Numerical detection of shaft misalignments using a sensor‐integrating jaw coupling
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Shaft misalignments are one of the main causes of damage to couplings in machines. If they are not detected in time, they can lead to machine downtimes. When assembling a machine, however, it is not always possible to align the shafts perfectly. Elastic couplings are able to compensate for such misalignments up to a certain degree. To detect the present radial misalignment, the concept of a sensor‐integrating jaw coupling, developed to determine the transmitted torque, is used. In the teeth of the gear rim, boreholes are drilled and dielectric elastomer sensors (DES) are inserted. If the teeth deform during use of the coupling the DES will deform as well, leading to a change in capacitance, which can be detected. If the two shafts, which the coupling connects, are perfectly aligned to each other, each of the loaded teeth will deform uniformly. However, if there is a radial or angular misalignment, the deformation is different for each tooth, which can be determined with the help of the DES. To demonstrate this effect, a finite element model of the sensor‐integrating jaw coupling with misalignments is created, and numerical simulations are conducted. In this model, the hyper‐viscoelastic material behavior of (i) the gear rim of the jaw coupling and (ii) the DES is taken into account. From the mechanical simulation, the deformed state of the DES is obtained, which is used to compute the capacitance of the sensor. With the results of the numerical simulations, a symbolic regression is performed. The result is an analytical formula that makes the accurate detection of the present radial misalignment possible. The developed framework can later be easily programmed on a microcontroller which is integrated in the sensor‐integrating jaw coupling.
Details
Original language | English |
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Article number | e202400038 |
Journal | PAMM |
Volume | 24 |
Issue number | 2 |
Publication status | Published - Aug 2024 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0002-6437-4496/work/170582717 |
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ORCID | /0000-0002-5317-1431/work/170586580 |
Mendeley | 4c07ed08-27f6-3f4b-8a6a-0975592c6d54 |
unpaywall | 10.1002/pamm.202400038 |