ANALYTİCAL IDENTİFİCATİON AND INTELLİGENT CONTROL OF EMERGENCY MODES İN PARALLEL GAS PİPELİNES BASED ON IOT MONİTORİNG

This study proposes an analytically driven framework for the detection and control of emergency operating conditions in parallel gas pipeline networks supported by real-time digital monitoring. The approach addresses the limitations of purely sensor-based supervision by incorporating gas-dynamic analysis into the decision-making process, which allows a clear distinction between normal operational transients and emergency-induced disturbances. A pressure-based analytical condition is formulated for emergency recognition using inlet and outlet measurements, followed by a physics-oriented method for estimating the location of gas leakage without deploying additional sensing equipment. In addition, a time-dependent control rule is derived for the activation of interconnecting pipeline valves, accounting for compressor station dynamics in order to restore system stability and preserve the integrity of unaffected pipeline lines. The proposed solution is structured as an automated feedback control scheme compatible with SCADA architectures and IoT environments. Its implementation enables a reduction in gas losses, operational uncertainty, and system vulnerability, while supporting the transition toward digitally managed gas transmission infrastructures.