本文選題：結(jié)構(gòu)健康監(jiān)測 + 無線傳感器��； 參考：《哈爾濱工業(yè)大學(xué)》2014年碩士論文

【摘要】：無線傳感器和無線傳感網(wǎng)絡(luò)技術(shù)是結(jié)構(gòu)健康監(jiān)測的發(fā)展趨勢,無線傳感器不僅具有數(shù)據(jù)智能處理能力,而且具“無需布線、布置靈活”的特點,目前在國內(nèi)外的高層和大跨橋梁中得到了廣泛地應(yīng)用,但是無線傳感器在數(shù)據(jù)傳輸過程中,由于環(huán)境因素、布設(shè)方式以及同頻段的其它設(shè)備的干擾等原因,導(dǎo)致無線傳感器在數(shù)據(jù)傳輸過程中會出現(xiàn)數(shù)據(jù)丟失現(xiàn)象。傳感器的監(jiān)測數(shù)據(jù)在無線傳輸中丟失,不僅影響數(shù)據(jù)本身質(zhì)量,而且還影響基于監(jiān)測數(shù)據(jù)的后續(xù)結(jié)構(gòu)分析和安全評估。因此,本文研究結(jié)構(gòu)健康監(jiān)測無線傳感器的數(shù)據(jù)丟失恢復(fù)方法。 本文的主要研究內(nèi)容： 研究基于哈夫曼編碼和指數(shù)哥倫布編碼的無線傳感器數(shù)據(jù)壓縮方法。首先研究這兩種編碼方法的原理,然后設(shè)計無線傳感器原始數(shù)據(jù)的預(yù)處理方法,最后給出在無線傳感器硬件上嵌入算法的實現(xiàn)步驟。 提出一種基于無損壓縮編碼和隨機冗余矩陣的無線傳感器數(shù)據(jù)傳輸?shù)那度胧剿惴�。根�?jù)隨機冗余矩陣數(shù)學(xué)模型,對隨機冗余矩陣在發(fā)生數(shù)據(jù)丟失后的情況,討論數(shù)據(jù)恢復(fù)失敗概率的上限,驗證隨機冗余矩陣在數(shù)據(jù)恢復(fù)時的有效性。 研究提出的數(shù)據(jù)丟失恢復(fù)算法的數(shù)值模擬和實際工程應(yīng)用效果,對西堠門大橋結(jié)構(gòu)健康監(jiān)測系統(tǒng)中的索力儀、橋面加速度傳感器、傾斜度儀、溫度計、濕度計、液壓儀等多種類型的傳感器數(shù)據(jù)進行模擬研究,采用哥倫布壓縮編碼和隨機冗余矩陣,驗證方法的效果。同時將算法嵌入Imote2無線加速度傳感器里,對哈爾濱松浦大橋進行現(xiàn)場實驗,驗證方法的有效性。
[Abstract]:Wireless sensor and wireless sensor network technology is the development trend of structural health monitoring. Wireless sensor not only has the capability of intelligent data processing, but also has the characteristics of "no wiring, flexible layout". At present, it has been widely used in high-rise and long-span bridges at home and abroad. However, in the process of wireless sensor data transmission, due to environmental factors, layout methods and interference of other devices in the same frequency band, etc. The wireless sensor will lose data in the process of data transmission. The loss of sensor monitoring data in wireless transmission not only affects the quality of the data itself, but also affects the subsequent structural analysis and security assessment based on the monitoring data. Therefore, the data loss recovery method of structured health monitoring wireless sensor is studied in this paper. The main contents of this paper are as follows: The data compression method of wireless sensor based on Huffman coding and exponential Columbus coding is studied. Firstly, the principle of the two coding methods is studied, then the preprocessing method of the raw data of the wireless sensor is designed. Finally, the steps of embedding the algorithm on the hardware of the wireless sensor are given. An embedded algorithm for wireless sensor data transmission based on lossless compression coding and random redundancy matrix is proposed. According to the mathematical model of random redundancy matrix, the upper limit of data recovery failure probability is discussed for the case of random redundancy matrix after data loss, and the validity of random redundancy matrix in data recovery is verified. The numerical simulation and practical application effect of the proposed data loss recovery algorithm are studied. The cable dynamometers, bridge acceleration sensors, tilt meters, thermometers, hygrometers in the structural health monitoring system of Xihoumen Bridge are studied. Many kinds of sensor data, such as hydraulic instrument, are simulated and studied. Columbus compression coding and random redundancy matrix are used to verify the effectiveness of the method. At the same time, the algorithm is embedded in the Imote2 wireless acceleration sensor, and the field experiment of Songpu Bridge in Harbin is carried out to verify the effectiveness of the method.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TU317

【相似文獻】

相關(guān)期刊論文 前10條

1 熊海貝;李志強;;結(jié)構(gòu)健康監(jiān)測的研究現(xiàn)狀[J];結(jié)構(gòu)工程師;2006年05期

2 陳啟飛;李愛群;繆長青;孫大松;;淮安大橋結(jié)構(gòu)健康監(jiān)測和評估系統(tǒng)研究與實施[J];特種結(jié)構(gòu);2007年02期

3 王利恒;薛景鋒;宋昊;郭偉;張立U，

本文編號：1797028