user

Application of fuzzy neural network for fire detecting system

被引：0
|
作者：
Liao Yanfen [1 ]
Ma Xiaoqian [1 ]
机构：
[1] S China Univ Technol, Elect Power Coll, Guangzhou 510640, Peoples R China
来源：
PROCEEDINGS OF THE FIRST INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1 - 3 | 2006年
关键词：
fire detect; fuzzy logic; artificial neural net; image characteristic;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
According to the fire image properties,;an intelligent fire detecting system based on multi-sensor data fusion technology was developed, which adopt CCD image sensor, temperature sensor and CO gas sensor. Three kinds of fire characteristic signals are obtained as the expanding rate of fire image area. CO gas density, and temperature. BP neural net technique was synthesized to realize the data fusion of different fire signals, and identify the fire into smoldering fire, developed fire and non-fire source. Then according to the fire properties the fuzzy logic rules were organized to identify the probability of fire danger. The intelligent fire detecting system can reach the aim of fire alarm and reducing mis-alarm.
引用
收藏
页码：1043 / 1048
页数：6
相关论文
共 50 条
  • [31] Neural fuzzy system design in forest fire detection
    Gudikandhula Narasimha Rao
    Peddada Jagadeeswara Rao
    Rajesh Duvvuru
    Kondapalli Beulah
    E. Laxmi Lydia
    Prasanthi Rathnala
    Bangaru Balakrishna
    Vijaya Raju Motru
    [J]. Microsystem Technologies, 2024, 30 : 455 - 467
  • [32] Neural fuzzy system design in forest fire detection
    Rao, Gudikandhula Narasimha
    Rao, Peddada Jagadeeswara
    Duvvuru, Rajesh
    Beulah, Kondapalli
    Lydia, E. Laxmi
    Rathnala, Prasanthi
    Balakrishna, Bangaru
    Motru, Vijaya Raju
    [J]. MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS, 2024, 30 (04): : 455 - 467
  • [33] Compound Fire Detection Algorithm Based on Fuzzy Neural Network
    Feng, Yang
    Na, Qu
    Chao, Li
    [J]. PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MACHINERY, ELECTRONICS AND CONTROL SIMULATION (MECS 2017), 2017, 138 : 718 - 722
  • [34] System fuzzy modeling based on fuzzy neural network
    [J]. Harbin Gongye Daxue Xuebao, 5 (79-81, 85):
  • [35] Study on application of adaptive fuzzy control and neural network in the automatic leveling system
    Xu Xiping
    Zhao Zizhao
    Lan Weiyong
    Sha Lei
    Qian Cheng
    [J]. SELECTED PAPERS FROM CONFERENCES OF THE PHOTOELECTRONIC TECHNOLOGY COMMITTEE OF THE CHINESE SOCIETY OF ASTRONAUTICS 2014, PT II, 2015, 9522
  • [36] Application of Fuzzy Neural Network Controller for Cement Rotary Kiln Control System
    Xue, Zeng Tao
    Li, Zheng
    [J]. ADVANCED MATERIALS AND ENGINEERING MATERIALS, PTS 1 AND 2, 2012, 457-458 : 531 - 535
  • [37] Application of Fuzzy Neural Network for Evaluating Sustainable Development with Energy Indicators System
    Ran, Wei
    [J]. 2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 2, PROCEEDINGS, 2009, : 296 - 299
  • [38] Application of adaptive fuzzy wavelet neural network in AC servo control system
    School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing
    Jiangsu
    210094, China
    [J]. Binggong Xuebao, 5 (781-788):
  • [39] Application study of ILC with fuzzy neural network in shaking table control system
    Chen, Jianqiu
    Zhang, Xinzheng
    Tan, Ping
    Zhou, Fulin
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007), 2007,
  • [40] The Application of Fuzzy Neural Network in the State Evaluation of Marine Electric Propulsion System
    Ren Zhenzhen
    [J]. ISTAI 2016: PROCEEDINGS OF THE SIXTH INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, 2016, : 103 - 106
12345