- Library Home /
- Search Collections /
- Open Collections /
- Browse Collections /
- UBC Theses and Dissertations /
- Real-time performance monitoring and fault diagnosis...
Open Collections
UBC Theses and Dissertations
UBC Theses and Dissertations
Real-time performance monitoring and fault diagnosis of hydraulic manipulators Sun, Xiaodan
Abstract
In this thesis, a revised hydraulic model of a heavy-duty Caterpillar 215B excavator is presented. The functional module based dynamic and hydraulic simulator is rewritten in C and tested. The simulator, which is the fundamental part of the model-based fault diagnostic algorithm for real-time performance monitoring and fault diagnosis, is validated by means of using real system data., Fault diagnosis algorithms are reviewed in both the control and artificial intelligence communities. Based on the analysis of the system's working mechanism, system structure and behavior, a model-based Incremental Fault Diagnostic Algorithm — IFDA is presented which has the capability of multiple fault detection for both sensor and component faults. The IFDA's task is to monitor and diagnose active machine component faults, sensor faults or other electronics faults. Another diagnostic algorithm for the idle machine is proposed to detect electronics failures based on the contribution of hydraulic component deadband behavior. The monitoring and diagnostic system structure and software/hardware configuration are proposed, and the main scheme has been implemented. Experimental data on steady state single fault and multiple fault tests have demonstrated the algorithm.
Item Metadata
Title |
Real-time performance monitoring and fault diagnosis of hydraulic manipulators
|
Creator | |
Publisher |
University of British Columbia
|
Date Issued |
1995
|
Description |
In this thesis, a revised hydraulic model of a heavy-duty Caterpillar 215B excavator is presented. The
functional module based dynamic and hydraulic simulator is rewritten in C and tested. The simulator, which is
the fundamental part of the model-based fault diagnostic algorithm for real-time performance monitoring and
fault diagnosis, is validated by means of using real system data.,
Fault diagnosis algorithms are reviewed in both the control and artificial intelligence communities. Based
on the analysis of the system's working mechanism, system structure and behavior, a model-based Incremental
Fault Diagnostic Algorithm — IFDA is presented which has the capability of multiple fault detection for both
sensor and component faults. The IFDA's task is to monitor and diagnose active machine component faults,
sensor faults or other electronics faults. Another diagnostic algorithm for the idle machine is proposed to detect
electronics failures based on the contribution of hydraulic component deadband behavior. The monitoring and
diagnostic system structure and software/hardware configuration are proposed, and the main scheme has been
implemented. Experimental data on steady state single fault and multiple fault tests have demonstrated the
algorithm.
|
Extent |
5332419 bytes
|
Genre | |
Type | |
File Format |
application/pdf
|
Language |
eng
|
Date Available |
2009-01-15
|
Provider |
Vancouver : University of British Columbia Library
|
Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
|
DOI |
10.14288/1.0064865
|
URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
|
Graduation Date |
1995-05
|
Campus | |
Scholarly Level |
Graduate
|
Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.