| With the development of embedded technology, sensor technology and wireless communication technology, data acquisition, processing and wireless sensor network technology has been widely used in various fields of today’s society. In bridge health monitoring, usually in the bridge laying a large number of wireless sensor nodes, and through the acquisition of bridge structure state related data to bridge in special climate,complex traffic environment and bridge structure condition of abnormal warning signals,for bridge management and maintenance and maintenance to provide a scientific basis.Wireless sensor networks need to collect and send a large number of data in real time,which brings great pressure to the communication bandwidth of the whole network. In addition, wireless data transmission accounted for the vast majority of the energy consumption of nodes, so to try to prolong the life of sensor nodes must reduce the amount of data transmission, and data compression effective means is to solve the above problems..Firstly, for bridge health monitoring problem based on topological structure of wireless sensors for structural health monitoring, and from the aspects of the node energy consumption and network bandwidth limited demonstrates the necessity of data compression algorithm.Secondly, in view of the bridge vibration data acquisition, processing and transmission requirement. In this paper, the design of the based on Embedded Technology of wireless sensor front-end node, the node contains vibration data acquisition module,DSP data processing module and a wireless transceiver module. The module of the vibration data sampling precision reached to 16 bit, the highest sampling rate reached to250 Kbps.In addition, a compression algorithm based on the correlation of sampled data is proposed in this paper, which can be used for lossless compression of the vibration data.The content consists of two parts, which are the definition of the data format and the implementation of the compression algorithm. The data format adopts the variable lengthframe format to obtain the optimal compression effect. The compression algorithm is mainly divided into three steps, respectively, calculate the difference of adjacent data bitwise XOR and data grouping. Experimental results show that the proposed method can effectively compress the data, and has obvious advantages compared to the classic Hoffman compression coding and ZLIB compression coding. In order to further verify the performance of the compression method, in the design of the sensor node platform for practical verification. Through the actual verification platform, the algorithm can guarantee for the effective data compression based can realize data real-time transmission. |
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