Expert diagnostic system for moving-coil loudspeakers using nonlinear modeling.
This work aims at the development of an expert diagnostic system for moving-coil loudspeakers. Special emphasis is placed on the defects resulting from loudspeaker nonlinearities. As a loudspeaker operates in the large signal domain, nonlinear distortions may arise and impair sound quality. Analysis of nonlinear responses can shed light on potential design faults of a loudspeaker. By exploiting this fact, this expert diagnostic system enables classification of design faults using a defect database alongside an intelligent fault inference module. Six types of defects are investigated in this paper. A large signal model based on electromechanical analogous circuits is employed for generating the defect database, through which a neural-fuzzy network is utilized for inferring the defect types. Numerical simulations and experimental investigations were undertaken for validating the loudspeaker diagnostic system.
Bai
Mingsian R
MR
Department of Mechanical Engineering, National Chiao-Tung University, Hsin-Chu, Taiwan. msbai@mail.nctu.edu.tw
Huang
Chau-Min
CM
D000162:Acoustics / Q000295:instrumentation*; D000669:Amplifiers, Electronic; D004867:Equipment Design; D017143:Fuzzy Logic; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D014732:Vibration