發(fā)布時(shí)間：2018-08-06 10:39

【摘要】：隨著科技創(chuàng)新智能化的發(fā)展越來(lái)越普及,關(guān)乎人們?nèi)粘Ｉ畹幕驹O(shè)施的智能化也在快速發(fā)展,而智能建筑火災(zāi)報(bào)警系統(tǒng)就是其中一個(gè)體現(xiàn)。提高火災(zāi)報(bào)警系統(tǒng)的檢測(cè)效率、靈敏度和可靠性,實(shí)現(xiàn)火災(zāi)的早期發(fā)現(xiàn)和報(bào)警,具有一定的實(shí)用價(jià)值。本論文主要研究了智能建筑火災(zāi)自動(dòng)報(bào)警系統(tǒng)的構(gòu)成原理,介紹了系統(tǒng)有關(guān)的基本概念、基本結(jié)構(gòu)、基本性能。在對(duì)數(shù)據(jù)信息識(shí)別分析和數(shù)字圖像處理技術(shù)識(shí)別等方法研究的基礎(chǔ)上,重點(diǎn)研究了圖像型火災(zāi)現(xiàn)場(chǎng)的信息識(shí)別分析方法。經(jīng)過(guò)對(duì)圖像進(jìn)行濾波預(yù)處理、分割處理、優(yōu)化處理,消除噪聲,獲取優(yōu)化的圖像樣本后,通過(guò)對(duì)火焰的面積大小、形態(tài)變化和邊緣變化等特征信息的提取和檢測(cè),進(jìn)行了一系列火災(zāi)識(shí)別實(shí)驗(yàn),通過(guò)仿真技術(shù),驗(yàn)證火災(zāi)信息識(shí)別算法的可靠性和有效性。本文在火災(zāi)現(xiàn)場(chǎng)圖像探測(cè)中引入BP神經(jīng)網(wǎng)絡(luò)算法,結(jié)合了該算法的特點(diǎn)和相關(guān)的數(shù)學(xué)模型函數(shù),對(duì)實(shí)驗(yàn)進(jìn)行了構(gòu)建,給出了實(shí)驗(yàn)的具體輸入輸出單元的設(shè)計(jì)和神經(jīng)網(wǎng)絡(luò)的具體拓?fù)浣Y(jié)構(gòu)。對(duì)大量火災(zāi)圖像樣本和干擾圖像樣本進(jìn)行了相關(guān)的對(duì)照實(shí)驗(yàn)。由實(shí)驗(yàn)的結(jié)果可以表明,基于BP神經(jīng)網(wǎng)絡(luò)算法的火災(zāi)報(bào)警系統(tǒng)相比于傳統(tǒng)火災(zāi)報(bào)警系統(tǒng)有著更加明顯的優(yōu)勢(shì),大大的減少了火災(zāi)的誤報(bào)率,提高了火情火災(zāi)報(bào)警的精準(zhǔn)度,未來(lái)可以將其廣泛運(yùn)用于現(xiàn)代智能建筑綜合體中。
[Abstract]:With the development of science and technology innovation and intelligence, the intelligence of basic facilities related to people's daily life is also developing rapidly, and the intelligent building fire alarm system is one of the embodiment. It is of practical value to improve the detection efficiency, sensitivity and reliability of the fire alarm system and to realize the early detection and alarm of the fire. In this paper, the principle of automatic fire alarm system for intelligent building is studied, and the basic concepts, basic structure and basic performance of the system are introduced. Based on the research of data information recognition and digital image processing technology, this paper focuses on the information recognition and analysis method of image fire scene. After the image is processed by filtering, segmentation, optimization, noise elimination, and the optimized image samples are obtained, the characteristic information such as flame area, shape change and edge change are extracted and detected. A series of fire identification experiments were carried out to verify the reliability and effectiveness of the fire information recognition algorithm. In this paper, BP neural network algorithm is introduced into the fire scene image detection, combining the characteristics of the algorithm and the related mathematical model function, the experiment is constructed. The design of the experimental input-output unit and the specific topology of the neural network are given. A large number of fire image samples and interference image samples were compared with each other. The experimental results show that the fire alarm system based on BP neural network has more obvious advantages than the traditional fire alarm system, greatly reduces the false alarm rate of fire, and improves the accuracy of fire alarm. In the future, it can be widely used in modern intelligent building complex.
【學(xué)位授予單位】：東華理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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本文編號(hào)：2167474