Next Level Gear Noise Detection Software
Gear noise contributors like transmission errors caused by geometrical deviations have long been known to be noise contributors in gear mesh. Gear specialists understand the influences of undesired gear and tooth deviations on noise and have found ways to improve them over the years. Tooth flank deviations, which lead to so-called “ghost noise”, are still hard to detect, and therefore, in many cases, have to be accepted by gearbox manufacturers. Now, with the surge of electric vehicles, ghost noise has caught new attention, and ways are sought to overcome it. Since tooth flank waviness is the main contributor to undesired high-frequency noise behavior in gear mesh, Gleason offers two pioneering software solutions for waviness detection.
Advanced Waviness Analysis (GAMA)
Advanced Waviness Analysis provides a fast way to analyze tooth flanks for waviness. The software uses single-trace inspection data of all tooth flanks of a gear, on both profile and lead. By combining tooth profile traces of all teeth and analyzing the gear for an entire rotation, it gives users a good understanding of the contribution of measured data to gear noise. The software uses enhanced mathematical techniques to analyze all wave lengths and amplitudes and present them in simplified graphics.
The detected amplitudes are shown in an easy-to-read bar chart, giving numerical value of the amplitudes. Additional functions, like removal of pitch and runout influences in the Waviness Analysis, make it even easier to detect the source of gear noise in the final application.
Kinematic Transmission Error Prediction Software (KTEPS)
Using topographical data of all teeth to detect tooth flank waviness, KTEPS offers a revolutionary method of showing tooth flank surface deviations in relation to their frequency. In fact, KTEPS is the only software tool, which is showing surface deviations and their relation to frequency. By calculating the transmission error of the analytically measured gear topography, KTEPS offers the functionality to extract tooth waviness from the tooth flank, revealing the basis of bad noise behavior in a 3D, easy-to-understand false color chart.
Tracing the source of tooth flank waviness to a specific machine, which had produced the analyzed gear, understanding the cause, and being able to adjust/correct the respective process to actually reduce gear noise, makes gear noise analysis truly valuable.
For more information: www.gleason.com
