本文選題：安全預(yù)警 + 多傳感器��； 參考：《太原理工大學(xué)》2014年碩士論文

【摘要】：我國作為資源大國,煤炭在國民生產(chǎn)生活中一直占據(jù)不可替代的作用。據(jù)統(tǒng)計(jì)煤炭在我國能源結(jié)構(gòu)中的占比為74.29%(根據(jù)中國統(tǒng)計(jì)年鑒)。而煤礦事故頻發(fā)又成為影響人民安定幸福的巨大隱患,雖然在近年國家的大力投入和科研工作人員的努力下,安全事故總體呈現(xiàn)明顯下降趨勢,但仍然存在依靠單一傳感器預(yù)警,預(yù)警準(zhǔn)確率低,容易出現(xiàn)誤報(bào)警等現(xiàn)象,既影響生產(chǎn)效率又可能導(dǎo)致煤礦工作人員的麻痹大意。 因此本文致力于構(gòu)建一種綜合多種傳感器信息,并運(yùn)用數(shù)據(jù)融合中分層融合思想的瓦斯預(yù)警系統(tǒng)模型。考慮到煤礦災(zāi)害的不確定性和非線性問題,本文分析了影響事故因素的內(nèi)在關(guān)聯(lián)性,提取多種傳感器信息。通過對多傳感器信息融合一般構(gòu)架結(jié)果分析,提出了由數(shù)據(jù)層、特征層和決策層組成的瓦斯預(yù)警的分層融合結(jié)構(gòu)。 為提高多傳感器監(jiān)測系統(tǒng)預(yù)警的精度,降低多傳感器監(jiān)測過程中出現(xiàn)的狀態(tài)不明或狀態(tài)誤判的發(fā)生率,具體到每個(gè)層次的融合,在數(shù)據(jù)層,運(yùn)用層析分析法確定隸屬度和相應(yīng)權(quán)數(shù),在特征層運(yùn)用模糊評(píng)價(jià)法進(jìn)行數(shù)據(jù)融合,在決策層運(yùn)用D-S證據(jù)理論進(jìn)行數(shù)據(jù)融合的理論模型。對實(shí)驗(yàn)礦井采集到的瓦斯、風(fēng)速和溫度數(shù)據(jù)進(jìn)行了數(shù)據(jù)融合實(shí)驗(yàn)。實(shí)驗(yàn)結(jié)果表明,安全、輕微、危險(xiǎn)三種狀態(tài)隸屬度與初始數(shù)據(jù)比較分別提高8.3%,6%,29.2%,驗(yàn)證了該技術(shù)的有效性。
[Abstract]:China as a large country of resources, coal has been playing an irreplaceable role in national production and life. According to statistics, the proportion of coal in China's energy structure is 74.29. And the frequent occurrence of coal mine accidents has become a huge hidden danger affecting the stability and happiness of the people. Although in recent years, thanks to the great investment of the state and the efforts of scientific research workers, the overall trend of safety accidents has shown a marked downward trend. However, there are still some phenomena such as relying on single sensor, low accuracy and false alarm, which not only affect the production efficiency but also cause the workers to be careless. Therefore, this paper is devoted to constructing a gas early warning system model which synthesizes the information of multiple sensors and applies the idea of hierarchical fusion in data fusion. Considering the uncertainty and nonlinearity of coal mine disaster, this paper analyzes the internal relation of the influencing factors of accidents, and extracts the information of various sensors. Based on the analysis of the results of the general framework of multi-sensor information fusion, a hierarchical fusion structure of gas warning is proposed, which is composed of data layer, feature layer and decision layer. In order to improve the accuracy of multi-sensor monitoring system early warning, reduce the occurrence of state uncertainty or state misjudgment in the process of multi-sensor monitoring, specific to each level of fusion, in the data layer, The membership degree and the corresponding weights are determined by the chromatography analysis method. The fuzzy evaluation method is used to fuse the data in the feature layer and the D-S evidence theory is applied to the theoretical model of the data fusion at the decision-making level. The data fusion experiment of gas, wind speed and temperature collected from experimental mine is carried out. The experimental results show that compared with the initial data, the membership degree of safety, slight and dangerous states is increased by 8.3% and 6% respectively, and the effectiveness of the technique is verified.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TD712

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