Cascaded H-bridge Multilevel Inverter (CHMI) is widely used in industrial applicationsthanks to its many advantages. However, the reliability of a CHMI is decreased with the increaseof its levels. Fault diagnosis techniques play a key role in ensuring the reliability of a CHMI.The performance of a fault diagnosis method depends on the characteristics of the extracted features.In practice, some extracted features may be very similar to ensure a good diagnosis performance atsome H-bridges of CHMI. The situation becomes even worse in the presence of noise. To fix theseproblems, in this paper, signal denoising and data preprocessing techniques are firstly developed.Then, a Principal Components Rearrangement method (PCR) is proposed to represent the differentfeatures sufficiently distinct from each other. Finally, a PCR-based fault diagnosis strategy is designed.The performance of the proposed strategy is compared with other fault diagnosis strategies, based ona 7-level CHMI hardware platform.