Composite Fire Detection System Using Sparse Representation Method
Joint Authors
Qu, Na
Wang, Jianhui
Liu, Jinhai
Li, Zhonghai
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-11
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
This paper proposes that fire parameter data of smoke, temperature, and CO is fused by sparse representation algorithm.
It designs a kind of overcomplete dictionary and obtains the sparse solution of fire recognition through L1 norm, L3/4 norm, L1/2 norm, and L1/4 norm, respectively, in order to select more suitable norm type.
A comprehensive classification method is proposed for fire identification.
The simulation results show that L1 norm and L3/4 norm are used to obtain the solution with remarkable sparsity and high accuracy.
The comprehensive classification method is more effective than minimum residual method and sum of weight coefficients method.
This paper uses DSP TMS320F28022 as the core chip, TC72 as the temperature sensor, MQ-7 as the CO gas sensor, and MQ-9 as the smoke sensor to design the hardware of fire detection system.
Code Composer Studio (CCS) software is used to compile and debug the program.
Proteus software is used to load the program into the hardware circuit for joint simulation.
The simulation results show that system design is feasible.
American Psychological Association (APA)
Qu, Na& Wang, Jianhui& Liu, Jinhai& Li, Zhonghai. 2017. Composite Fire Detection System Using Sparse Representation Method. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1191496
Modern Language Association (MLA)
Qu, Na…[et al.]. Composite Fire Detection System Using Sparse Representation Method. Mathematical Problems in Engineering No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1191496
American Medical Association (AMA)
Qu, Na& Wang, Jianhui& Liu, Jinhai& Li, Zhonghai. Composite Fire Detection System Using Sparse Representation Method. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1191496
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191496