To ensure the product is qualified for use, strict inspection must be conducted before leaving the factory, and simulation testing is also a necessary method. The usage status of fire smoke exhaust fans is also understood.

In the basic analysis and processing of vibration signals for fire exhaust fans, the signal preprocessing theory, digital filtering theory, and spectrum analysis theory used were analyzed and studied at the same time. Then, based on the characteristics of vibration signals in the actual operation of fire exhaust fans, the actual operating conditions of fans, and on-site maintenance experience, methods for removing pseudo points, eliminating trend terms, reducing frequency aliasing and spectrum leakage, selecting and designing digital filters, basic time-domain and frequency-domain analysis methods, etc. were determined in the vibration signal processing process. Finally, the entire process of signal basic analysis and processing was simulated and tested in the laboratory, and relevant parameters and methods were determined. The theoretical analysis results were verified, To ensure that the on-site fire smoke exhaust fan can extract the required signals well under various working conditions.

In Chapter 3, on the research of using wavelet analysis for signal denoising, the basic theory and multi-resolution analysis methods of wavelet analysis were first analyzed. Then, based on the actual vibration signal of the fire exhaust fan, suitable wavelet functions were selected through data comparison. Finally, MATLAB software was used to simulate the wavelet soft and hard threshold denoising and its improvement methods.