Research on the Bearing Load Measurement Method Based on the Fusion of Redundant Strain Data and Jacking Data
Source abstract
Abstract
To improve the accuracy of bearing load measurement in propulsion shafting, a bearing load measurement method based on redundant strain and jacking data fusion is proposed. Firstly, to address the issue of low measurement accuracy in strain gauge methods (SGM), a redundant strain gauge method (RSGM) is introduced to enhance the precision of strain-based measurements. Secondly, synchronize the measurement of strain data during the jacking phase and fuse the measurement data from the jacking phase based on the Bayesian estimation method to enhance the measurement accuracy of the jack-up method (JM). Lastly, the pre-decision results of the two types of measurement data are integrated at the decision level to obtain the final measured load. Simulation experiments have verified the correctness and applicability of the proposed measurement method. The research results indicate that, compared to the SGM, the RSGM offers higher measurement precision; the fusion measurement method can achieve more accurate results than the JM and RSGM under different bearing support conditions and jack-up scenarios.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Hydraulic and Pneumatic Systems · Advanced Measurement and Detection Methods · Fault Detection and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China
Funding
National Natural Science Foundation of China (NSFC)
References (30)
Show source-provided references
1. Exploration of Ship Shaft Alignment Technological Process
2. Influence of Shaft Alignment Deviation on Vibration of Single-support Shafting
3. (2024, December 27). Snow Dragon’s Bearing Failure Investigation: The Case Study. The Shaft Calculation Software by IMT. Available online: https://shaftsoftware.com/snow-dragons-bearing-failure-investigation-the-case-study.
4. Deng, Y., Li, Y., Zhu, H., and Fan, S. (2023). Displacement Values Calculation Method for Ship Multi-Support Shafting Based on Transfer Learning. J. Mar. Sci. Eng., 12.10.2139/ssrn.4588792 ↗
5. Theoretical and experimental research on turbo-generator shaft alignment using strain gauge method10.1177/1077546315590908 ↗
6. Identification of bearing load by three section strain gauge method: Theoretical and experimental research10.1016/j.measurement.2013.07.017 ↗
7. Strain gauge placement optimization methodology to measure multiaxial loads of complex structure10.1177/03093247211063088 ↗
8. Shaft Alignment Methods with Strain Gages and Load Cells10.5957/mt1.1980.17.1.8 ↗
9. Verification Technique of Marine Shafting Alignment Based on the Curve Fitting Algorithm
10. Song, Z. (2019). Error Analysis of Load Testing for Large Ship Propulsion Shaft System. [Master’s Thesis, Dalian University of Technology].
11. Load identification and calibration method of ship propulsion shafting bearing
12. Multisensor data fusion: A review of the state-of-the-art10.1016/j.inffus.2011.08.001 ↗
13. Kenyeres, M., and Kenyeres, J. (2020). Average Consensus over Mobile Wireless Sensor Networks: Weight Matrix Guaranteeing Convergence Without Reconfiguration of Edge Weights. Sensors, 20.10.3390/s20133677 ↗
14. A Model-Based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics10.1109/LRA.2020.3008120 ↗
15. A data fusion-based approach for structural damage detection with distributed long-gauge strain measurements10.1088/1361-6501/ad4f03 ↗
16. Theory and Application of Multi-sensor Information Fusion
17. Estimation of ship berthing parameters based on Multi-LiDAR and MMW radar data fusion10.1016/j.oceaneng.2022.113155 ↗
18. Wang, J., Song, Z., Li, R., Liu, Y., and Liu, X. (2018, January 23). Study on Measurement Error of Load Resistance Strain Gauge Method for Ship Propulsion Shafting. Proceedings of the Ninth General Meeting of the Ship Mechanics Academic Committee of the China Society of Naval Engineers, Wuxi, China.
19. Inverse calculation method of shaft system installation status evaluation based on bending moment influence coefficient
20. Survey on Information Fusion of Probability Density Functions
21. Fusion of Probability Density Functions10.1109/JPROC.2022.3154399 ↗
22. Multi-Sensor Data Fusion Technology Based on NB-IoT Environment Monitoring
23. Zhou, W., Zhao, Y., Yuan, H., Liu, J., and Wang, X. (2022). Research on the Contact Pressure Calculation Method for the Misaligned Elastomeric Journal Bearing. J. Mar. Sci. Eng., 10.10.3390/jmse10020141 ↗
24. Cuturi, M., and Doucet, A. (2014, January 21–26). Fast Computation of Wasserstein Baryeenters. Proceedings of the 31st International Conference on Machine Leaming, Beijing, China.
25. Multi-source monitoring information fusion method for dam health diagnosis based on Wasserstein distance10.1016/j.ins.2023.03.053 ↗
26. Statistical Aspects of Wasserstein Distances10.1146/annurev-statistics-030718-104938 ↗
27. The Construction Method of Possibility Distribution Based on One-Variable Linear Regression
28. Multi-sensor data fusion technique and its application
29. Kumar, M., Garg, D., and Zachery, R. (2006, January 14–16). A generalized approach for inconsistency detection in data fusion from multiple sensors. Proceedings of the 2006 American Control Conference, Minneapolis, MN, USA.10.1109/ACC.2006.1656526 ↗
30. Yeong, D.J., Velasco-Hernandez, G., Barry, J., and Walsh, J. (2021). Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review. Sensors, 21.10.20944/preprints202102.0459.v1 ↗