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The performance of the proposed observer, improved fault detection algorithm, and fault-tolerant control system are investigated by simulation.
More widespread use of robotic welding has necessitated greater capability to control welding parameters and robotic motion and improved fault detection and fault correction.
In Section 3, basis of k-NN and its application for fault detection as well as an improved fault detection algorithm are presented.
Systematic sensitivity analyses, made possible by a new iterative approach, allows the identification of key parameters for improved fault detection and model based process control of plasma reactors.
The P+F interface led to faster detection times overall, as well as improved fault detection rate and more accurate fault diagnosis under higher fault loads.
The results show that this method has improved fault detection rate (FDR) in comparison with other currently existing conventional process monitoring methods.
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Simulation study is carried out on the IEEE 34 node test feeder, and the results demonstrate that the proposed approach has significantly improved fault-tolerant capability with satisfatory convergence speed.
The second approach provides modularity and improves fault tolerance of the architecture.
Also, the flexibility provided by RAs can improve fault tolerance and system reliability.
Directional relays such as [16] are widely used to improve fault discrimination in AC grids.
The proposed model improves fault tolerance, assists in cluster capacity management, and monitors the QoS.
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