(1 ) in view of practice that the data obtained from accelerometer has serious zero deviation, it is very difficult to diagnosis fault by hardware redundant . a fault diagnosis scheme for multi-accelerometers employing predictor based on radial basis function ( rbf ) neural network is proposed 论文的主要创新成果有:(1)在摆式列车实际运行中,检测子系统的加速度传感器存在严重零偏,使用硬件冗余法进行故障诊断的设计初衷面临着巨大的困难。
the strategy eliminates the disturbance with zero deviation and improves the reliability of fault diagnosis . ( 2 ) in the light of reality adopting double redundant gyroscope, the fault diagnosis model for double redundant sensors taking the basic principle of adaptive noise cleaner is established . the diagnosis method, recurrence algorithm and implement are given (2)根据检测子系统采用双冗余陀螺仪的实际情况,利用自适应噪声消除器的基本原理构造了双余度传感器的故障诊断模型,给出了双余度传感器的故障诊断原理和递推算法,实现了双冗余陀螺仪的故障诊断。
aees employs the multi-staged digital filter algorithm to reduce random error . meanwile, the system correct zero deviation through linear opreation . the instrument, from hardware aspect increases the feature of anti-interference by the way of reasonable layout, sepration of digital and analogue 系统采用了中值滤波和滑动平均滤波相结合的多级数字滤波算法来减小随机误差,并以精密基准电压作为比较信号的输入,由智能系统通过线性运算,实时地修正、校准测量数据,减小系统的零漂,实现自动定标并提高测量的精度。