A new fault diagnosis method based on multiple preset models is also proposed.
在此基础上，提出了系统的多重预设模型的故障诊断方法。
Diagnosis models based on multilayer feedforward neural networks are widely used in the field of machinery fault diagnosis.
基于多层前向网络的诊断模型在设备故障诊断领域应用比较广泛。
Based on these two models, we propose an associative search algorithm for fault diagnosis and apply it to a control system. At last, the simulation results are given out.
基于这两种模型，我们提出了一种用于故障诊断的联想搜索网络，并把它应用于一个锅炉给水装置的控制系统故障诊断上，最后给出了计算机的仿真结果。
Then, an observer bank of autoregressive time series models based on multi-component neural-network architecture is used for model diagnosis of rotor fault vibration signals.
最后根据该方法组成了一个自回归时间序列模型库，用于转子故障的模型诊断中。
Then, an observer bank of autoregressive time series models based on multi-component neural-network architecture is used for model diagnosis of rotor fault vibration signals.
最后根据该方法组成了一个自回归时间序列模型库，用于转子故障的模型诊断中。
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