George O. de A. Azevedo;Leandro H. de S. Silva;Agostinho Freire;Rogério P. de Araújo;Bruno J. T. Fernandes
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Monitoring rotating machines is essential for evaluating operations, preventing failures, and improving efficiency. Traditional rotational measurement methods, like magnetic induction or optical sensors, typically require dedicated hardware for each rotating part, making them costly and complex to implement, especially in industrial scenarios. The challenge intensifies when multiple rotations must be measured simultaneously. This study introduces a novel method using a single-event-based vision sensor, or dynamic vision sensor (DVS), which offers asynchronous pixel activation, high temporal resolution, and a wide dynamic range. Unlike traditional frame-based sensors, which require high frame rates and generate large data volumes, the DVS analyzes event streams and processes signals to identify crossing edges and time intervals. This enables simultaneous measurement of multiple rotating parts. The method was tested on a fan propeller, a CNC lathe, and drone propellers, demonstrating a relative mean absolute error (MAE) of around 0.5%. This method allows safe distance measurements without altering the original production line due to its non-contact nature.
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