Data-driven bending fatigue life forecasting and optimization via grinding Top-Rem tool parameters for spiral bevel gears. (August 2022)
- Record Type:
- Journal Article
- Title:
- Data-driven bending fatigue life forecasting and optimization via grinding Top-Rem tool parameters for spiral bevel gears. (August 2022)
- Main Title:
- Data-driven bending fatigue life forecasting and optimization via grinding Top-Rem tool parameters for spiral bevel gears
- Authors:
- Ding, Han
Zhang, Yuntai
Kong, Xiannian
Shi, Yingjie
Hu, Zehua
Zhou, Zhenyu
Lu, Rui - Abstract:
- Abstract: To establish a bridge between grinding tool parameters and loaded tooth fatigue life, an innovative data-driven root flank bending fatigue life forecasting and optimization via Top-Rem tool parameters was proposed for grinding spiral bevel gears. The recent machine settings modification is extended into grinding Top-Rem tool parameters modification in case that geometric accuracy and root bending fatigue life are integrated into a collaborative optimization. The proposed Top-Rem modification includes three key steps: (I) arc-shaped blade, (II) top part, and (III) top fillet part. Then, while root bending stress is determined by using finite element method (FEM)-based simulated loaded tooth contact analysis (SLTCA), data-driven fatigue life forecasting is developed by correlating with the multiaxial fatigue damage model based assessment. Moreover, data-driven bending fatigue life optimization model is established by using Top-Rem tool parameters modification, where the important constraints in target flank determination includes: (i) root overcutting, (ii) geometric accuracy, and, (iii) fatigue life. For high accuracy and efficiency, two different strategies are proposed: (i) the different parameters modification types; and, (ii) sensitivity analysis of grinding Top-Rem tool parameters. Finally, proposed method can verify that bending fatigue life can be significantly improved by modifying the key Top-Rem tool parameters in early stage of the whole life productAbstract: To establish a bridge between grinding tool parameters and loaded tooth fatigue life, an innovative data-driven root flank bending fatigue life forecasting and optimization via Top-Rem tool parameters was proposed for grinding spiral bevel gears. The recent machine settings modification is extended into grinding Top-Rem tool parameters modification in case that geometric accuracy and root bending fatigue life are integrated into a collaborative optimization. The proposed Top-Rem modification includes three key steps: (I) arc-shaped blade, (II) top part, and (III) top fillet part. Then, while root bending stress is determined by using finite element method (FEM)-based simulated loaded tooth contact analysis (SLTCA), data-driven fatigue life forecasting is developed by correlating with the multiaxial fatigue damage model based assessment. Moreover, data-driven bending fatigue life optimization model is established by using Top-Rem tool parameters modification, where the important constraints in target flank determination includes: (i) root overcutting, (ii) geometric accuracy, and, (iii) fatigue life. For high accuracy and efficiency, two different strategies are proposed: (i) the different parameters modification types; and, (ii) sensitivity analysis of grinding Top-Rem tool parameters. Finally, proposed method can verify that bending fatigue life can be significantly improved by modifying the key Top-Rem tool parameters in early stage of the whole life product development for spiral bevel gears. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 53(2022)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 53(2022)
- Issue Display:
- Volume 53, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 53
- Issue:
- 2022
- Issue Sort Value:
- 2022-0053-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08
- Subjects:
- Spiral bevel gears -- Bending fatigue life forecasting and optimization -- Grinding Top-Rem tool parameters -- Root bending stress -- Simulated loaded tooth contact analysis (SLTCA)
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2022.101724 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23316.xml