本文選題：探地雷達(dá)　切入點(diǎn)：無損檢測　出處：《湖南大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：我國高速的城市化進(jìn)程使道路交通和地下管道處于超高負(fù)荷的運(yùn)行狀態(tài)中，大量基礎(chǔ)設(shè)施瀕臨老化，地下的過度開發(fā)利用都使得城市地下空間存在眾多隱伏病害，隨時(shí)都有可能危及公眾的生命財(cái)產(chǎn)安全。探地雷達(dá)檢測技術(shù)以其高效、連續(xù)、無損、經(jīng)濟(jì)和操作簡單方便等特征在準(zhǔn)確探測此類病害中有獨(dú)特的作用，在許多工程應(yīng)用領(lǐng)域中能經(jīng)常見到它的蹤跡，是淺層探測的有效方法。而今越來越多的學(xué)者投入到探地雷達(dá)的研究當(dāng)中，不斷完善和發(fā)展該技術(shù)，使它擁有廣闊的應(yīng)用前景。 從目前的應(yīng)用效果來看，在圖像的解釋判別方面存在分歧，每個(gè)人的知識儲(chǔ)備、對原理和方法的認(rèn)識深度及積累的經(jīng)驗(yàn)不同，對圖像的解釋判別也會(huì)有所差異。因此建立常見地下目標(biāo)體的圖像數(shù)據(jù)庫顯得尤為重要，正確的解釋判別雷達(dá)圖像，提高判讀效率和精度，，實(shí)現(xiàn)自動(dòng)判別解釋一直是研究的熱點(diǎn)。對城市地下空間缺陷、空洞及隱伏病害等進(jìn)行探地雷達(dá)探測識別技術(shù)研究，以用于城市道路隱伏災(zāi)害全面系統(tǒng)地排查和科學(xué)防災(zāi)預(yù)測評估具有重要的現(xiàn)實(shí)意義和應(yīng)用價(jià)值。 本文圍繞無開挖城市地下空間隱伏病害的雷達(dá)探測識別問題展開研究，用不同材質(zhì)的目標(biāo)體模擬地下隱伏病害，以土壤為填充介質(zhì)進(jìn)行試驗(yàn)，讓目標(biāo)體周圍的環(huán)境更接近實(shí)際狀況，以期獲得更準(zhǔn)確的圖像。在不同埋深、不同間距和不同形狀的工況下，對不同材質(zhì)的目標(biāo)體用不同頻率天線進(jìn)行探測，得到常見目標(biāo)體的雷達(dá)圖像，對其進(jìn)行分析對比得到城市地下空間隱伏病害的雷達(dá)圖像規(guī)律和特征，最終形成有效的雷達(dá)探測圖譜。讓我們能夠詳細(xì)準(zhǔn)確的探查和監(jiān)測地下空間隱伏病害，并能在其對道路交通造成不利影響前，及時(shí)采取科學(xué)的防治措施，把病害消弭于無形，對維護(hù)工程的長遠(yuǎn)質(zhì)量安全能起到非常積極的作用，對提高圖像判別解釋的準(zhǔn)確性有著非常重要的意義。
[Abstract]:With the rapid urbanization of our country, the road traffic and underground pipeline are in the state of ultra-high load, a large number of infrastructure is on the verge of aging, and the over-exploitation and utilization of underground make the city underground space have many hidden diseases. GPR detection technology has a unique role in accurate detection of such diseases with its characteristics of high efficiency, continuity, non-damage, economy and ease of operation. It is an effective method for shallow detection to be found in many engineering applications. Now more and more scholars have put into the research of ground penetrating radar to perfect and develop the technology and make it have a broad application prospect. From the current application results, there are differences in the interpretation and discrimination of images. Everyone has different knowledge reserves, different understanding of principles and methods, and accumulated experience. Therefore, it is very important to establish the image database of common underground objects. The correct interpretation and discrimination of radar images can improve the efficiency and accuracy of interpretation. The realization of automatic discriminant interpretation has always been a hot research topic. The research of ground penetrating radar detection and identification technology is carried out on the defects of urban underground space, voids and hidden diseases, etc. It is of great practical significance and practical value to apply it to the comprehensive and systematic investigation of hidden disasters on urban roads and to the scientific prediction and evaluation of disaster prevention. In this paper, the problem of radar detection and identification of latent diseases in excavated urban underground space is studied. The underground hidden diseases are simulated with different materials, and the soil is used as the filling medium to carry out the experiment. The environment around the target is closer to the actual situation, in order to obtain more accurate image. Under different conditions of buried depth, different spacing and different shape, the target body of different material is detected with different frequency antenna. The radar images of common objects are obtained, and the laws and characteristics of radar images of hidden diseases in urban underground space are obtained by analyzing and comparing them. Finally, an effective radar detection map will be formed. This will enable us to detect and monitor hidden diseases in underground space in detail and accurately, and to take scientific preventive measures in time before they adversely affect road traffic, so that the diseases can be eliminated in an invisible way. It can play a very positive role in maintaining the long-term quality and safety of engineering, and it is of great significance to improve the accuracy of image discriminant interpretation.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P631.3;TU91

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