基于迭代学习的速度传感器故障诊断研究

Research on fault diagnosis of speed sensor based on iterative learning

霍尔式速度传感器利用实时检测的速度信号作为系统速度反馈参考,广泛应用于轨道交通和汽车电子产品中,为系统安全可靠运行提供保障。针对霍尔式速度传感器工作原理,构建含有实时故障估计变量的线性时不变系统模型,根据传感器实际输出和估计输出的残差信号确定目标函数及基于迭代学习的故障诊断数学模型,并对此迭代学习故障诊断策略进行收敛速度和收敛精度分析。为验证诊断策略的普适性和正确性,在速度传感器正常工作状态下施加典型阶跃、指数和正弦形式的故障信号,探究诊断算法对故障信号估计的准确性和时效性。研究结果表明:所提故障诊断策略能够利用实时故障估计变量准确估计故障信号,并在有限时域周期内全局收敛,为诊断策略的工程化应用奠定基础。

Hall type speed sensor is widely used in rail transit and automotive electronic products.The real-time detected speed signal is used as the speed feedback reference of the system to ensure the safe and reliable operation of the system.Aiming at the speed acquisition system based on hall speed sensor,a linear time invariant system model with real-time fault estimation variables was constructed.On the basis of the residual signal of sensor output and estimated output,the objective function and iterative learning fault diagnosis strategy were determined,and the convergence rate and convergence accuracy of iterative learning fault diagnosis strategy were analyzed.In order to verify the universality and correctness of the diagnosis strategy,the typical step,exponential and sinusoidal fault signals were applied under the normal working state of the speed sensor to explore the accuracy and timeliness of the fault diagnosis algorithm.The simulation results show that the proposed fault diagnosis strategy can converge in finite time-domain period and quantitatively describe the real-time fault signal,which plays the foundation for the engineering application of the diagnosis strategy.