A method for spectral data real-time acquisition with Firm shrinkage wavelet filtering was presented in this paper to improve the performance of biochemical analyzers. Firstly, two spectral lines were acquired and their average spectrum was taken to be processed. Then, the noise variance from two spectral lines was calculated to be used as the next threshold to replace the noise variance estimation based on traditional wavelet denoising. Furthermore, by adjusting the threshold on the line, the average spectrum was processed with Firm wavelet filtering and evaluation criteria were obtained. A relative spectral absorbance experiment was carried out based on the traditional 10 times average method and proposed Firm wavelet filtering method, and the experiment results indicate that the standard deviation of spectral signals obtained from the proposed method has decreased from 0.007 96 to 0.006 97,which means the acquired speed of the proposed method is higher than that of the traditional method. Moreover, the method has been used in a micro biochemical analyzer, tested results show that it optimizes the detection accuracy, reduces the detection time and the detection efficiency has improved by 4-5 times.