张兰玲, 刘贺平, 孙一康. 复杂生产过程工况的自动识别[J]. 工程科学学报, 1997, 19(4): 398-402. DOI: 10.13374/j.issn1001-053x.1997.04.040
引用本文: 张兰玲, 刘贺平, 孙一康. 复杂生产过程工况的自动识别[J]. 工程科学学报, 1997, 19(4): 398-402. DOI: 10.13374/j.issn1001-053x.1997.04.040
Zhang Lanling, Liu Heping, Sun Yikang. Automatic Recognition of the Operating Mode in Process of Complex Production[J]. Chinese Journal of Engineering, 1997, 19(4): 398-402. DOI: 10.13374/j.issn1001-053x.1997.04.040
Citation: Zhang Lanling, Liu Heping, Sun Yikang. Automatic Recognition of the Operating Mode in Process of Complex Production[J]. Chinese Journal of Engineering, 1997, 19(4): 398-402. DOI: 10.13374/j.issn1001-053x.1997.04.040

复杂生产过程工况的自动识别

Automatic Recognition of the Operating Mode in Process of Complex Production

  • 摘要: 针对复杂生产过程中的工况识别问题,利用了模块化的设计方法,将其分为离线建模模块和在线决策模块.建模模块采用自适应延时神经网络构造各类工况相应的预测模型,决策模块通过计算未知工况序列相对于各类预测模型的匹配程度判断其所属类别.

     

    Abstract: A modular design method to recognize the operahng mode in process of complex production is provided. The enhre recognihon task is divided into two sub-modules; modeling module, trained off-line, and decision module, Performed on-line.In modeling module, the adaphve time-delay neura network is used to construct various predicting models which correspond to different operating modes. In decision module, for a new sequence, which operating mode it belong to is deduced depending on matching degree between this new sequence and all predichng models. The simulation results show the effectiveness of the method.

     

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