| Title | Multi-band Analysis for Enhancing Multiple Combined Fault Diagnosis |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Hmida, Mohamed Ali, Abid, Firas Ben, Braham, Ahmed |
| Conference Name | 2021 18th International Multi-Conference on Systems, Signals Devices (SSD) |
| Date Published | mar |
| Keywords | compound fault, Cyber-physical systems, fault diagnosis, fault location, Hardware, Harmonic analysis, human factors, induction motor, Induction motors, Metrics, multiple fault diagnosis, pubcrawl, Resiliency, Rotors, Wavelet packets, wavelet transform |
| Abstract | In this work, a novel approach to detect and diagnose single and combined faults in the Induction Motor (IM) is proposed. In Condition Monitoring Systems (CMS) based on the Motor Current Signature Analysis (MCSA), the simultaneous occurrence of multiple faults is a major challenge. An innovative technique called Multiple Windowed Harmonic Wavelet Packet Transform (MWHWPT) is used in order to discriminate between the faulty components of the IM, even during compound faults. Thus, each motor component is monitored by a specific Fault Index (FI) which allows the fault diagnosis without the need for a classifier. The tests carried on Rotor and Bearing faults show high fault diagnosis rate even during compound faults and proves the competitive performance of the proposed approach with literature works. |
| DOI | 10.1109/SSD52085.2021.9429467 |
| Citation Key | hmida_multi-band_2021 |
Multi-band Analysis for Enhancing Multiple Combined Fault Diagnosis