| 摘要: |
| 采用模式识别方法,用Visual Basic开发了一套熔滴过渡光谱信号模式识别软件系统。根据熔滴过渡与光谱信号的对应关系,以及光谱信号波形的几何特征,抽取了多个关键性的特征参数。基于统计模式识别的Bayes决策理论,建立了相应的识别函数和最小距离法分类器。判别结果表明,利用该系统能够较好地对MIG,MAG和CO2焊熔滴过渡类型进行自动识别,为实现熔化极气体保护焊熔滴过渡自动控制奠定了基础。 |
| 关键词: 熔滴过渡 光谱信号 Bayes决策 模式识别 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金资助项目(59575059) |
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| Pattern recognition of spectrum information of metal transfer |
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YUN Shao-hui1,2, ZHANG De-qin2, HAN Guo-ming3
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1.Institute of Systems Engineering, Tianjin University, Tianjin 300072, China;2.Department of Materials Science and Engineering, Jiujiang University, Jiujiang 332005, Jiangxi, China;3.School of Materials Science and Engineering, Tianjin University, Tianjin 300072, China
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| Abstract: |
| A software system for pattern recognition of spectrum signal of metal transfer mode was developed using Visual Basic. Based on consistency of the spectrum and metal transfer and geometrical pattern features of the spectrum, several key characteristic parameters were extracted.Correspondent recognition function and a minimum-distance classifier were constructed based on Bayes decision theory. The results show that using this system, pattern recognition of metal transfer mode for metal inert-gas welding, metal activegas welding, and CO2 welding can be done automatically. This provides a basis for automatic control of metal transfer in metal gas arc welding. |
| Key words: metal transfer spectrum signal Bayes decision pattern recognition |
