Abstract

Process Monitoring System is implemented in machining process to get the quality products, increase the precision, reduce defects, reduce machining time. The process monitoring system, involves in monitoring many parameters such as temperature, force, pressure, voltage, vibration etc., these parameters are implemented in machining process like lathe operation, milling operation, drilling operation, boring, welding etc. On a traditional way of process monitoring system, there are two techniques namely sensor-based technique and image processing technique. In sensor-based techniques different types of sensors has been used for monitoring such as thermocouple, thermistor, RTD, pressure sensor, accelerometer, vibration sensor, load cell, strain gauge etc., these sensors have been calibrated with a microcontroller for data analysis. Image Processing technique involves in capturing the radiation of the machined/machining product by using Infrared camera, ultraviolet camera, photoelectric thermoscope, optical thermoscope, thermal image camera, continuous circuit television etc., the data captured by using the image sensing devices has been processed and analysed by using machine learning algorithm. In this work monitoring system was developed for monitoring the temperature of the weld region that were welded using MIG/TIG, GTAW, GMAW, Laser, Gas Welding. It can be achieved by using Sensor-based technique. A K-Type thermocouple is fixed with a titanium alloy. This kit is placed under the welded metal and the heat distribution of the metal is studied and analysed.

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