CAJ | 학술논문

为解决通讯环境较差的农业机械作业状态数据的传输难题，该文提出了基于改进Huffman编码技术的数据压缩方法实现数据的压缩、传输、解析与解压。数据压缩与解压测试的结果表明，数据采集周期为5 s、数据长度为918.38 kb时，基于改进Huffman算法压缩的数据长度为412.56 kb，同样条件下对比传统Huffman算法压缩的数据长度498.56 kb小86 kb，压缩率从传统Huffman算法的45.71%提升至改进Huffman算法的55.08%；传统Huffman算法中数据传输出错率和数据传输丢包率为2.47%和4.18%，而在同样传输要求下的筛选压缩传输中数据传输出错率和数据传输丢包率降至2.06%和0.78%。该方法能满足农业机械作业状态数据压缩传输要求，在单个数据包数据较少、传输时间短的压缩传输方式下能够获得较低的传输出错率和丢包率，且该方法具有计算量少、压缩效率较高特点，适合在农业机械作业区域进行数据传输。
위해결통신배경교차적농업궤계작업상태수거적전수난제，해문제출료기우개진Huffman편마기술적수거압축방법실현수거적압축、전수、해석여해압。수거압축여해압측시적결과표명，수거채집주기위5 s、수거장도위918.38 kb시，기우개진Huffman산법압축적수거장도위412.56 kb，동양조건하대비전통Huffman산법압축적수거장도498.56 kb소86 kb，압축솔종전통Huffman산법적45.71%제승지개진Huffman산법적55.08%；전통Huffman산법중수거전수출착솔화수거전수주포솔위2.47%화4.18%，이재동양전수요구하적사선압축전수중수거전수출착솔화수거전수주포솔강지2.06%화0.78%。해방법능만족농업궤계작업상태수거압축전수요구，재단개수거포수거교소、전수시간단적압축전수방식하능구획득교저적전수출착솔화주포솔，차해방법구유계산량소、압축효솔교고특점，괄합재농업궤계작업구역진행수거전수。
In order to solve the poor communication environment problem of agricultural machinery operation state data transmission caused by the unbalanced coverage of a mobile communication base station, a data filtering and data compression method based on an improved Huffman coding technique was proposed for data selecting, compression, transmission, parsing, and extracting in this paper. First, the agricultural machinery operation data types, exchange mode, and compression mode were defined. Then, data collection and exchange were realized based on a Compass/GPS dual-mode state data collection terminal. Finally, an improved Huffman coding technique was proposed. At present, most of the data transmission is using a compression-decompression method to ensure data integrity of data transmission, which can reduce the data traffic and save many communication costs, but its disadvantages are also obvious. The disadvantages are fewer on the terminal in the data transmission, and are mainly manifested in the need to compress the data of each group, leading to delayed transmission time, which will affect the platform performance. Considering the common problem of an agricultural machinery state data collection terminal and monitoring platform, a driving state data optimization method combined with platform data recognition was proposed in this paper, whose research has practical significance for the platform designing of data collection, transmission, and monitoring. To achieve data transmission and access, the design of a monitoring platform necessarily must use data extraction methods combined with terminal data optimization. That is, adding the terminal data processing optimization algorithm while designing a terminal data transmission module to overcome the pressure of the data management system for wireless communications and the corresponding pressure for a backstage management system. At the same time, adding data extraction and recognition algorithms while monitoring platform receiving data could optimize the expression of data and reduce the amount of data, so as to improve the efficiency of the whole system. Data compression and decompression testing results showed that it could obtain a 55.08% compression ratio with 412.56 kb transmission operation data length by the data acquisition cycle of 5 seconds, and the error rate of data transmission and data transmission packet loss rate were 2.47% and 4.18% respectively, while the error rate of data transmission and data transmission packet loss rate fell to 2.06% and 0.78% respectively at the same screening requirements of the selecting compression and transmission. This method can achieve the requirements of agricultural machinery operation state data compression and transmission. In the compression and transmission mode of single data packet with less data and short transmission time, it could obtain a lower transmission error rate and transmission packet loss rate. Moreover, the method has less computation and high compression efficiency characteristics, which are suitable for data transmission in the agricultural machinery operation area.