Litcius/Paper detail

Analysis of pneumatic parameters to identify leakages and faults on the demand side of a compressed air system

Kyle Abela, Paul Refalo, Emmanuel Francalanza

2021Cleaner Engineering and Technology27 citationsDOIOpen Access PDF

Abstract

Despite their significant use in industrial automation, compressed air systems have a typical efficiency of around 10–20%. Literature shows that data monitoring systems are being introduced to detect losses, however, demand side monitoring techniques make use of highly dedicated proprietary equipment which has a number of limitations. This study sought to setup an experimental methodology that identifies the effective parametric data which can be monitored on the demand side to identify inefficiencies in compressed air systems. A compressed air test bed was used to quantifiably compare and contrast leakage inefficiencies in varying system complexities and at different system pressures. The test results confirmed that benchmarking is essential when monitoring data on the demand side. Furthermore, it was also concluded that a single pressure sensor, installed at the supply point of an automation system, could be used to detect the pressure difference which is caused by a leak further downstream along the system. This research establishes that this data can be used to estimate the volume of compressed air that is wasted due to a leak. Analysis of the data collected has shown how a 1.6 mm leak results in a pressure drop of around 10%, downstream to the leak. As expected, a leakage increases the air flowrate, however it is concluded that the percentage increase is relative to the complexity and size of the pneumatic system and may not be significantly conclusive when comparing diagnostic data. It is demonstrated that the measurable effects on pressure and flow rate become less profound in more complex systems.

Topics & Concepts

Compressed airLeakLeakage (economics)Pressure dropParametric statisticsComputer scienceAutomationEnvironmental scienceSimulationAutomotive engineeringEngineeringReal-time computingProcess engineeringReliability engineeringMechanical engineeringMathematicsStatisticsEnvironmental engineeringPhysicsThermodynamicsEconomicsMacroeconomicsEnergy Efficiency and ManagementBuilding Energy and Comfort OptimizationSmart Grid Energy Management