摘要
针对挥发雾化式汽车独立燃油加热器的点火判别问题,提出了一个基于神经网络模型的线性分类函数,并讨论了网络的监督学习规则问题。函数由一个以燃烧传感器温度、温升速率、缸体温度为输入的单层感知器构成。试验结果表明,在环境温度-40^-35℃的情况下,该算法均可以对加热器点火过程进行快速可靠的判别。
A linear classified function based on the neural network （NN） model is put forward, for the vaporized automobile fuel heater ignition discrimination, and the supervision learning rule is discussed. The function is composed of a single layer sensor in which inputs are fire sensor temperature, temperature gradient and vat body temperature. The experimental results show that arithmetic can correctly and quickly discriminate the igniting process when the environment temperature is between-40 ℃ and-35 ℃.
出处
《长春工业大学学报》
CAS
2008年第4期420-423,共4页
Journal of Changchun University of Technology
关键词
汽车加热器
点火
判别算法
神经网络
监督学习
automobile heater
ignition
discriminant arithmetie
neural network, supervised learning.
