【摘要】：隨著高鐵的飛速發(fā)展,讓人們的出行越來(lái)越便捷,為國(guó)家的經(jīng)濟(jì)發(fā)展增添了新的活力。軌道交通作為國(guó)家的經(jīng)濟(jì)大動(dòng)脈,其能否安全運(yùn)營(yíng)直接關(guān)系著人民的財(cái)產(chǎn)生命安全。因?yàn)殍F路具有性能安全、可靠、高效、運(yùn)輸距離長(zhǎng)、運(yùn)輸成本低并且運(yùn)輸能力強(qiáng)、環(huán)保、在大多惡劣天氣下均能進(jìn)行運(yùn)輸作業(yè)等諸多無(wú)與倫比優(yōu)勢(shì),都是公路、海運(yùn)、航空無(wú)法比擬的,所以鐵路是陸上的主要運(yùn)力。 但是,由于我國(guó)的高鐵建成時(shí)間較短、采用的新技術(shù)、新設(shè)備較多,再加之我國(guó)的高鐵覆蓋范圍廣等諸多因素使得高鐵在建設(shè)和運(yùn)營(yíng)上面臨著諸多風(fēng)險(xiǎn)問(wèn)題。因此,為了保障高鐵的安全運(yùn)營(yíng),鐵路部門將系統(tǒng)的安全理論引入到了高鐵的管理中并大力推行針對(duì)高鐵的風(fēng)險(xiǎn)管理體系,加大對(duì)鐵路風(fēng)險(xiǎn)的管控力度,從而降低事故發(fā)生的可能性,為高鐵的安全開(kāi)行保駕護(hù)航。 本文主要針對(duì)高鐵中存在的風(fēng)險(xiǎn)隱患,建立適當(dāng)?shù)脑u(píng)價(jià)指標(biāo)體系,并采用BP神經(jīng)網(wǎng)絡(luò)方法建立模型。從而利用建立的模型對(duì)高鐵進(jìn)行風(fēng)險(xiǎn)評(píng)價(jià)并得出相應(yīng)的結(jié)論和整改建議。 本文首先針對(duì)高鐵上存在的風(fēng)險(xiǎn)隱患,采用故障樹(shù)的方法識(shí)別出影響高鐵安全運(yùn)營(yíng)的主要因素,并建立相應(yīng)的評(píng)價(jià)指標(biāo)體系。然后采用模糊算法量化出20條樣本鐵路的數(shù)據(jù),再采用加權(quán)求和法降低數(shù)據(jù)的主觀性。另外為了簡(jiǎn)化網(wǎng)絡(luò)的輸入,提高了網(wǎng)絡(luò)的收斂速率。因此,當(dāng)輸入數(shù)據(jù)的維數(shù)較大時(shí),采用主成分分析法對(duì)歸一化后的分?jǐn)?shù)進(jìn)行降維處理,從而簡(jiǎn)化BP網(wǎng)絡(luò)結(jié)構(gòu),提高了訓(xùn)練速率。 其次,的指標(biāo)體系進(jìn)行降維處理后,將得到的前15條鐵路的的分?jǐn)?shù)作為BP神經(jīng)網(wǎng)絡(luò)的訓(xùn)練數(shù)據(jù),后5條鐵路的分?jǐn)?shù)作為BP神經(jīng)網(wǎng)絡(luò)的測(cè)試數(shù)據(jù)。測(cè)試結(jié)果表明該風(fēng)險(xiǎn)評(píng)價(jià)模型的預(yù)測(cè)精度達(dá)到了95%,因此該高鐵風(fēng)險(xiǎn)評(píng)價(jià)模型是有效的。 最后,對(duì)京滬高鐵同時(shí)采用BP神經(jīng)網(wǎng)絡(luò)模型評(píng)價(jià)和模糊評(píng)價(jià)法進(jìn)行評(píng)價(jià),分別得出京滬高鐵的相應(yīng)的風(fēng)險(xiǎn)狀況,并對(duì)兩種評(píng)價(jià)法進(jìn)行了分析、比較。此外,還根據(jù)主成分分析法中主成分公式的系數(shù)分析了影響高鐵安全的主要指標(biāo)因素。進(jìn)而,可以將有限的人力物力投入到對(duì)這些主要因素的管控和處理上,將好鋼用在刀刃上,從而對(duì)高鐵的安全管理更加的有的放矢。
[Abstract]:With the rapid development of high-speed rail, people travel more and more convenient, adding new vitality to the country's economic development. As the national economic artery, whether rail transit can operate safely or not is directly related to the safety of people's property. Because the railway has many unparalleled advantages, such as safety, reliability, high efficiency, long transportation distance, low transportation cost, strong transportation capacity, environmental protection, and the ability to carry out transportation operations in most bad weather, all of them are roads, sea transportation, etc. Aviation is incomparable, so rail is the main onshore capacity. However, due to the short construction time of high-speed railway in China, the new technology and equipment, and the wide coverage of high-speed rail in China, the construction and operation of high-speed rail are facing a lot of risk problems. Therefore, in order to ensure the safe operation of the high-speed railway, the railway department has introduced the safety theory of the system into the management of the high-speed railway and vigorously promoted the risk management system for the high-speed railway, and increased the control of railway risks. Thus reducing the possibility of accidents, for the safety of high-speed rail escort. In this paper, an appropriate evaluation index system is established for the hidden risks in high-speed rail, and the BP neural network method is used to establish the model. The model is used to evaluate the risk of high-speed rail, and the corresponding conclusions and corrective suggestions are obtained. In this paper, the main factors affecting the safety operation of high-speed railway are identified by fault tree method, and the corresponding evaluation index system is established. Then the fuzzy algorithm is used to quantify the data of 20 sample railways, and the weighted summation method is used to reduce the subjectivity of the data. In addition, in order to simplify the input of the network, the convergence rate of the network is improved. Therefore, when the dimension of the input data is large, the normalized fraction is reduced by principal component analysis, which simplifies the BP network structure and improves the training rate. Secondly, after dimensionality reduction, the scores of the first 15 railways are taken as the training data of the BP neural network, and the scores of the last 5 railways are taken as the test data of the BP neural network. The test results show that the prediction accuracy of the model is 95%, so the model is effective. Finally, the BP neural network model and fuzzy evaluation method are used to evaluate the Beijing-Shanghai high-speed railway, and the corresponding risk status of the Beijing-Shanghai high-speed railway is obtained, and the two evaluation methods are analyzed and compared. In addition, according to the coefficient of principal component formula in principal component analysis, the main index factors affecting the safety of high iron are analyzed. Furthermore, the limited manpower and material resources can be put into the management and treatment of these main factors, and the good steel can be used on the blade, thus the safety management of high-speed railway can be more targeted.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U238;U298

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