Design an optical communication weak signal detection method based on big data mining with the aim of efficiently and accurately detecting weak signals submerged in noise in optical communication. The noise component in the optical communication signal is completely removed based on improved EMD and singular value decomposition. Af- ter the parameters of the support vector machine are optimized by the gray wolf algorithm , the signal classification hy- perplane is constructed from the support vector machine model , and the weak signals in the samples are classified and detected. The experimental results show that after denoising the optical communication signal using the proposed meth- od , the signal-to-noise ratio of the signal decreases , with a maximum value of only 0. 01 dB. The fluctuation ampli- tude of the weak signal detected by the proposed method highly matches the actual amplitude of the weak signal , with an error of no more than 1% , 100% detect samples of weak optical communication signals submerged in noise.