ENHANCEMENT OF THE METHODOLOGY FOR ASSESSING THE NEGATIVE ENVIRONMENTAL IMPACT OF DIESEL FIRE ENGINES IN THE FREE ACCELERATION MODE USING A ROBOTIC MANIPULATOR

The aim of this study is to improve the objectivity and validity of an original methodology for assessing the negative environmental impact of diesel fire trucks on the air by automating the procedure for measuring exhaust gas smoke in free acceleration mode. A robotic manipulator has been developed to replace the human operator during a standardized free acceleration cycle for smoke control, as a technical standard for environmental safety under current legislation. Comparative experimental studies were conducted on a fleet of diesel fire trucks using both a manual method and an automated system. The results were processed using mathematical statistics, including the calculation of the coefficient of variation and linear correlation. The theoretical basis for the diagnostics was provided by physicochemical models of soot formation in the fuel plume and the operation of catalytic converters, described by a system of kinetic equations and the diffusion limitation criterion (Thiele modulus). It has been established that the use of a robotic manipulator can significantly improve the reproducibility of exhaust smoke measurements. The coefficient of variation of the results decreased from 18,1 % (manual method) to 6,9 % (automated method). The obtained stable data allowed us to identify a strong statistically significant correlation between smoke emission and the mileage of fire trucks (determination coefficient R² = 0,87). Smoke emission was shown to be an integral parameter suitable for assessing the reduction in the efficiency of a catalytic converter due to the degradation of its active layer. The scientific novelty lies in the development of a comprehensive methodology integrating a hardware platform, a measurement procedure, and an analytical apparatus based on physicochemical models for diagnosing diesel fire trucks. For the first time in this type of technology, the possibility of using stable smoke emission data as a reliable input parameter for models based on diffusion limitation theory was demonstrated. The practical significance of the results lies in the creation of a tool for generating a reliable evidence base for environmental monitoring, proactively identifying technical faults and fire-hazardous conditions, and developing systems for predicting the remaining life of fire suppression systems.