The passive radio frequency identification (RFID) tag has advantages of compact node size, battery-free and wireless operation, low cost, and less restricted by line-of-sight conditions. To address the limitations of existing RFID vibration sensing research-such as the difficulty in analyzing multi-frequency fault features and the susceptibility of raw signals to environmental noise and spectral interference, this study proposes a multi-frequency fault feature detection method using passive RFID tags for centrifugal pumps. Firstly, a multi-frequency vibration sensing model based on the RFID phase signals is formulated to clarify the mechanism of vibration sensing using phase information. Then, by utilizing the non-uniform random sampling characteristics of the reader, a compressed measurement matrix and a sparse basis are established, transforming the denoising and reconstruction of feature signals into a sparse optimization problem, which is solved using the orthogonal matching pursuit (OMP) algorithm. Finally, the quantum particle swarm optimization (QPSO) algorithm is utilized to optimize the number of iterations and the data length in the reconstruction algorithm. Two indexes-the support reconstruction ratio (quantity of the completeness of diagnostic band recovery) and the diagnostic contrast (quantity of the prominence of fault features) are proposed. The comprehensive evaluation index is constructed as the fitness function to ensure accurate recovery of the fundamental frequency and its harmonics for different fault conditions. Experimental results show that, after processing with the proposed method, the signal-to-noise ratio of the phase signal at the rotating frequency and the second harmonic under the misalignment condition increases to approximately 40 dB, and the full width at half maximum of the spectral peak is reduced to 0.41 Hz, indicating a substantial enhancement in the separation and localization of fault frequency components. For both misalignment and bolt-loosening faults, the method clearly reconstructs the second- and third-harmonic components, with frequency errors less than 1.2 Hz, and the harmonic amplitude ratios are highly consistent with those measured by the accelerometer sensor. Further pump-room field tests show that the rotational and harmonic frequency components of the pipeline circulation centrifugal pump are highly consistent with the accelerometer results, confirming good engineering applicability and providing an effective new solution for centrifugal-pump fault feature detection.