【摘要】：隨著當(dāng)代工業(yè)技術(shù)不斷向前發(fā)展,長(zhǎng)距離管道泄漏點(diǎn)檢測(cè)技術(shù)取得了很大的研究成果,此類技術(shù)屬于這個(gè)領(lǐng)域內(nèi)的主要探索目標(biāo)之一,但是到現(xiàn)在為止每種泄漏點(diǎn)檢測(cè)的方法依然不全面完善,還有很多技術(shù)難點(diǎn)問(wèn)題等待解決。本文主要針對(duì)的是長(zhǎng)距離礦漿管道的泄漏點(diǎn)檢測(cè)分析研究,針對(duì)其復(fù)雜的工況、特殊的介質(zhì)以及準(zhǔn)確性和快速性等,對(duì)長(zhǎng)距離礦漿管道泄漏檢測(cè)點(diǎn)檢測(cè)技術(shù)進(jìn)行了全面探索,采用了兩種改進(jìn)后的方法,并用某管道數(shù)據(jù)驗(yàn)證了方法的有效性。本文主要針對(duì)長(zhǎng)距離礦漿管道泄漏點(diǎn)檢測(cè)的準(zhǔn)確性問(wèn)題進(jìn)行了以下工作：1、對(duì)傳統(tǒng)的管道泄漏定位模型進(jìn)行了改進(jìn),利用基于GPS和PAC的數(shù)據(jù)采集系統(tǒng)對(duì)聲波信號(hào)進(jìn)行同步采集,使信號(hào)到達(dá)首站控制機(jī)的時(shí)間差的誤差最�。煌瑫r(shí)分析并確定了不同管道中介質(zhì)流動(dòng)的速度對(duì)聲波波速的影響,利用改進(jìn)的模型進(jìn)行理論計(jì)算,較傳統(tǒng)的定位模型定位精度有一定提高。2、針對(duì)長(zhǎng)距離礦漿管道系統(tǒng)的噪聲源進(jìn)行了分析確定。并且針對(duì)這些噪聲,使用了一種基于自適應(yīng)算法的噪聲抑制模型。該模型利用噪聲和有用信號(hào)之間的相關(guān)長(zhǎng)度的差異,對(duì)泄漏信號(hào)中的噪聲進(jìn)行抑制。提高了檢測(cè)信號(hào)的信噪比。3、針對(duì)長(zhǎng)距離礦漿管道使用了一種噪聲分離及泄漏識(shí)別的方法。該方法利用盲信號(hào)理論下的核獨(dú)立元分析法以及支持向量機(jī)理論下的最小二乘支持向量機(jī)的方法對(duì)信號(hào)進(jìn)行去噪和泄漏識(shí)別。通過(guò)仿真研究比較系統(tǒng)的穩(wěn)定性和準(zhǔn)確性更好,可以更快的檢測(cè)泄漏的發(fā)生,增強(qiáng)系統(tǒng)定位的準(zhǔn)確性。文中利用某管道的歷史數(shù)據(jù)對(duì)管道泄漏點(diǎn)檢測(cè)系統(tǒng)進(jìn)行分析研究,通過(guò)仿真結(jié)果可以表明在通過(guò)噪聲抑制模型的性能有一定提高,信噪比最大提高6.1740dB�；贙ICA和LS-SVM的噪聲分離及識(shí)別仿真研究中,我們可以清楚的看出該方法能較準(zhǔn)確的找到泄漏發(fā)生的時(shí)間以及對(duì)故障的類型進(jìn)行識(shí)別,同時(shí)較其他方法在快速性和準(zhǔn)確性的比較有一定提高。
[Abstract]:With the development of modern industrial technology, great achievements have been made in long distance pipeline leak detection technology, which is one of the main exploration goals in this field. However, up to now, every leak detection method is still incomplete, and there are still many technical difficulties to be solved. This paper mainly aims at the analysis and analysis of leakage point of long distance slurry pipeline. In view of its complex working condition, special medium, accuracy and rapidity, the leakage detection point detection technology of long distance slurry pipeline is comprehensively explored. Two improved methods are adopted and the validity of the method is verified by a pipeline data. In this paper, aiming at the accuracy of leak detection in long distance slurry pipeline, the following work is done: 1, the traditional pipeline leak location model is improved, and the sound wave signal is collected synchronously by using the data acquisition system based on GPS and PAC. At the same time, the influence of the velocity of medium flow in different pipes on the acoustic wave velocity is analyzed and determined, and the theoretical calculation is carried out by using the improved model. Compared with the traditional positioning model, the positioning accuracy is improved by 0.2. The noise source of the long distance slurry pipeline system is analyzed and determined. For these noises, a noise suppression model based on adaptive algorithm is proposed. The model uses the difference of correlation length between the noise and the useful signal to suppress the noise in the leakage signal. The signal-to-noise ratio (SNR) of the detected signal is improved. A method of noise separation and leakage identification is used for long distance slurry pipeline. In this method, the kernel independent element analysis method based on blind signal theory and the least squares support vector machine method based on support vector machine theory are used to Denoise and identify the signals. Comparing the stability and accuracy of the system with simulation research, the leak detection can be faster and the accuracy of the system location can be enhanced. In this paper, a pipeline leak detection system is analyzed and studied by using the historical data of a pipeline. The simulation results show that the performance of the model can be improved and the signal-to-noise ratio (SNR) can be increased by 6.1740dB. In the simulation research of noise separation and recognition based on KICA and LS-SVM, we can clearly see that the method can find the time of leakage and identify the type of fault. At the same time, compared with other methods in the comparison of speed and accuracy has a certain improvement.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TD50

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