In pneumatic actuating systems, various kinds of faults are key factors in degrading system performance and increasing air consumption. It is therefore valuable to monitor pneumatic systems and implement predictive maintenance based on detection and diagnosis of fault conditions. This research investigates effects of leakages on a PLC control industrial multi-actuator (9 cylinders) pneumatic system. Leakages at 8 different levels and 9 different places are introduced in experimental tests. The dynamic models of actuators and control valves in pneumatic systems are discussed and extracted as system performance features in a quantitative study of leakage fault. Due to nonlinear properties of compressed air and friction force, derived dynamic model alone is not able to effectively indicate fault location and level with an expected accuracy. On the other hand, new qualitative methods using processed sensory information for recognizing fault and estimating its levels are devised. The reliability of fault detection and diagnosis solution in a pneumatic system offered by the mathematical tools is found to be highly dependent on the successful selection of input features those are extracted from original signals and the relationship between those extracted features. Finally we present the multi-actuator based vectorized map and a diagnostic features search method which are improvements of previous fault analysis research in one-cylinder pneumatic system. The proposed method is also a good asset to pneumatic component selection applications. My research work concludes that it is possible to find suitable and reliable on-line monitoring solutions for multi-actuator pneumatic systems by means of locating and estimating compressed air leakage with a better confidence and a relatively small number of sensor installations.