Scholarly record

OPTIMIZING ENERGY EFFICIENCY AND OCCUPATIONAL SAFETY IN ATEX ENVIRONMENTS THROUGH VARIABLE STRUCTURE INDUSTRIAL VENTILATION SYSTEMS

Adrian Matei, Alexandru Camarasescu, Razvan Dragoescu, Emeric Chiuzan, Andrada Denisa Matei

Abstract

This paper presents the development and experimental validation of an intelligent variable-structure control system for optimizing industrial ventilation in ATEX (ATmospheres EXplosibles) environments. Current ventilation solutions, based on continuous maximum-flow operation, consume 15 to 40 percent of total industrial hall energy and remain largely reactive to hazardous atmosphere formation. The proposed system integrates Model Predictive Control (MPC) with Artificial Neural Network (ANN) algorithms and a spatial 3D sensor network to achieve proactive, real-time optimization of ventilation parameters. The architecture features variable topology – selectively activating exhausters based on emission source localization – and edge computing for sub-second response latency. Experimental validation on a representative laboratory stand (210 m3) demonstrates energy consumption reductions of at least 30 percent compared to conventional continuous ventilation, while maintaining concentrations of flammable and toxic gases below 10 to 25 percent of the Lower Explosive Limit (LEL). The system’s modular architecture supports scalability across chemical, petrochemical, mining, and food processing industries, with a projected investment payback period of less than two years. Utilizing preliminary results, we will demonstrate that transitioning from a static to an adaptive operating regime not only significantly reduces operational costs but also increases the resilience of explosion protection systems, aligning with European ATEX directives and modern sustainable development standards.

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