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| 基于最小二乘支持向量机的声波测距系统消噪处理 | |
| 引用本文： | 张亮亮,何鹏举,秦丽丽,杨晶,宋阿梅,吴琼. 基于最小二乘支持向量机的声波测距系统消噪处理[J]. 传感技术学报, 2012, 25(5): 633-638 |
| 作者姓名： | 张亮亮 何鹏举 秦丽丽 杨晶 宋阿梅 吴琼 |
| 作者单位： | 1. 西北工业大学自动化学院,西安,710129 2. 江西理工大学机电工程学院,江西 赣州,341000 3. 甘肃省地矿局第一地质勘察院,甘肃 天水,741020 |
| 基金项目： | 陕西省基金，总装预言项目，西北工业大学研究生创业种子基金，江西省教育厅基金 |
| 摘 要： | 针对声波测距系统噪声复杂,淹没在噪声中的回波难以检测的问题,以机器统计学习理论为基础,采用最小二乘支持向量机(LS-SVM)建立系统模型,实现了声波测距系统异常值的预测和噪声的消除,并与传统的时间序列分析方法建立的自回归滑动平均求和模型(ARIMA)的消噪效果进行了仿真对比。仿真结果表明,利用最小二乘支持向量机建立的模型预测精度高,能有效地抑制声波测距系统中的噪声。 |
| 关 键 词： | 声波测距系统 消噪处理 最小二乘支持向量机 ARIMA模型 |
The Acoustic Ranging Signal De-noising Based on Least Squares Support Vector Machines |
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| ZHANG Liangliang , HE Pengju , QIN Lili , YANG Jing , SONG Amei , WU Qiong. The Acoustic Ranging Signal De-noising Based on Least Squares Support Vector Machines[J]. Journal of Transduction Technology, 2012, 25(5): 633-638 | |
| Authors: | ZHANG Liangliang HE Pengju QIN Lili YANG Jing SONG Amei WU Qiong |
| Affiliation: | 1.College of automation,Northwestern Polytechnical University,Xi′an 710129,China; 2.Faculty of Mechanical and Electronic Engineering,Jiangxi University of Science and Technology,Ganzhou Jiangxi 341000,China; 3.The First Geology Survey Institute,Gansu Bureau of Geology and Mineral Resources,Tianshui Gansu 741020,China) |
| Abstract: | Aiming at the problem of complex noise in acoustic ranging system and weak echo difficultly detected from signals with high noise,least squares support vector machines based on the statistical learning theory are used in model building to realizes the unusual values detection and noise elimination.Comparing the de-noising result with the traditional autoregressive integrated moving average(ARIMA),simulated results show that the proposed method can improve the prediction accuracy and restrain the noise of acoustic ranging system. |
| Keywords: | the audio ranging signal de-noising processing LS-SVM(Least Squares Support Vector Machines) ARIMA |
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