Feature Analysis and Fault Diagnosis of Internal Leakage in Dual-Cylinder Parallel Balance Oil Circuit
Source abstract
Abstract
The dual-cylinder parallel balance oil circuit is an important heavy-duty support mechanism. Driven by the automation and unmanned trend of equipment in various industries, the internal leakage analysis and corresponding fault diagnosis for this mechanism are increasingly being valued. To solve this problem, verified by numerous simulation analyses and theoretical deduction, the pressure signal in the rodless chamber during the pressure maintenance stage was used innovatively to construct the fault features of the internal leakage, which is common and low-cost to be obtained. Then, the wavelet packet decomposition was used to extract three energy features and two time-domain features. Finally, an internal leakage diagnosis was performed based on the five features extracted from the experimental data, and the accuracy and robustness of the proposed five features were verified, which indicated that the proposed fault features and diagnosis method are practical in engineering.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Fault Detection and Control Systems · Machine Fault Diagnosis Techniques · Power Transformer Diagnostics and Insulation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
References (42)
Show source-provided references
1. Performance analysis of hydraulic excavator powertrain hybridization10.1016/j.autcon.2008.10.001 ↗
2. Reliability-based weight reduction optimization of forearm of bucket-wheel stacker reclaimer considering multiple uncertainties10.1007/s00158-020-02627-y ↗
3. A bucket wheel dredge system for offshore tin mining beyond the 50 m water depth10.1016/S0029-8018(02)00003-3 ↗
4. Application of Generalized Frequency Response Functions and Improved Convolutional Neural Network to Fault Diagnosis of Heavy-duty Industrial Robot10.1016/j.rcim.2021.102228 ↗
5. Fault diagnosis of wind turbine based on Long Short-term memory networks10.1016/j.renene.2018.10.031 ↗
6. Multitask Convolutional Neural Network With Information Fusion for Bearing Fault Diagnosis and Localization10.1109/TIE.2019.2942548 ↗
7. Sparse transfer learning for identifying rotor and gear defects in the mechanical machinery10.1016/j.measurement.2021.109494 ↗
8. Failure monitoring and predictive maintenance of hydraulic cylinder—State-of-the-art review10.1109/TMECH.2021.3053173 ↗
9. Development of low-cost air-based hydraulic leakage detection system through real-time pressure decay data acquisition technology10.1007/s00170-016-8639-8 ↗
10. Internet of Things for Smart Ports: Technologies and Challenges10.1109/MIM.2018.8278808 ↗
11. Smart port: A bibliometric review and future research directions10.1016/j.tre.2023.103098 ↗
12. A Wavelet-Based Approach for External Leakage Detection and Isolation from Internal Leakage in Valve-Controlled Hydraulic Actuators10.1109/TIE.2010.2095396 ↗
13. Improved Leakage Detection Generalization Ability for Multiscenes Deployment in Industry10.1109/JSEN.2023.3253697 ↗
14. Experimental study of hydraulic cylinder leakage and fault feature extraction based on wavelet packet analysis10.1016/j.compfluid.2014.09.034 ↗
15. Watton, J. (2007). Modelling, Monitoring, and Diagnostic Techniques for Fluid Power Systems, Springer.
16. Condition monitoring and fault diagnosis of planetary gearboxes: A review10.1016/j.measurement.2013.11.012 ↗
17. Chen, P., Li, X., and Tang, Z. (2019, January 14–17). Simulation analysis of steering gear hydraulic system fault mechanism based on AMESim. Proceedings of the 2019 5th International Conference on Transportation Information and Safety (ICTIS), Liverpool, UK.10.1109/ICTIS.2019.8883800 ↗
18. Signal-Based Intelligent Hydraulic Fault Diagnosis Methods: Review and Prospects10.1186/s10033-019-0388-9 ↗
19. A Survey of Fault Diagnosis and Fault-Tolerant Techniques-Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches10.1109/TIE.2015.2417501 ↗
20. Taborri, J., Palermo, E., and Rossi, S. (2019). Automatic Detection of Faults in Race Walking: A Comparative Analysis of Machine-Learning Algorithms Fed with Inertial Sensor Data. Sensors, 19.10.3390/s19061461 ↗
21. A comparative analysis of machine learning algorithms for faults detection in wireless sensor networks10.1504/IJSNET.2017.084209 ↗
22. Ensemble diagnosis method based on transfer learning and incremental learning towards mechanical big data10.1016/j.measurement.2020.107517 ↗
23. Hydraulic actuator leakage fault detection using extended Kalman filter10.1080/14399776.2005.10781210 ↗
24. Leakage fault detection in hydraulic actuators subject to unknown external loading10.1080/14399776.2008.10781301 ↗
25. Leakage diagnosis method of hydraulic cylinder considering friction and measurement noise
26. The development of an adaptive threshold for model-based fault detection of a nonlinear electro-hydraulic system10.1016/j.conengprac.2004.11.014 ↗
27. Applications of machine learning to machine fault diagnosis: A review and roadmap10.1016/j.ymssp.2019.106587 ↗
28. A Wavelet-Based Approach to Internal Seal Damage Diagnosis in Hydraulic Actuators10.1109/TIE.2009.2032198 ↗
29. Application of fast Fourier and wavelet transforms towards actuator leakage diagnosis: A comparative study10.1080/14399776.2013.10781074 ↗
30. A time-frequency analysis based internal leakage detection method for hydraulic actuators10.1177/1687814016685058 ↗
31. Energy features fusion based hydraulic cylinder seal wear and internal leakage fault diagnosis method10.1016/j.measurement.2022.111042 ↗
32. (2024, November 13). SANY Group. Available online: https://sanyglobal-img.sany.com.cn/product/picture_album/20220428/SANY_RS_2022-120435.pdf.
33. Merritt, H.E. (1967). Hydraulic Control Systems, Wiley.
34. Hydraulic system fault diagnosis method based on a multi-feature fusion support vector machine
35. Blackburn, J.F. (1960). Fluid Power Control, Technology Press of M.I.T.
36. Daubechies, I. (1992). Ten Lectures on Wavelets, Society for Industrial and Applied Mathematics.10.1137/1.9781611970104 ↗
37. Fault Diagnosis of Hydraulic Seal Wear and Internal Leakage Using Wavelets and Wavelet Neural Network10.1109/TIM.2018.2863418 ↗
38. (2024, November 13). Huba Control Official Website. Available online: https://www.hubacontrol.com/en/products/pressure-transmitter/pressure-sensor-520.
39. Coordinated approach fusing time-shift multiscale dispersion entropy and vibrational Harris hawks optimization-based SVM for fault diagnosis of rolling bearing10.1016/j.measurement.2020.108580 ↗
40. Internal Leakage Detection of Hydraulic Cylinder Based on BP Neural Network
41. Intelligent fault diagnosis of planetary gearbox based on refined composite hierarchical fuzzy entropy and random forest10.1016/j.isatra.2020.10.028 ↗
42. Advance and prospects of AdaBoost algorithm10.3724/SP.J.1004.2013.00745 ↗