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Abstract
Mazkur ilmiy maqolada ishlab chiqarish jarayonlarida yuzaga keladigan texnik nosozliklarni oldindan aniqlashga qaratilgan sun’iy intellekt va mashinaviy o‘rganish algoritmlariga asoslangan intellektual diagnostika modeli ishlab chiqilgan. Tadqiqotda ishlab chiqarish uskunalaridan real vaqt rejimida olinadigan sensor ma’lumotlari (harorat, vibratsiya, bosim va elektr parametrlar) asosida nosozliklarni erta bosqichda aniqlash imkonini beruvchi mashinaviy o‘rganish usullari tahlil qilingan
References
1. Mobley R. K. An Introduction to Predictive Maintenance. — 2nd edition. — Oxford: Butterworth-Heinemann, 2002. — 440 p.
2. Jardine A. K. S., Lin D., Banjevic D. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 2006, Vol. 20, Issue 7, pp. 1483–1510.
3. Lee J., Bagheri B., Kao H. A. A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 2015, No. 3, pp. 18–23.
4. Zhang W., Yang D., Wang H. Data-driven methods for predictive maintenance of industrial equipment: A survey. IEEE Systems Journal, 2019, Vol. 13, No. 3, pp. 2213–2227.
5. Soha A., Hamid R. Deep learning-based fault diagnosis in industrial systems. Journal of Intelligent Manufacturing, 2020, Vol. 31, No. 4, pp. 905–917