Nonlinearity of Magnetostrictive Torque Sensor under Varying External Magnetic Field Strength

Jack A Wilkie,Knut Moeller

doi:10.1515/cdbme-2021-2194

Jack A Wilkie, Knut Moeller

Open Access

https://doi.org/10.1515/cdbme-2021-2194

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Abstract

Abstract Correctly torquing bone screws is an important factor in achieving positive patient outcomes during orthopaedic surgery. A torque-limiting smart screwdriver concept has been proposed, and ongoing work is being undertaken to model the screwing process and allow the concept to work. These models require experimental validation, so a test rig was developed. The magnetostrictive torque sensor in this test rig was affected by magnetic parts of the test rig, which offset the zero-torque point; this raised concerns over the effects on linearity, which were tested here. The torque sensor was tested against a non-magnetostrictive reference under varying external magnetic conditions. While the magnetic field offset the torque, there was no notable change in linearity under the conditions tested, and the linearity was always within the datasheet specifications. Hence, we conclude that in the context of this test rig, there were no negative effects on linearity, although under higher loading or stronger magnetic conditions, this may not hold.

Highlights

Bone screws are widely used in orthopaedic surgery to secure implants, and to support bones during natural healing
This paper investigates the effects of external magnetic fields on the linearity of the torque sensor used in our test rig
It is noteworthy that the best nonlinearity was found at the highest level of magnetic influence, this could be an artefact of the data processing employed

Summary

Introduction

Bone screws are widely used in orthopaedic surgery to secure implants, and to support bones during natural healing. In both cases, it is critical that the connections are as resilient as possible. Previous work has focused on developing and testing models of screw insertion for detecting the bone material properties [4]–[6], and for predicting the optimal torque from these properties [7]. To test these models, a test rig was developed [8]. The test rig had to collect torque and displacement data with a high accuracy and sample rate

Results

Discussion

Conclusion