Abstract: In this paper, the corrosion process of the 304 stainless steel in the acidic NaCl solution is studied by using the electrochemical noise(EN) and acoustic emission(AE) techniques. The AE signals in the corrosion process are clustered based on the K-Means clustering algorithm, and the AE signal characteristics are analyzed through the wavelet packet. It is shown that the stress corrosion cracking(SCC) occurs easily in the experimental system, and the corrosion forms are developed gradually from the localized corrosion to the general corrosion. The AE signal characteristics of the pitting corrosion, the crack and the bubble break-up are quite different during the corrosion process. The AE test results are found to be consistent with the EN test results.