Abstract: To solve the problem of tool wear monitoring in the machining process of titanium alloy structural parts under complex operational conditions, a novel tool wear monitoring method based on the power spectrum energy of spindle vibration was proposed. Firstly, the energy indicators of the 0~7f₀ frequency band reflecting the tool wear degradation process, as well as the tooth passing frequency f₀ and the frequency multiplier 3f₀ amplitude indicators are extracted through power spectrum analysis as sensitive information for monitoring the tool degradation process. Secondly, a method is proposed to determine the tool wear fault threshold based on the machining quality constraints of structural parts. Finally, the feasibility of this method is verified on the cavity structure. The results show that compared with the tool wear monitoring methods based on FFT spectrum, time-domain statistical, and wavelet packet frequency band energy, the proposed tool wear monitoring method is more effective and can accurately identify the early tool wear.