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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.

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