Analisis Sinyal Getaran Untuk Menentukan Jenis Dan Tingkat Kerusakan Bantalan Bola (Ball Bearing)

An Engineer can determine accurately the type and the level of engine faults using vibration-signal, like a doctor investigates his/her patient by analyzing the hart beat. Vibration is a response of a mechanical system caused by both excitation forces and the changes of operating conditions that vary within certain limits. The excitation forces introduced by several sources such as contact between moving elements, unbalanced mass, misalignments, ball bearing defects, which is the topic of this research may be arised. There are two kinds of bearing defects, local and distributed defects. The most cases of local defects are the defect of inner and outer raceway also rolling elements. Moreover the most cases of distributed defects are the unroundness of inner and outer raceway, missalignment of inner and outer raceway, ununiformed ball dimension. Furthermore, for many machine elements such as ball bearing, the vibration has a typical level, and its frequency spectrum has a characteristic shape when the machine is in good condition or defect. The most popular and the latest sophisticated method to detect bearing defect is computer-based vibration monitoring. This method analyzes the measured vibration-signal in both time and frequency domain. An experiment to detect the type and the level of ball bearing defects has been done in bench grinding machine by changing such a certain defect of bearing elements. A comparison of the vibration-signal of the good condition and the defect one can be determined the type and the level of such a bearing defect. In general the result of this experiment showed that the vibration-signal of the good bearing is a harmonic, but the defect one has a random signal. For determining the type of defect of bearing elements, the frequency must be synchronized with the calculation of bearing parameters such as inner and outer raceway diameters, number of balls and number of rotations. The application of this research is the vibration monitoring for predictive maintenance