Abstract: This patents refers to a system developed for detecting leaks in single-phase and multiphase fluid transport pipelines characterized by use measurements cells (3), sensors (4), locals processors (5) and neural models, where the measuring sensors (4) and the measurement cells (3) are installed at a number of locations along the pipeline with the purpose of monitoring the characteristic leak and normal operational pipeline transient waveforms. The local processors (5) are responsible for obtaining and sampling the signals supplied by the sensors (4), as well as their pre-processing, to make them compatible with the inputs to the neural model, this are associated to dynamic memory banks for analyzing the signals supplied by the sensors with the aim of emitting an alarm in the event that waveforms with the characteristics of a leak are detected.

Abstract: The invention here presented regards to an integrated leak detection system which combines the acoustic technology with mass balance technology using artificial neural networks to achieve leak location, quantification provided with pressure sensors installed in strategic points along the pipeline, which act as acoustic sensors or sonic sensors; remotes units denominated FPU (Field Processing Unit); analog and digital filters; artificial neural networks (ANN); and, center monitoring station responsible for gathering and processing system information, using artificial neural networks algorithms that process also signals from the mass balance CFD (Computacional Fluid Dynamics) based on flow temperature pressure and density readings, to allow process parameter actualization in real time such as fluid density, acoustic wave propagation speed, flow speed and signal attenuation coefficient.

Abstract: This patents refers to a system developed for detecting leaks in single-phase and multiphase fluid transport pipelines characterized by use measurements cells (3), sensors (4), locals processors (5) and neural models, where the measuring sensors (4) and the measurement cells (3) are installed at a number of locations along the pipeline with the purpose of monitoring the characteristic leak and normal operational pipeline transient waveforms. The local processors (5) are responsible for obtaining and sampling the signals supplied by the sensors (4), as well as their pre-processing, to make them compatible with the inputs to the neural model, this are associated to dynamic memory banks for analyzing the signals supplied by the sensors with the aim of emitting an alarm in the event that waveforms with the characteristics of a leak are detected.