CAJ | 학술논문

根据催化传感器在不同的电场条件下具有不同气体检测灵敏度的特点,介绍了采用单一的热催化传感器在不同的电场强度下,通过分布式多子网神经网络对含未知气体的可燃混合气体进行分析的新方法.应用分布式神经网络,通过训练建立了信号识别的模型,并以3种混合气体为对象进行实验,结果证明了分析方法的可行性.实验表明:该网络在泛化能力与学习速度等均优于BP和RBF网络,其多子网、自动分解任务的特点尤其适用于复杂样本的学习,具有很好的应用前景.
근거최화전감기재불동적전장조건하구유불동기체검측령민도적특점,개소료채용단일적열최화전감기재불동적전장강도하,통과분포식다자망신경망락대함미지기체적가연혼합기체진행분석적신방법.응용분포식신경망락,통과훈련건립료신호식별적모형,병이3충혼합기체위대상진행실험,결과증명료분석방법적가행성.실험표명:해망락재범화능력여학습속도등균우우BP화RBF망락,기다자망、자동분해임무적특점우기괄용우복잡양본적학습,구유흔호적응용전경.
Based on the feature of the sensitivity detection of catalytic sensor to inflammble different gas,single catalytic sensor is used to analyze mixed-inflammable gases with unknown components by distributed multi-subnet neural networks in difierent electric field.Distributed neural networks are used to set model of signal recognition by training.Three mixed gases are adopted.The result proves that the method is feasible.And the result shows that it achieves better performance than BP or RBF network on generalization ability and training speed etc.The feature of multi-subnet and dividing a complex task automatically is especially suitble for complex task learning.And it has good application prospect.