Analysis of Sensor Signals with Machine and Deep Learning Algorithms

Industry 4.0 relies heavily on data generation and analysis. Sensor signals are difficult for analysis using traditional methods and mathematical techniques. Machine and Deep Learning algorithms in combination with mathematical transformations offer effective new ways of approaching the difficult problems of processing sensor signals. The paper’s goal is to propose and validate the data-driven prediction model to analyze sensor data based on machine and deep learning algorithms. The models show promising results in predicting wear values and open the problem to further research.