The current noise reduction methods have noise residue and inadequate adaptability, so that the abnormal detection index is greatly affected by noise, a sensor fault detection method based on double noise reduction and fuzzy index for central air conditioning is proposed. Complete EEMD with adaptive noise (CEEMDAN) is used to extract k-order modes and replace modal estimation to achieve initial noise reduction. For the false mode appearing in the early stage, firstly, the noise-containing components are screened by the correlation coefficient criterion to retain the effective information as much as possible. Then, singular value difference spectrum is calculated to determine the order of denoising and singular value decomposition ( SVD) to complete the secondary denoising. The experimental data of central air conditioning system are used to verify the proposed method, this method has good ability of noise reduction and sensitive feature screening, the SNR was improved by 20. 203 7 dB, the mean square error was reduced by 48. 75% on average, the fault detection accuracy was improved by 8. 67% on average, and the response speed was improved by 33. 3%.