In order to meet the requirement of intelligent monitoring for precise cylindrical plunge grinding, an online optimization algorithm with respect to the grinding time based on acoustic emission signals for precise cylindrical plunge grinding was designed. By establishing the theoretical model of acoustic emission (AE) signal root mean square (RMS) curves, the relationship between the acoustic emission signal and the time constant of grinding system was obtained, and the AE signal RMS curves at each stage before optimization were provided. By preparing a cylindrical plunge grinding time online optimization algorithm, through the test and analysis on the effect of processing time of grinding system on the machining accuracy and surface roughness, and validating the optimization algorithm, the AE signal RMS curves at each stage after optimization were also provided. The test results show that the optimization method can shorten the processing time and improve the processing efficiency, while the total removed amount of material can be ensured unchanged. The improvement of the processing technology provides an important basis for precision cylindrical plunge grinding.