Fault Diagnostic System Bearing Centrifugal Pump Using K-Means Method For Thermography Image And Signal Analysis Vibrations
| Autor: | Yudhistira Hidayat Agung, Widodo Achmad, Dwi Haryadi Gunawan |
|---|---|
| Jazyk: | English<br />French |
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | MATEC Web of Conferences, Vol 159, p 02006 (2018) |
| Druh dokumentu: | article |
| ISSN: | 2261-236X 20181590 |
| DOI: | 10.1051/matecconf/201815902006 |
| Popis: | Numerous studies reported that infrared thermography and vibration are condition monitoring technology that is important and effective for doing a condition diagnostic of bearing centrifugal pump health without destructing or disturbing machine operational. This paper focuses on thermography image processing based on K-Mean color segmentation which will produce normal and abnormal condition features. Health diagnostic of bearing by processing of digital image, image clustering, segmentation and extraction. Extraction of image pattern is done by calculating the area of heat point and color feature bearing condition of RGB colour space and active contour segmentation in order to process and differentiate between normal and abnormal bearing image by statistical technique. The parameters that can be used as reference to classifying conditions are standard deviation, Mean, Variance, Skewness, Kurtosis, Vibration (RMS) and Shape features (area). Final step is determining the boundary condition between normal and abnormal using statistical logic method. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|