| dc.description.abstract | With the progress of Industry 4.0, the demand for cycloidal gears is increasing rapidly, and precision machining technologies and methods are being upgraded and becoming more popular as a result. At the same time, with the improvement of the machining precision of the cycloidal gear disc, the importance of the precision inspection method becomes more and more important. The purpose of this study is to establish a set of evaluation methods for the machining precision of cycloidal gear discs, which can be used to identify the systematic errors in the machining process, and then to improve the machining precision.
The method is based on the pin gauging method, which makes use of the simulation of the characteristics of the pin circle in contact with the tooth profile at two points, and analyses the geometrical characteristics of the pin circle at each tooth space under the same pin diameter to assess the corresponding errors. Specifically, this method can accurately assess the centre error, pitch error and symmetric axis error of the profile grinding of the cycloidal disc, and further quantify the feed error by combining it with a comparative profile analysis of the ideal curve data of the design.
In order to implement this method, the B-Spline curve is used to fit the measured point data, and Newton′s method is used to calculate the pin centres at different pin diameters, and the least square circle method is used to find the mean centre in order to reduce the random errors. Combining the least square method and the Powell method, the pitch error and the symmetric axis error of the profile grinding were further calculated, and finally the feeding error was evaluated based on the designed ideal curve data.
In verifying the performance of the algorithm, this study tests several types of errors, including contour error, centre error, pitch error, feed error and symmetric axis error of the profile mill, and generates ideal and deviated contours for analysis. The results show that the contour error has a significant effect on the measurement accuracy, for example, when the contour error is ±5μm, the measurement error is about 10μm, which confirms that the performance of the algorithm is closely related to the accuracy of the contour data. In addition, the analysis of the cycloidal disc data produced by machines with different machining levels confirms that the results are as expected.
The results show that the developed algorithm can effectively evaluate the machining error of the cycloidal disc, accurately diagnose the machining precision problems, and provide a reliable basis for the subsequent machining control and improvement. This method is of great significance for improving the machining accuracy and ensuring the stable operation of the machine.
In verifying the performance of the algorithm, this study tests several types of errors, including contour error, center error, pitch error, feed error, and symmetric axis error of the profile mill. Ideal and deviated contours are generated for analysis. The results indicate that contour error significantly impacts measurement accuracy, with an error of ±5 μm resulting in a measurement error of approximately 10 μm. This validates the algorithm′s performance correlation with contour data accuracy.Additionally, an analysis of cycloidal disc data generated by machines with varying machining levels substantiates the expected outcomes.
The findings demonstrate that the developed algorithm can effectively evaluate the machining error of the cycloidal disc, accurately diagnose machining precision problems, and provide a reliable basis for subsequent machining control and improvement. This method is of great significance for improving machining accuracy and ensuring the stable operation of the machine. | en_US |