拼接异常是光谱在红蓝两端拼接区域表现出的光谱连续性差的一种现象。 在LAMOST的光谱处理中, 仪器的稳定性、 观测条件以及获得的响应函数等问题都是造成拼接异常的原因。 光谱拼接是否正常对于光谱发布等后续工作的质量有重要影响。 提出一种拼接异常光谱的自动检测方法, 有效地提高了工作效率。 该研究可以为LAMOST数据提供一个自动的标记, 来评价拼接质量, 也可以为用户提供一个使用数据时的选择。 该方法首先将待测光谱进行流量归一化、 去除钠线等预处理, 并将其分为红蓝两端； 然后对红蓝两端分别进行拟合； 最后对两条拟合曲线, 选取一系列等波长间隔的点, 计算在这些点处的流量差值, 得到所有流量差值的均值, 标准差, 并且计算两条曲线积分面积的差值； 基于上述统计量, 提出了一个判断光谱是否异常及其异常程度的评价函数。 大量的实验证明, 该方法具有良好的拼接异常光谱检测效果。

Splicing abnormality is a phenomenon of poor continuity spectrum showed in the splicing wavelengths of the red and blue end. In the spectral processing, this problem can be caused by several factors, such as stability of instrument, observation condition, the response function and so on. It has important effect on the spectra quality whether the splicing is normal or not. In the research of this paper we define a tag on the Lamost spectra automatically to evaluate the quality of spectra splicing and it can provide users with a choice when using data. In this paper, a method of automatic detection of splicing abnormality spectra for LAMOST is proposed to improve the work efficiency greatly.With this method, first of all, we get the red end and blue end of the test spectrum in the splicing wavelengths after flux normalized and the feature lines deleted. Then, we fit the continuum in the red and blue end separately. Thirdly, we calculate the differences of flux between the two fitted curves at a series of independent variables with regular intervals. We get the average and standard deviation of the differences and the area of the two curves formed. Based on the statistics above, an evaluation function is presented in this paper which can be used to judge whether the test spectra are normal or not and determine their abnormal class. The method has been proved to have a good effect in the reorganization of splicing abnormality spectra through a mass of experiments.