15 citations as recorded by crossref.

1. Microstructural analysis on the compatibility of various dilution oils on magnetorheological grease performance Z. Pang et al. 10.1088/2631-8695/ad78aa
2. Photoluminescence Induced in Mineral Oil by Ionizing Radiation V. Bliznyuk et al. 10.3390/lubricants11070287
3. A two-step Fabry-Perot filter array in mid-infrared wavelength range for integration with photochemical microreactors Z. Wang et al. 10.1016/j.sna.2020.112047
4. Vibration Viscosity Sensor for Engine Oil Monitoring Using Metal Matrix Piezoelectric Composite T. Yanaseko et al. 10.3390/ma12203415
5. A digital twin solution for fault detection in time-critical IIoT applications A. Ranpariya & S. Sharma 10.1080/17477778.2025.2453725
6. Evaluating petrol engine oil deterioration through oxidation and nitration parameters by low-cost IR sensor H. Shinde & A. Bewoor 10.1007/s13203-020-00248-6
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8. Recording gear-type pump acoustic signals for assessing the hydraulic oil impurity level in a hydraulic excavator transmission S. Ivanov et al. 10.1051/e3sconf/202132600014
9. Comparison of the mineral oil lifetime estimates obtained by differential scanning calorimetry, infrared spectroscopy, and dielectric dissipation factor measurements R. Polansky et al. 10.1016/j.tca.2016.12.002
10. Study of frequency dependence of shear horizontal surface acoustic wave sensor for engine oil measurements J. Kondoh et al. 10.1016/j.sna.2020.112503
11. Quantifying the Effect of Catalysts on the Lifetime of Transformer Oil R. Polanský et al. 10.3390/app10041309
12. FEATURES OF REFRACTOMETRIC CHARACTERISTICS OF SURFACE PLASMON RESONANCE OF MOTOR OILS FOR USE G. Dorozinsky 10.15407/jopt.2018.53.261
13. Failure Monitoring and Predictive Maintenance of Hydraulic Cylinder—State-of-the-Art Review V. Shanbhag et al. 10.1109/TMECH.2021.3053173
14. A laboratory investigation into the effect of waste non-tire rubber particles on the performance properties of terminal blend rubberized asphalt binders L. Sun et al. 10.1016/j.conbuildmat.2021.125409
15. Health condition monitoring of a complex hydraulic system using Deep Neural Network and DeepSHAP explainable XAI A. Keleko et al. 10.1016/j.advengsoft.2022.103339