کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
731942 893188 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Extension of the bond graph causality inversion method for fault detection and isolation
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Extension of the bond graph causality inversion method for fault detection and isolation
چکیده انگلیسی


• The bond graph model bicausality is used to generate ARRs.
• These ARRs are used to improve the isolability capabilities of the diagnosis technique.
• The algorithm was implemented in an electromechanical subsystem of a Robot.

Controlled systems can be subjected to faults that may affect the performance of the system, and unable its objectives to be achieved. Fault detection and isolation algorithms are then used to study these faults. The bond graph tool can be used for modeling purposes and then its structural, and causal properties can be exploited for automatic generation of analytical redundancy relations (ARRs) through a procedure named causality inversion method, which are used for diagnosis applications. These ARRs are mathematical constraints that are used to verify the coherence between the process measurements and the system model. This paper proposes an extension of the causality inversion method by different versions of the same ARR. The goal is to increase the number of isolable faults. Moreover, structural conditions are given in order to avoid the generation of redundant ARRs. To validate the obtained structural procedure, a fault is imposed in a traction of an omnidirectional mobile robot.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechatronics - Volume 24, Issue 8, December 2014, Pages 1042–1049
نویسندگان
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