Servomotors are used in a variety of industrial applications where precise movements are of critical importance. Degradation mechanisms in servomotors have been mostly studied and modeled for systems with long duration steady state modes. However, some specialized applications require health estimation from very short duration intermittent operations, which require different analysis techniques. With such applications in mind, a simulated dataset for servomotor health modeling and prediction is described and made available for public use. The application scenario is motivated by a fine motion control rod drive (FMCRD) mechanism used for intermittent, and typically infrequent, fine motion (insertion or withdrawal) adjustment of control rods in some nuclear reactor designs. Though the drives do not run continuously, servomotor and associated linear motion mechanisms do show wear and damage during its operational lifetime. Specifically, in FMCRD such degradations may be caused by internal as well as external damage to the system. While the causes of such damage can be diverse, in simulation we model the impact of cumulative damage as an external opposing load which resists the movement of the motor shaft. Such scenarios represent effects of rod-binding and debris in the fuel channels. The dataset includes measurements such as motor currents and rotor speed which would be part of the instrumentation in a typical deployments of rotating machinery. These observable measurements can be used to predict the health state of the servomotor. Also presented are baseline results on health state estimation, formulated as classification and regression problems, which can be used by the larger PHM community for performance comparisons. This dataset is hosted at the PHM Society Data repository [https://data.phmsociety.org/servomotor_dataset/].
How to Cite
servomotor drive, intermittent operation, rotating machinery, transient operation, health prediction, classification, regression, benchmark, dataset
Chapter 4: Reactor, AWBR: Design Control Document / Tier 2 (Vol. 25A5675AF Revision 6). (2016, Febru- ary). GE Hitachi Nuclear Energy. Retrieved June 8, 2023, from https://www.nrc.gov/docs/ ML1608/ML16081A093.pdf
GE Hitachi Nuclear Energy. (2020). Bwrx-300 fact sheet. Retrieved June 13, 2023, from https:// nuclear.gepower.com/content/dam/ gepower-nuclear/global/en_US/ documents/product-fact-sheets/ BWRX-300_Fact_Sheet-2020.pdf
GE Hitachi Nuclear Energy (2023). Bwrx-300. Retrieved June 13, 2023, from https://nuclear.gepower.com/ build-a-plant/products/nuclear-power -plants-overview/bwrx-300
Fullilove, N., Santos, D. D., Saxena, A., & Coble, J. (2022, Oct). Leveraging within-bank comparison for anomaly detection, diagnostics, and prognostics in advanced nu- clear power plants. Annual Conference of the PHM So- ciety, 14(1). doi: 10.36001/phmconf.2022.v14i1.3215
Krichen, M., Elbouchikhi, E., Benhadj, N., Chaieb, M., Benbouzid, M., & Neji, R. (2020, June). Motor Current Signature Analysis-Based Permanent Magnet Synchronous Motor Demagnetization Characterization and Detection. Machines, 8(3), 35. doi: 10.3390/machines8030035
Liang, S. Y., Li, Y., Billington, S. A., Zhang, C., Shiroishi, J., Kurfess, T. R., & Danyluk, S. (2014). Adap- tive prognostics for rotary machineries. Procedia En- gineering, 86, 852-857. (Structural Integrity) doi: 10.1016/j.proeng.2014.11.106
Saxena, A., Goebel, K., Simon, D., & Eklund, N. (2008). Damage propagation modeling for aircraft engine run- to-failure simulation. In 2008 international conference on prognostics and health management (p. 1-9). doi: 10.1109/PHM.2008.4711414
Subramanian, A., Saxena, A., & Coble, J. (2023). Servomo- tor Driven Ballscrew Mechanism Data Set. Retrieved June 13, 2023, from https://data.phmsociety .org/servomotor_dataset/
The MathWorks, Inc. (2023a, June). AC6 - PM Syn- chronous 3HP Motor Drive. Retrieved June 9, 2023, from https://www.mathworks.com/help/ sps/ug/ac6-pm-synchronous-3hp-motor -drive.html
The MathWorks, Inc. (2023b, June). PM Synchronous Motor Drive: Implement Permanent Magnet Synchronous Motor (PMSM) vector control drive. Retrieved June 9, 2023, from https:// www.mathworks.com/help/sps/powersys/ ref/pmsynchronousmotordrive.html
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.