發(fā)布時間：2019-04-19 09:54

【摘要】：礦井瓦斯一直是我國煤礦主要的災(zāi)害形式之一，并嚴(yán)重困擾著煤礦的安全生產(chǎn)。研究礦井日常檢/監(jiān)測數(shù)據(jù)的有效處理及其預(yù)測預(yù)警應(yīng)用，有利于拓展安全監(jiān)測監(jiān)控系統(tǒng)的功能，是提高瓦斯災(zāi)害預(yù)警能力的重要手段。本論文在分析礦井瓦斯檢/監(jiān)測數(shù)據(jù)特征及其集成管控模式的基礎(chǔ)上，深入研究了基于云計算數(shù)據(jù)集成模式下的礦井瓦斯預(yù)警分析理論和方法。 研究了礦井瓦斯檢/監(jiān)測數(shù)據(jù)的特點及其集成管控模式。分析了瓦斯檢/監(jiān)測數(shù)據(jù)的特征，并對于環(huán)境、人為、管理等因素影響下存在的異常數(shù)據(jù)、數(shù)據(jù)缺失問題，針對其特征進(jìn)行平滑處理，使其形成完整的監(jiān)測數(shù)據(jù)序列，符合監(jiān)測數(shù)據(jù)整體統(tǒng)計特性，并構(gòu)建了云計算模式下檢/監(jiān)測數(shù)據(jù)集成管控模式。 研究了礦井瓦斯?jié)舛茸兓厔蓊A(yù)測預(yù)警方法。在瓦斯監(jiān)測數(shù)據(jù)預(yù)處理的基礎(chǔ)上，基于時間序列分析的自回歸滑動平均（ARMA）模型，建立了適用于實時監(jiān)測數(shù)據(jù)的瓦斯?jié)舛葎討B(tài)趨勢預(yù)測預(yù)警分析模型，結(jié)合實時預(yù)測結(jié)果與所在時段瓦斯監(jiān)測數(shù)據(jù)的統(tǒng)計特征實現(xiàn)了瓦斯?jié)舛茸兓厔莸膭討B(tài)預(yù)警。 研究了礦井瓦斯突出危險性預(yù)測預(yù)警方法。通過分析瓦斯實時監(jiān)測數(shù)據(jù)的特征，提取反映瓦斯?jié)舛葘崟r變化趨勢的參數(shù)、瓦斯?jié)舛茸兓俾实膮?shù)以及用于表達(dá)瓦斯涌出特征的參數(shù)，結(jié)合防突檢測參數(shù)，，基于v-支持向量機(jī)（v-SVM）模型，構(gòu)建了瓦斯突出危險性預(yù)測預(yù)警模型，結(jié)合瓦斯突出危險性預(yù)測結(jié)果與防突檢測數(shù)據(jù)的統(tǒng)計特征，實現(xiàn)了瓦斯突出危險性預(yù)警。 研究了礦井瓦斯預(yù)警的云計算模型架構(gòu)�；谠朴嬎愕脑恚瑯�(gòu)建了應(yīng)用于礦井瓦斯預(yù)警分析的云計算模式的物理架構(gòu)及其云計算平臺模式，并將礦井瓦斯檢/監(jiān)測數(shù)據(jù)處理及預(yù)測預(yù)警算法予以封裝，為瓦斯預(yù)警計算的程序化服務(wù)構(gòu)建了云計算模式，實現(xiàn)了高效的預(yù)警分析。 研究了云計算數(shù)據(jù)集成模式下瓦斯預(yù)警分析應(yīng)用。基于所建立的瓦斯預(yù)警數(shù)學(xué)模型，將瓦斯檢/監(jiān)測數(shù)據(jù)處理的云計算模式應(yīng)用于現(xiàn)場預(yù)警分析，經(jīng)過實際檢/監(jiān)測數(shù)據(jù)的對照檢驗，表現(xiàn)出了良好的適用性和有效性。 本論文研究的云計算數(shù)據(jù)集成模式下瓦斯預(yù)警分析理論和方法，適用于煤礦現(xiàn)場的瓦斯預(yù)警分析應(yīng)用，為煤礦瓦斯災(zāi)害防治提供了新的數(shù)字化平臺構(gòu)建方法和手段。
[Abstract]:Mine gas has always been one of the main disaster forms of coal mines in our country, and seriously perplexed the safety production of coal mines. To study the effective processing of mine daily inspection / monitoring data and its prediction and early warning application is helpful to expand the function of safety monitoring and monitoring system and is an important means to improve the ability of gas disaster early warning. On the basis of analyzing the characteristics of mine gas inspection / monitoring data and its integrated management and control mode, this paper deeply studies the theory and method of mine gas early warning analysis based on cloud computing data integration mode. The characteristics of mine gas inspection / monitoring data and its integrated control mode are studied. In this paper, the characteristics of gas inspection / monitoring data are analyzed, and the problems of abnormal data and data missing under the influence of environment, man-made, management and other factors are analyzed, and the characteristics of gas inspection / monitoring data are smoothed to form a complete monitoring data sequence. In accordance with the overall statistical characteristics of monitoring data, the integrated control model of inspection / monitoring data under cloud computing model is constructed. The prediction and early warning method of gas concentration change trend in mine is studied. Based on the pretreatment of gas monitoring data and the autoregressive moving average (ARMA) model based on time series analysis, a prediction and early warning model of gas concentration dynamic trend is established, which is suitable for real-time monitoring data. Combined with the real-time prediction results and the statistical characteristics of the gas monitoring data in the time period, the dynamic early-warning of the gas concentration change trend is realized. The prediction and early warning method of mine gas outburst risk is studied. By analyzing the characteristics of real-time gas monitoring data, the parameters reflecting the trend of real-time change of gas concentration, the parameters of gas concentration change rate and the parameters used to express the characteristics of gas emission are extracted, and combined with the detection parameters of outburst prevention. Based on the v-support vector machine (v-SVM) model, a gas outburst risk prediction and early warning model is constructed. Based on the statistical characteristics of gas outburst risk prediction results and outburst prevention detection data, the gas outburst risk early warning is realized. The cloud computing model architecture of mine gas early warning is studied. Based on the principle of cloud computing, the physical structure and cloud computing platform model of cloud computing model applied to mine gas early warning analysis are constructed, and the mine gas inspection / monitoring data processing and prediction and early warning algorithm are encapsulated. The cloud computing mode is constructed for the programmed service of gas early warning calculation, and the efficient early warning analysis is realized. The application of gas early warning analysis in cloud computing data integration mode is studied. Based on the established gas early warning mathematical model, the cloud computing model of gas detection / monitoring data processing is applied to the field early warning analysis. Through the comparison test of actual inspection / monitoring data, it shows good applicability and effectiveness. This paper studies the theory and method of gas early warning analysis under cloud computing data integration mode, which is suitable for the application of gas early warning analysis on the spot of coal mine, and provides a new method and means of constructing digital platform for the prevention and control of coal mine gas disaster.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TD712.7

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本文編號：2460839