Bearing Vibration Signal Restoration Method Based on Fuzzy Adaptive Sliding Mode Algorithm

With the development of intelligent algorithms on the Internet and the widespread application of signal recovery technology in the current mechanical industry, signal recovery systems based on fuzzy adaptive sliding mode algorithms are becoming increasingly important for improving mechanical bearing fault diagnosis. In the construction of the entire mechanical bearing signal recovery model, how to improve the accuracy of signal recovery and reduce the time for model signal feature extraction is currently a key issue that needs to be urgently solved. This article conducts simulation experiments and analysis on the parameter dataset of mechanical bearing components that are prone to faults. Based on the fuzzy adaptive sliding mode algorithm process, combined with adaptive law parameter calculation and fuzzy system model design, the following conclusion is drawn: the application of improved signal recovery models on the sampled four bearing component parameters has an average improvement of 6.65% in recovery accuracy and 9.25% in recovery efficiency. This method uses fuzzy adaptive sliding mode algorithm to adaptively extract fault features, accurately identify fault types and degrees, innovatively suppress noise and interference, and improve the accuracy of vibration signal recovery.