结构健康监测无线传感数据丢失恢复的随机冗余矩阵方法

发布时间：2018-04-24 14:29

本文选题：结构健康监测 + 无线传感器　；参考：《哈尔滨工业大学》2014年硕士论文

【摘要】：无线传感器和无线传感网络技术是结构健康监测的发展趋势,无线传感器不仅具有数据智能处理能力,而且具“无需布线、布置灵活”的特点,目前在国内外的高层和大跨桥梁中得到了广泛地应用,但是无线传感器在数据传输过程中,由于环境因素、布设方式以及同频段的其它设备的干扰等原因,导致无线传感器在数据传输过程中会出现数据丢失现象。传感器的监测数据在无线传输中丢失,不仅影响数据本身质量,而且还影响基于监测数据的后续结构分析和安全评估。因此,本文研究结构健康监测无线传感器的数据丢失恢复方法。本文的主要研究内容：研究基于哈夫曼编码和指数哥伦布编码的无线传感器数据压缩方法。首先研究这两种编码方法的原理,然后设计无线传感器原始数据的预处理方法,最后给出在无线传感器硬件上嵌入算法的实现步骤。提出一种基于无损压缩编码和随机冗余矩阵的无线传感器数据传输的嵌入式算法。根据随机冗余矩阵数学模型,对随机冗余矩阵在发生数据丢失后的情况,讨论数据恢复失败概率的上限,验证随机冗余矩阵在数据恢复时的有效性。研究提出的数据丢失恢复算法的数值模拟和实际工程应用效果,对西堠门大桥结构健康监测系统中的索力仪、桥面加速度传感器、倾斜度仪、温度计、湿度计、液压仪等多种类型的传感器数据进行模拟研究,采用哥伦布压缩编码和随机冗余矩阵,验证方法的效果。同时将算法嵌入Imote2无线加速度传感器里,对哈尔滨松浦大桥进行现场实验,验证方法的有效性。
[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.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU317

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