针对寻峰算法不能自适应检测光纤布拉格光栅(FBG)多峰值光谱的问题，提出了一种多峰自适应寻峰算法。采用滑动均值滤波法对光谱信号进行去噪预处理，并结合希尔伯特变换对多峰光谱自适应峰值区域分割；分析了谱峰的不对称特性，对单峰光谱采用基于非对称广义高斯模型的峰值修正策略，实现了峰值的精确定位。实验结果表明，与对比算法相比所提算法寻峰精度最高，稳定性最好，检测误差在1 pm 以下，对分布式传感网络中的多峰值检测具有借鉴意义。

To the problem of the peak detection that could not be adaptively solved in the multi-peak fiber Bragg grating (FBG) signal, a self-adaptive multi-peak detection algorithm is proposed. This algorithm uses the sliding mean filtering method to remove the noise in spectral signal, and combines with the Hilbert transform to adaptively segment the peak area of the multi-peak spectrum. By analyzing the asymmetric characteristic of spectral peak, a peak value is compensated by the strategy based on the asymmetric generalized Gaussian model for improving position precision of spectral peak. Experimental results show that the proposed algorithm could gain higher accuracy and better stability than the comparing algorithms, and the detection error is under 1 pm. The proposed algorithm impacts on the multi-peak detection of distributed sensor networks.