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A mode identification method for hybrid system diagnosis is proposed. The method is presented as a module of a quantitative health monitoring framework for hybrid systems. After fault occurrence, the fault is detected and isolated. The next step is fault parameters estimation, where the size of the fault is identified. Fault parameter estimation is based on data collected from the hybrid system while...
In this paper, a Hybrid Bond Graph based fault estimation is developed to estimate faulty parameters. This estimation method is based on a set of unified equations called the Global Analytical Redundancy Relations (GARRs). The developed estimation technique estimates fault parameters that can be linearly or nonlinearly parameterized, and it is formulated as a nonlinear least-square problem. This method...
Manufacturing shop floor dynamics such as tool breakage or machine performance degradation or breakdown will disrupt the execution of planned production schedules. An intelligent shop floor is one that is able to react to changes that are occurring in a positive way. To give the early warning of the system/equipment health conditions and job execution capability to the supervisory control will improve...
Recently, a Bond-graph based Fault Detection and Isolation (FDI) framework has been developed with a new concept of Global Analytical Redundancy Relations (GARRs). This new concept allows the fault diagnosis for hybrid systems which consist of both continuous dynamics and discrete modes. In this paper the newly developed method is studied in details using an electro-hydraulic steering system of a...
Manufacturing shop floor dynamics such as machine performance degradation or breakdown will affect the execution of planned production schedules. An intelligent shop floor is able to react to changes in a positive way. To give the early warning of the system/equipment health conditions and mission execution capability to the supervisory control will improve the productivity and efficiency of the shop...
This paper presents a method for the identification of the fault parameters of hybrid systems with unknown mode changes after fault occurring. The identification method utilizes genetic algorithm (GA) to identify fault parameters and unknown mode changes simultaneously based on global analytical redundancy relation (GARR). Fault parameters and mode change time of all switches are encoded into one...
In this work we present a new health monitoring method for hybrid systems. The method utilizes the concept of unified constraint relations, named the global analytical redundancy relations (GARRs). Using GARRs for health monitoring of hybrid system requires the system's current mode and this information is provided by a mode tracker. To make the mode tracking more efficient, a unique mode-change isolation...
A hybrid system combines continuous and discrete dynamics and runs with a set of modes. In we proposed an efficient health monitoring method for hybrid systems. This method utilizes unified constraint relations, named the global analytical redundancy relations (GARRs). Using GARRs for hybrid system health monitoring requires knowledge of the system's mode which is provided by a mode tracker. GARRs...
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