊断,诊断结果与实际情况比较吻合。运用MATLAB实现神经网络故障诊断仿真,仿真结果表明诊断误差较小,输出向量与实际故障矩阵结果接近。
Mine air compressor is an important component of modern coal mine safety production equipment, mining air compressor for the current frequent failures, collected mine air compressor fault symptoms and the corresponding fault type, the fault sample data and fuzzy nerve Network, and based on the improved BP neural network to determine the input and output vector of the network, the combination of mine air compressor fault diagnosis, diagnostic results and the actual situation more in line. Using MATLAB to realize the neural network fault diagnosis and simulation, the simulation results show that the diagnostic error is small, and the output vector is close to the actual fault matrix.