A SEA MODEL FOR THE NOISE ANALYSIS AND PREDICTION OF A VACUUM CLEANER

As an effective method for middle and high-frequency vibro-acoustics prediction, SEA (Statistical Energy Analysis) has been successfully applied to some areas such as aerospace, ship, and car. In this paper, a statistical energy analysis model is built for studying the noise prediction and control of vacuum cleaner. First the principles for subsystem partition are provided and subsystems and connections of SEA model are completed in AutoSEA software. Then for complex structures, their equivalent parameters are discussed. For different structures, a series of formulae of SEA parameters are provided, such as module density, damping loss factor and coupling loss factor, the input power is obtained by experimental measurement. By comparing the simulated SPL(sound pressure level) with the measured SPL, the correctness of the model is verified. Furthermore, error sources of the model are analyzed. This study can offer guidance and reference on how to carry out noise-vibration study and build up vacuum cleaner SEA model.