Earticle

초록

영어

In accordance with the requirements for home security and safe guard, a new type of intelligent monitoring system is researched and developed. The system is established with CAN bus and wireless as the foundation. Multi-sensor technology is used to improve the alarm algorithm of the system, a new fuzzy neural network is put forward as the classifier. There are four layers in the network, and the input signals are temperature and the concentration of CO, smoke and CO2, the output signal is the fire probability. Radial basis function (RBF) is used as the fuzzy membership function. The principal component analysis (PCA) is used to extract the information of sensors and an observation window is used to extract the necessary information for neural network. Experiments show that the system can provide accurate detection results in a short time.

목차

Abstract
 1. Introduction
 2. The Overall Hardware Structure of Monitoring System
 3. Fire Alarm System Based on Data Fusion
  3.1 Sensor Selection of Fire alarm System
  3.2 PCA algorithm used for Feature Extraction
  3.3 Extract the Characteristics by Fuzzy Neural Network
 4. Data Selection and Experiment Analysis
 5. Experimental Results and Analysis
  5.1 Sensitivity Analysis
  5.2 Reliability Analysis
 6. Conclusion
 References

키워드

저자

• Dezhong Zheng [ Measurement Technology and Instrumentation Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China ]
• Yang Wang [ Measurement Technology and Instrumentation Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China ]
• Yan Wang [ Measurement Technology and Instrumentation Key Lab of Hebei Province, Yanshan University, Qinhuangdao 066004, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605