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Title: Using probabilistic models to investigate torque in motors
Authors: Sim, Jie Hui
Keywords: Engineering::Mechanical engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Sim, J. H. (2022). Using probabilistic models to investigate torque in motors. Final Year Project (FYP), Nanyang Technological University, Singapore.
Project: I2001E0067
Abstract: In our current day and age, robots are used in several industries for tasks that are repetitive and are commonly used in contact tasks such as assembly. Humans are able to do these tasks and exert the appropriate amount of force required for the tasks easily. These tasks are however difficult to programme for robots. One important aspect of contact tasks is torque sensing. Torque sensors would inherently sense the intrinsic mechanical torques in addition to the torques that is due to the contact task itself. To isolate the contact task torques, the torques due to the intrinsic mechanics must be regressed and cancelled. This paper analyzes how torque sensed is affected by the intrinsic mechanical sources in the motor with a wheel bearing attached. In this paper, basis functions were utilized to model the torque sensed.
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Schaeffler Hub for Advanced REsearch (SHARE) Lab 
Fulltext Permission: embargo_restricted_20240518
Fulltext Availability: With Fulltext
Appears in Collections:MAE Student Reports (FYP/IA/PA/PI)

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