【摘要】：在當(dāng)代社會(huì)中，隨著科技和經(jīng)濟(jì)的不斷發(fā)展，商業(yè)區(qū)、住宅區(qū)以及校園區(qū)等集中區(qū)域越來(lái)越多，火災(zāi)危害的程度越來(lái)越高。如果人們能在火災(zāi)初期就能及時(shí)發(fā)現(xiàn)并且將其迅速撲滅，那么就能夠使火災(zāi)中的損失降到最低。因此，火災(zāi)探測(cè)技術(shù)在建筑消防系統(tǒng)中的作用顯得很重要，對(duì)其研究也是有很大意義的。 傳統(tǒng)的火災(zāi)探測(cè)系統(tǒng)一般只用到單一探測(cè)器，利用其閾值進(jìn)行火災(zāi)信息的判斷，然而，現(xiàn)在的建筑越來(lái)越復(fù)雜，使得探測(cè)環(huán)境變量以及干擾信號(hào)越來(lái)越多，單一探測(cè)器無(wú)法可靠地探測(cè)火災(zāi)信息。因此，為了提高火災(zāi)探測(cè)器探測(cè)信息的準(zhǔn)確性，目前很多科研工作者正在研制多傳感火災(zāi)探測(cè)器來(lái)取代傳統(tǒng)的火災(zāi)探測(cè)器。 本文結(jié)合火災(zāi)探測(cè)技術(shù)的基本特點(diǎn)，建立起基于多傳感器信息融合的火災(zāi)探測(cè)系統(tǒng)的模型。整個(gè)系統(tǒng)的探測(cè)算法分為三層，即像素層、特征層和決策層，在像素層中，探測(cè)器對(duì)CO氣體、溫度、煙霧等特征參數(shù)進(jìn)行數(shù)據(jù)采集和預(yù)處理；在特征層中，將像素層中得到的信息利用人工神經(jīng)網(wǎng)絡(luò)和線性變換進(jìn)行融合，實(shí)現(xiàn)目標(biāo)對(duì)象特征明火概率、陰燃火概率、非火災(zāi)源概率以及火災(zāi)概率的識(shí)別，為決策層提供直接性判據(jù)和間接性判據(jù)；在決策層中，根據(jù)特征層提供的信息進(jìn)行判斷分析，當(dāng)特征層提供的信息可以判定火災(zāi)情況，則直接輸出，反之，則利用模糊邏輯推理判斷技術(shù)把像素層的數(shù)據(jù)再次進(jìn)行融合得到?jīng)Q策結(jié)果。在本文的研究中，利用MATLAB仿真軟件對(duì)廚房干擾信號(hào)、我國(guó)標(biāo)準(zhǔn)陰燃火以及標(biāo)準(zhǔn)明火三種火災(zāi)信息進(jìn)行了仿真。在特征層仿真研究中，得出了不同神經(jīng)網(wǎng)絡(luò)隱含層的誤差曲線，，由此確立了隱含層數(shù)目為7的BP神經(jīng)網(wǎng)絡(luò)。在決策層仿真研究中，設(shè)定的模糊規(guī)則得出最終的輸出結(jié)果。仿真結(jié)果表明基于信息融合技術(shù)的火災(zāi)探測(cè)系統(tǒng)具有可行性。
[Abstract]:In contemporary society, with the development of science and technology and economy, there are more and more concentrated areas, such as commercial district, residential district and campus area, and the degree of fire hazard is becoming higher and higher. If people can detect and extinguish the fire in time at the beginning of the fire, the damage in the fire can be minimized. Therefore, the role of fire detection technology in building fire protection system is very important, and the study of fire detection technology is of great significance. The traditional fire detection system usually only uses a single detector to judge the fire information by using its threshold value. However, the buildings are becoming more and more complex, which makes the detection of environmental variables and interference signals more and more. A single detector cannot reliably detect fire information. Therefore, in order to improve the accuracy of fire detection information, many researchers are developing multi-sensor fire detectors to replace the traditional fire detectors. Based on the basic characteristics of fire detection technology, a fire detection system model based on multi-sensor information fusion is established in this paper. The detection algorithm of the whole system is divided into three layers: pixel layer, feature layer and decision layer. In the pixel layer, the detector collects and preprocesses the characteristic parameters such as CO gas, temperature, smoke, etc. The information obtained in the pixel layer is fused with artificial neural network and linear transformation to realize the recognition of the target object's characteristic open fire probability, smoldering fire probability, non-fire source probability and fire probability. Direct criterion and indirect criterion are provided for the decision layer. In the decision layer, the information provided by the feature layer is judged and analyzed. When the information provided by the feature layer can determine the fire situation, it is directly output. Then the decision result is obtained by using fuzzy logic reasoning and judgment technology to fuse the pixel layer data again. In this paper, MATLAB simulation software is used to simulate three kinds of fire information, such as kitchen disturbance signal, standard smoldering fire and standard open fire in China. In the characteristic layer simulation, the error curves of the hidden layers of different neural networks are obtained, and the BP neural networks with the number of hidden layers 7 are established. In the study of decision-making simulation, the fuzzy rules are set to get the final output. The simulation results show that the fire detection system based on information fusion technology is feasible.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TU892

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