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- Title
Prediction of Tooth Profile Deviation for WEDM Rigid Gears Based on ISSA-LSSVM.
- Authors
Wang, Yazhou; Wang, Zhen; Wang, Gang; Xu, Huike
- Abstract
This study aimed to develop and validate an improved sparrow search algorithm (ISSA)-optimized Least Squares Support Vector Machine (LSSVM) model for accurately predicting the tooth profile deviation of rigid gears produced by wire electrical discharge machining (WEDM). The ISSA was obtained by optimizing the sparrow search algorithm (SSA) using Tent chaotic mapping, adaptive adjustment strategy, dynamic inertia weights, and grey wolf hierarchy strategy. The effectiveness of the ISSA was verified using four different classes of benchmark test functions. Four main process parameters (peak current, pulse width, pulse interval, and tracking) were taken as inputs and the tooth profile deviations of rigid gears were considered as outputs to develop an ISSA-LSSVM-based profile deviation prediction model. The prediction performance of the ISSA-LSSVM model was evaluated by comparing it with the LSSVM model optimized by three standard algorithms. The prediction results of the ISSA-LSSVM model were R2 = 0.9828, RMSE = 0.0029, and MAPE = 0.0156. The results showed that the established model exhibits high prediction accuracy and can provide reliable theoretical guidance for predicting the tooth profile deviation of rigid gears.
- Subjects
TEETH; SUPPORT vector machines; SEARCH algorithms; GEARING machinery; LEAST squares
- Publication
Applied Sciences (2076-3417), 2024, Vol 14, Issue 11, p4596
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app14114596