Kristóf Lajber;József Szőlősi;Béla J. Szekeres;Mátyás Andó
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引用次数: 0
Abstract
In modern industrial settings, adopting data-driven methodologies in manufacturing processes has become essential. Reliable tools capable of providing real-time data on the operational status of equipment form the foundation of advanced automated systems. Such data can be used to develop digital systems that support decision-making processes based on real-time insights. This research presents the development of a sensor-based measurement system designed to accurately monitor the position of the welding torch in arc welding applications. The system integrates the sensor into a protective housing affixed to the welding torch and connects it to specialized software for data acquisition. Testing has demonstrated that the system delivers the precision required during welding operations, enabling real-time data visualization. The system was developed using electronic components, programming techniques, and additive manufacturing technologies.
期刊介绍：
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice
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