Theoretical Computer Science
The nature of statistical learning theory
The nature of statistical learning theory
Time-frequency representations-based detector of chaos in oscillatory circuits
Signal Processing - Signal processing in UWB communications
Real-Time Systems: Theory and Practice
Real-Time Systems: Theory and Practice
| Hi-index | 0.00 |
Motor fault diagnostics in dynamic condition is a typical multi-sensor fusion problem. It involves the use of multi-sensor information such as vibration, sound, current, voltage and temperature, to detect and identify motor faults. According to our experiments in BLDC motor controller results, the system has potential to serve as an intelligent fault diagnosis system in other hard real time system application. To make the system more robust we make the controller more adaptive that give the system response more reliable by the multisensory fusion techniques. We introduce a hybrid model based new methods and evaluate the performance of the proposed information fusion system. Finally, we report the efficiency of this system in dealing with controller stabitility and its nonlinear information that may arise among the sensors.