Internal leakage diagnosis in valve controlled actuation systems and electrohydrostatic actuation systems
| dc.contributor.author | Alozie, Chinenye | |
| dc.contributor.examiningcommittee | Kinsner, Witold (Electrical and Computer Engineering) Peng, Qingjin (Mechanical and Manufacturing Engineering) | en_US |
| dc.contributor.supervisor | Sepehri, Nariman (Mechanical and Manufacturing Engineering) | en_US |
| dc.date.accessioned | 2014-05-16T15:23:31Z | |
| dc.date.available | 2014-05-16T15:23:31Z | |
| dc.date.issued | 2014-05-16 | |
| dc.degree.discipline | Mechanical and Manufacturing Engineering | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Diagnosis of faults associated with hydraulic actuators is essential to avoid accidents or loss of system functionality. This thesis focuses on internal leakage fault diagnosis in valve controlled hydraulic actuation systems (VCA) as well as electrohydrostatic actuation systems (EHA). For the VCA, the hydraulic actuator is driven in a closed loop mode to track a pseudorandom input signal whereas for the EHA, an actuator is driven in an open loop mode to track a sinusoidal input. Motivated by developing a method that does not rely on the model of the system or type of fault, signal processing techniques based on the ratio of metric lengths of pressure signals, autocorrelation of pressure signal, cross correlation between chamber pressure signals, and cross correlation between control signal and piston displacement is employed for internal leakage diagnosis. For the VCA, autocorrelation of pressure signals performed well at lower lags (less than 4) and at a window size of 200 data points; both cross correlation between pressure signals and cross correlation between control signal and piston displacement performed well at higher lags (higher than 8) and at a window size of 100 data points; ratio of metric lengths of pressure signals was found to be more effective at higher lag ratios (more than 16:3). All methods were sensitive to the lowest simulated leakage of 0.047 L/min, though with different level of success; ratio of metric lengths produced 84% sensitivity, autocorrelation 19% sensitivity, cross correlation between pressure signals 25% sensitivity and cross correlation between piston displacement and control signal 20% sensitivity. For the EHA, all methods were capable of identifying small leakage of 0.98 L/min. The ratio of metric lengths produced 6.7% sensitivity, autocorrelation 2.59% sensitivity, cross correlation between pressure signals 9.4% sensitivity and cross correlation between piston displacement and control signal 31.9% sensitivity. The low leakage detection achieved without requiring a model of the actuator or leakage type make these methods very attractive for industrial implementation | en_US |
| dc.description.note | October 2014 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/23583 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Fault detection | en_US |
| dc.subject | Internal leakage diagnosis | en_US |
| dc.subject | Hydraulic systems | en_US |
| dc.subject | Autocorrelation | en_US |
| dc.subject | Fractal number | en_US |
| dc.subject | Cross correlation | en_US |
| dc.title | Internal leakage diagnosis in valve controlled actuation systems and electrohydrostatic actuation systems | en_US |
| dc.type | master thesis | en_US |