Hydraulic systems are complex dynamical systems whose performance can be degraded by certain faults, specifically internal or external leakage. The objective of this research is to develop an appropriate signal processing approach for detection and isolation of these faults. By analyzing the dynamics of the hydraulic actuator, an internal leakage is shown to increase the damping characteristic of the system and change the transient response of the pressure signals. An external leakage, on the other hand, drops the pressure signals without having a significant effect on transient responses.
Offline detection of internal leakage in hydraulic actuators is first examined by using fast Fourier, wavelet and Hilbert-Huang transforms. The original pressure signal is decomposed using these transform methods and the frequency component which is sensitive to the internal leakage is identified. The root mean square of the processed pressure signal is used and a comparison of the three transforms is made to assess their ability to detect internal leakage fault, through extensive validation tests. The wavelet transform method is shown to be more suitable for internal leakage detection compared to the other two methods. The wavelet based approach is then extended to an online detection method of internal leakage fault. The online approach considers the more realistic case of an actuator that is driven in a closed-loop mode to track pseudorandom position reference inputs against a load emulated by a spring. Furthermore, the method is shown to remain effective even with control systems which are tolerant to leakage faults.
Next, the application of wavelet transform to detect external leakage fault using both offline and online applications in hydraulic actuators is described. The method also examines the isolation of this fault from actuator internal leakage in a multiple-fault environment. The results show that wavelet transform is a fast and easily-implementable method for leakage detection in hydraulic actuators without any need to explicitly incorporate the model of actuator or leakage. Internal leakages as low as 0.124 lit/min, are shown to be detectable, for 80% of the times using structured input signal. For online application, internal leakages in the range of 0.2-0.25 lit/min can be identified. External leakages as low as 0.3 lit/min can be detected in all offline and online applications. Other methods such as observer based and Kalman filter methods, which require the model of the actuator or leakage fault, cannot report leakage detection of magnitudes as low as that reported in this work. The low leak rate detection and not requiring a model of the actuator or leakage make this method very attractive for industrial implementation.
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/4591 |
| Date | 15 April 2011 |
| Creators | Yazdanpanah Goharrizi, Amin |
| Contributors | Sepehri, Nariman (Mechanical and Manufacturing Engineering), Balakrishnan, Subramaniam (Mechanical and Manufacturing Engineering) Filizadeh, Shaahin (Electrical and Computer Engineering) Dumont, Guy (Electrical and Computer Engineering - University of British Columbia) |
| Source Sets | University of Manitoba Canada |
| Language | en_US |
| Detected Language | English |
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