Distinction of Roller Bearing Defect from Gear Defect via Envelope Process and Autocorrelation Enhancement

Bearing and gear condition monitoring are important to improve a mechanical system reliability and performance. In the early stage of bearing failures, the Bearing Characteristic Frequencies (BCFs) contain very little energy and are often overwhelmed by noise and higher-level macro-structural vibrations, an effective signal processing method would be necessary to eliminate such corrupting noise and interference. Referring to the non-stationary characteristics of roller bearing fault vibration signals, a roller bearing condition monitoring method based on Envelope Process to raw time-domain vibration signal and Autocorrelation enhancement to the residual signal is put forward in this paper. The concept of Envelope and Autocorrelation techniques and its implementation for defect identification are discussed. Also, distinction of bearing fault signal as cyclostationary from periodic signal for gear fault. An automotive gearbox is used on the test stand, which is equipped with three dynamometers; the input dynamometer serves as internal combustion engine, the output dynamometers introduce the load on the flanges of output joint shafts. This assertion is demonstrated by introducing an experimental study on artificial defects in one roller element of bearing on the input shaft and pinion gear tooth on the secondary shaft. The proposed method remains the periodicity of the characteristic features (repetitive patterns) of faulty bearing for lower frequency defects, which is very simple for operator to identify the bearing fault type. The results obtained from practical experiments prove that the proposed approach is very effective for distinction of roller bearing defect from gear fault.