To solve the problem of weak modulation characteristics and strong background noise ap-pearing in the detection of fault vibration signal of ship propeller cavitation ,a demodulation technique is proposed based on the delay-related noise reduction ,empirical mode decomposition (EMD) and Hil-bert transform .Firstly ,analyses are made of six kinds of demodulation algorithm that refer to the tra-ditional Hilbert transform ,Hilbert transform combined with EMD ,Hilbert transform combined with related noise reduction ,Hilbert transform combined with related reduction noise ,EMD and Hilbert transform ,Hilbert transform combined with delay association and Hilbert transform combined with delay association with EMD .Secondly ,at the signal to noise ratios of - 12 dB ,- 15 dB and - 18 dB , the modulation simulation data is dealt with and the time delay related to the noise reduction algorithm is greatly suppressed .The EMD adaptive frequency technology can find the best band according to di-vision modulation inherent characteristics ,and meanwhile the modulated signal is remarkably im-proved .Finally ,a propeller model test pump needs to go through the cavitation vibration signal de-modulation analysis . The results show that the proposed synthetic algorithm can well identify the cavitation modulation characteristics closely related to the speed and the number of blades .%针对舰艇推进器空化噪声检测中调制特征弱、背景干扰强等问题，提出了一种基于时延相关降噪、经验模态分解（EMD）和希尔波特（Hilbert）变换相结合的解调算法。该算法通过引入时延相关算法有效抑制了背景噪声，并利用 EMD 技术的自适应频带划分功能完成调制特征频带定位，实现了低信噪比条件下调制信号的有效检测。仿真试验证明：该方法在信噪比为-12 dB 、-15 dB 、-18 dB 条件下的检测效果明显优于传统的Hilbert 变换等5种方法，且背景噪声干扰成分得到了有效抑制，调制信号检测效果显著提升。最后，通过推进器空化信号检测台架试验验证表明：该方法能够有效捕捉舰艇空化噪声信号中与转速、叶片数密切相关的调制特征。
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