Increasing the Reliability of Real-Time Diagnostics of a Wear Particle Counter
Source abstract
Abstract
To diagnose wear in critical friction units, inductive wear particle counters are now widely used, which are built into the main lubrication line of the mechanism. One way to increase their sensitivity is to develop effective digital signal processing methods. The paper presents a technique that can increase the processing speed of the particle counter signal and reduce the amount of required microcontroller memory, which is important for real-time wear diagnostics.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Engineering Diagnostics and Reliability · Scientific Measurement and Uncertainty Evaluation · Surface Treatment and Coatings
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (8)
Show source-provided references
1. Myshkin, N.K. and Markova, L.V., On-Line Condition Monitoring in Industrial Lubrication and Tribology, Berlin: Springer-Verlag, 2018.10.1007/978-3-319-61134-1 ↗
2. Markova, L.V., Diagnostics of the wear of tribological assemblies using an inductive wear debris counter, J. Frict. Wear, 2018, vol. 39, no. 4, pp. 265–273.10.3103/S1068366618040104 ↗
3. Li, C. and Liang, M., Extraction of oil debris signature using integral enhanced empirical mode decomposition and correlated reconstruction, Meas. Sci. Technol., 2011, vol. 22, no. 8, p. 085701. https://doi.org/10.1088/0957-0233/22/8/08570110.1088/0957-0233/22/8/085701 ↗
4. Fan, X., Liang, M., and Yeap, T., A joint time-invariant wavelet transform and kurtosis approach to the improvement of in-line oil debris sensor capability, Smart Mater. Struct., 2009, vol. 18. https://doi.org/10.1088/0964-1726/18/8/08501010.1088/0964-1726/18/8/085010 ↗
5. Liang, M., et al., US Patent 8073634, 2011.
6. Li, C., Peng, J., and Liang, M., Enhancement of the wear particle monitoring capability of oil debris sensors using a maximal overlap discrete wavelet transform with optimal decomposition depth, Sensors, 2014, vol. 14, pp. 6207–6228. https://doi.org/10.3390/s14040620710.3390/s140406207 ↗
7. Addison, P.S., The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance, Boca Raton: CRC Press, 2016, 2nd ed.
8. D’yakonov, V.P. and Abramenkova, I.V., MATLAB. Obrabotka signalov i izobrazhenii. Spetsial’nyi spravochnik (MATLAB: Processing of Signals and Images. Special Handbook), St. Petersburg: Piter, 2002.