STEMM Institute Press
Science, Technology, Engineering, Management and Medicine
The Rear Oil Seal Manual Press is based on the Crankshaft of a Large Bore Engine
DOI: https://doi.org/10.62517/jes.202502429
Author(s)
Zhenyuan Zhang, Xianglian Li
Affiliation(s)
Weichai Power Co., Ltd., Weifang, Shandong, China
Abstract
To address challenges in the assembly of rear cranshaft oil seals for large-cylinder engines-Including low positioning accuracy, uneven pressing force, and seal damage-The manual pressing device is designed. This mechanism features a mechanical core with a positioning system for Precise alignment between the crankshaft and oil seal, a pressure transmission system ensuring force equilibrium during assembly, and a guiding structure to prevent track deviation. With its user-friendly operation and cost-effectiveness, this solution is ideal for small-to-medium batch production or on-site maintenance, offering a new approach for efficient and reliable assembly of rear crankshaft oil seals in large-cylinder engines.
Keywords
Rear Cranshaft Oil Seals; Guiding Structure; Mechanism; Small-To-Medium Batch Production
References
[1] vehicle power, 2013,(02):56-60. [2] Sun Caihua, Zhang Lixia. Improvement of Diesel Engine Density Detection standards and Solutions [J]. Railway Locomotive and Motor vehicle, 2018,(02):47-48+10 [3] Ruian Jian, Wang Feng, Duan Shuanlu, etc. Engine Gas-tight Leak Test Engine quality Control Research [C] // China Society of Automotive Engineering. Thesis Series (Volume1), China Society of Automotive Engineering Annual Conference 2015. FAW Liberation Automotive Co., Ltd. Wuxi Diesel Engine Factory, 2015:4 [4] Jing G, Lyu Z, Liu Y, et al. Reliability study for diesel engine cylinder head through fatigue failure analysis and Structural optimization[J]. Engineering failure Analysis, 2022, 142: 106768. [5] Abdelrahman M S, Khalifa W, Abdu M T. Faulty machining and micro-segregation assisted fatigue failure of cylinder Head stud of a diesel generator[J]. Engineering failure Analysis, 2024, 162: 108409 [6] Jing G, Li S, Xiao S, et al. Research on fatigue reliability assessment of engine cylinder head based on neural Network[J]. International Journal of fatigue, 2023, 175: 107800.
Copyright @ 2020-2035 STEMM Institute Press All Rights Reserved