Innovations in Methodology for Analyzing Automotive Engine Vibration Signals Based on Wavelet Transform Techniques to Determine Maintenance Needs

Abstract

This paper takes automotive engine vibration signals as its research object, proposes a wavelet transform analysis of automotive engine vibration signals, and further calculates the maintenance requirements of automotive engine vibration signals. It also analyzes the various operational status information contained in complex vibration signals. For engine vibration signals, traditional signal analysis techniques such as the Fourier transform have limitations in their analysis capabilities, particularly when dealing with non-stationary and nonlinear vibration signals. However, the wavelet analysis method, with its time-frequency locality characteristics, can completely avoid such contradictions. Under such circumstances, the analysis of engine vibration signals has a solid foundation and possesses fundamental functional significance. Based on this understanding, this paper conducts a specific and scientific study, establishing a scientifically reasonable signal analysis model. Using specific techniques such as wavelet packet decomposition and reconstruction, the paper performs a more in-depth and detailed analysis of the vibration signals of the Cummins KTA50 engine. Finally, the signal analysis process is validated through practical examples. The results demonstrate that wavelet transform technology can be used for the detection and analysis of engine fault information. Under certain conditions, it can provide more detailed and precise localization of fault information, enabling more accurate judgment of engine fault conditions and enhancing real-time reliability. From the technical perspective of high-order wavelets and adaptive analysis methods, wavelet analysis provides theoretical and methodological support for preventive maintenance of automotive engines and rapid, accurate fault diagnosis, holding significant application significance and value in both theoretical and engineering contexts.