Abstract
To reduce wind turbine failures by defective drive trains, deviations in the geometry of large gears (diameter ≳ 1 m) must be extensively determined with single-digit micrometer uncertainties. Fixed measuring volumes limit standard measuring methods like coordinate and gear measuring instruments for large gear measurements. Therefore, a model-based scanning multi-distance measurement approach for gear shape parameters is presented. The measurement approach has a scalable design and consists of a confocal-chromatic sensor, rotary table as a scanning unit and model-based signal processing. A preliminary study on a midsize spur gear demonstrates the general feasibility of the model-based scanning multi-distance measurement approach. As a result, the mean base circle radius as the fundamental gear shape parameter is determined with an uncertainty of <5 μm. The calibration and adjustment of the sensor arrangement were performed with a known calibration gear. Scalability is not experimentally validated in this article. However, simulations verify the scalability of the measurement approach in a first step. For gears with 1 m in diameter and varying tooth flank geometries, the estimated achievable uncertainty of the mean base circle radius is still <5 μm. Therefore, the model-based scanning multi-distance measurement approach is a promising alternative for gear inspection.
Highlights
The geometry of a known calibration gear is measured, compared with the reference geometry using the example of the shape parameter mean base circle radius and a correction value is calculated based on the offset
For the calibration of the measuring system, a mean correction value c = (1.4 ± 0.9) μm (k = 1) for the mean base circle radius is calculated from 22 repeated measurements with the same boundary conditions regarding sensor position, alignment and gear position on the rotary table
The model-based single-sensor multi-distance measurement approach is validated on a second gear with the same nominal geometry
Summary
Defects of the drive train are a significant cause of wind turbine failures [1]. The base circle radius of a spur gear correlates with the profile slope deviation and is the shaping parameter for an involute geometry. To reduce drive train defects, reliable quality assessments of the gear shape parameters such as the base circle radius, profile, lead, pitch and runout deviations of large gears with diameters & 1 m are required [2,3,4]. To evaluate the shape parameters of large gears, the geometry data of all teeth must be taken into account This means that extensive measurements of all teeth over the whole circumference are required. For this reason, a scalable gear measurement system that acquires extensive data from all teeth is desired to quantify shape parameters such as the base circle radius of large gears with single-digit micrometer uncertainty
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