title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³Ð° Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ° Ð¿Ð¾ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ 09.04.01 - ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸ÐºÐ° Ð¸ Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½Ð°Ñ ÑÐµÑ Ð½Ð¸ÐºÐ° ; 09.04.01_17 - ÐÐ½ÑÐµÐ»Ð»ÐµÐºÑÑÐ°Ð»ÑÐ½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ (Ð¼ÐµÐ¶Ð´ÑÐ½Ð°ÑÐ¾Ð´Ð½Ð°Ñ Ð¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð°Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð°)
titleType: Subtitle
Creators: name: Ð¨Ð°ÑÑÐ¸, Ð¨Ð°Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2019
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
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description: Ð Ð½Ð°ÑÑÐ¾ÑÑÐµÐµ Ð²ÑÐµÐ¼Ñ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÐµ Ð¾ÑÑÐ°ÑÐ»Ð¸ Ð¾Ð±ÑÐ°Ð±Ð°ÑÑÐ²Ð°ÑÑÐµÐ¹ Ð¿ÑÐ¾Ð¼ÑÑÐ»ÐµÐ½Ð½Ð¾ÑÑÐ¸ Ð¿ÑÐ¸Ð»Ð°Ð³Ð°ÑÑ Ð²ÑÐµ ÑÑÐ¸Ð»Ð¸Ñ Ð´Ð»Ñ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð¼Ð¸Ð½Ð¸Ð¼Ð°Ð»ÑÐ½ÑÑ Ð¿Ð¾ÑÐµÑÑ Ð¸ Ð¼Ð°ÐºÑÐ¸Ð¼Ð°Ð»ÑÐ½Ð¾Ð¹ Ð¿ÑÐ¸Ð±ÑÐ»Ð¸. ÐÐ»Ñ ÑÑÐ¾Ð³Ð¾ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼Ð¾ Ð¿ÑÐ¾Ð²ÐµÑÑÐ¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´ÑÑÐ²ÐµÐ½Ð½ÑÑ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð², ÐºÐ¾ÑÐ¾ÑÑÐµ Ð¸Ð¼ÐµÑÑ ÑÐ¾Ñ Ð¸Ð»Ð¸ Ð¸Ð½Ð¾Ð¹ Ð²Ð¸Ð´ ÑÐ±Ð¾ÐµÐ². Ð§Ð¸ÑÐ°Ñ ÑÐ¸Ð³Ð½Ð°Ð»Ñ Ð¾Ñ Ð¼Ð°ÑÐ¸Ð½Ñ, Ð¼Ñ Ð¼Ð¾Ð¶ÐµÐ¼ Ð½Ð°ÑÑÐ¸ÑÑÑÑ Ñ Ð½ÐµÐµ ÑÐ¾Ð·Ð´Ð°Ð²Ð°ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ñ, ÐºÐ¾ÑÐ¾ÑÐ°Ñ Ð¼Ð¾Ð¶ÐµÑ Ð¾Ð±Ð½Ð°ÑÑÐ¶Ð¸ÑÑ Ð½ÐµÐ¸ÑÐ¿ÑÐ°Ð²Ð½Ð¾ÑÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð½Ð¸Ð¹ ÑÐ¸Ð³Ð½Ð°Ð»Ð° Ð¸ Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸ÑÑ Ð¿ÑÐ¸Ð½ÑÑÐ¸Ðµ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼ÑÑ Ð¼ÐµÑ Ð´Ð»Ñ Ð¿ÑÐµÐ´Ð¾ÑÐ²ÑÐ°ÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¸ÑÐ¿ÑÐ°Ð²Ð½Ð¾ÑÑÐ¸. 
ÐÐ°Ð½Ð½ÑÐ¹ Ð¿ÑÐ¾ÐµÐºÑ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½ Ð½Ð° Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ ÑÐ±Ð¾ÐµÐ² Ð² ÑÐ¸ÑÑÐµÐ¼Ðµ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³Ð° Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð°. Ð ÑÐ°Ð¼ÐºÐ°Ñ ÑÐ²Ð¾Ð¸Ñ Ð·Ð°Ð´Ð°Ñ Ð°Ð²ÑÐ¾Ñ ÑÐ°Ð±Ð¾ÑÐ°Ð» Ð½Ð°Ð´ ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ð¼Ð¸, Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÐ¼Ð¸ Ð² ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐµÑÑÑÐµÑ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸. ÐÐ±ÑÐ°Ð±Ð°ÑÑÐ²Ð°ÑÑÐ¸Ðµ Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¸ Ð²ÐºÐ»ÑÑÐ°ÑÑ ÑÐ¾ÐºÐ°ÑÐ½ÑÑ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÑ, ÑÐ²ÐµÑÐ»ÐµÐ½Ð¸Ðµ, ÑÑÐµÐ·ÐµÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¸ ÑÐ¾ÑÑÐµÐ²Ð¾Ðµ ÑÑÐµÐ·ÐµÑÐ¾Ð²Ð°Ð½Ð¸Ðµ. ÐÐ½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ Ð¾Ñ ÑÑÐ¸Ñ ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð² Ð±ÑÐ»Ð° ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð°, Ð¿Ð¾ÑÐ»Ðµ ÑÐµÐ³Ð¾ Ð±ÑÐ»Ð¸ Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ñ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸ Ð¸ Ð¾Ð±ÑÐµÐ´Ð¸Ð½ÐµÐ½Ñ. Ð¢Ð°ÐºÐ¸Ð¼ Ð¾Ð±ÑÐ°Ð·Ð¾Ð¼, Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ð³Ð¾ÑÐ¾Ð² Ðº ÑÐ°Ð±Ð¾ÑÐµ. 
ÐÐ¾ÑÐ»Ðµ ÑÑÐ¾Ð³Ð¾ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ Ð±ÑÐ»Ð° Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð° Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð´Ð»Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ ÑÐ±Ð¾Ñ. ÐÐ¾ÑÐºÐ¾Ð»ÑÐºÑ ÑÐ±Ð¾Ð¹ Ð¿ÑÐ¸Ð²Ð¾Ð´Ð¸Ñ Ðº Ð¿Ð¾ÑÐµÑÑÐ¼, Ð±ÑÐ»Ð¾ Ð¾Ð³ÑÐ°Ð½Ð¸ÑÐµÐ½Ð¸Ðµ Ð¿Ð¾ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ñ Ð½Ð°Ð±Ð¾ÑÐ¾Ð² Ð´Ð°Ð½Ð½ÑÑ Ð¾ ÑÐ±Ð¾ÑÑ. ÐÐ»Ñ ÑÐµÑÐµÐ½Ð¸Ñ ÑÑÐ¾Ð¹ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð±ÑÐ»Ð° ÑÐ°ÐºÐ¶Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð° ÑÐ±Ð°Ð»Ð°Ð½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾ÑÑÑ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð°Ñ Ð°Ð²ÑÐ¾ÑÐ¾Ð¼ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ¹ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð° Ð¾ÑÐ»Ð¸ÑÐ½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¿ÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐ¾ÑÐ¾ÑÐ¸Ñ Ð¸ Ð¿Ð»Ð¾ÑÐ¸Ñ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÐ¼Ð¾Ð³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ. ÐÐ»Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¾ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ ÐÐ°ÑÐ»Ð°Ð±. ÐÑÐ» ÑÐ°ÐºÐ¶Ðµ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð¿Ð¾Ð´ÑÐ¾Ð±Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð². ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð±ÑÐ»Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð´Ð»Ñ Ð¸Ð·ÑÑÐµÐ½Ð¸Ñ Ð²Ð°ÑÐ¸Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ.
description: Nowadays, major manufacturing industries are striving hard to ensure minimum loss and maximum profit. A method to do so is to do research on the manufacturing processes which have some kind of failure. By reading the signals from the machine we can learn from it to create a model that could detect the failure by signal readings and ensure the necessary steps can be taken to avoid failure. 
This project deals with the detection of failures in a process monitoring system using a neural network approach. As part of his tasks, the author has worked on signals derived from four different machining processes. The machining operations are turning, drilling, milling and face milling. The information from these signals was segmented, following which features were extracted, and concatenated. Thus a data set was ready to work on. 
Following this, the information was used to train a neural network model to detect the failure. As failure causes losses, there was limitation in the amount of failure datasets. To tackle this problem, balancing of the dataset was also implemented. The neural network model designed by the author showed excellent results in classifying the good and bad processes based on the data set used. The software used for the programming of the model was Matlab. A detailed analysis was also done on the results obtained. The obtained results were then used for studying the parameter variation analysis of the neural network system.