RESEARCH OF THE EMOTIONAL STATE OF OPERATORS OF TECHNOLOGICAL INSTALLATIONS OF OIL REFINERIES USING THE METHODOLOGY OF DEEP CONVOLUTIONAL NEURAL NETWORKS

Abstract

Improvement of technical and technological components of such productions through automation of production processes, reduction of the share of manual labour in the performance of work functions by operators, introduction of digital technologies for collection and processing of large amounts of information on the one hand increases labour productivity, on the other hand increases occupational health risks for the personnel due to increasing labour tension caused by psychological and physiological stresses for the employee, which in the form of chronic fatigue and fatigue. To assess the functional state of the operator of oil refinery production units during the performance of their labour functions, an approach using the method of registration of biometric data with the help of deep convolutional neural networks based on the analysis of the characteristics of recognition of emotions on the image of the face to detect the facts of loss of concentration of attention is considered. The article is devoted to the application of deep convolutional neural networks to assess the emotional state of operators of technological units of oil refineries at the workplace.