Comprehensive Diagnosis of Localized Rolling Bearing Faults during Rotating Machine Start-Up via Vibration Envelope Analysis
[EN] The analysis of electrical machine faults during start-up, and variable speed and load conditions offers numerous advantages for fault detection and diagnosis. In this context, diagnosing localized bearing faults through vibration signals remains challenging, particularly in developing physical...
| Autores: | , , |
|---|---|
| Tipo de documento: | artigo |
| Data de publicação: | 2024 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglês |
| OAI Identifier: | oai:riunet.upv.es:10251/203999 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/203999 |
| Access Level: | Acceso aberto |
| Palavra-chave: | AC machines Vibration Transient analysis Fault diagnosis INGENIERIA ELECTRICA |
| Resumo: | [EN] The analysis of electrical machine faults during start-up, and variable speed and load conditions offers numerous advantages for fault detection and diagnosis. In this context, diagnosing localized bearing faults through vibration signals remains challenging, particularly in developing physically meaningful, simple, and resampling-free techniques to monitor fault characteristic components throughout machine start-up. This study introduces a straightforward method for qualitatively identifying the time-frequency evolutions of localized bearing faults during the start-up of an inverter-fed machine. The proposed technique utilizes the time-frequency representation of the envelope spectrum, effectively highlighting characteristic fault frequencies during transient operation. The method is tested in an open-source dataset including transient vibration signals. In addition, the work studies the method limitations induced by the mechanical transfer path, when the bearing surroundings are not directly accessible for vibration acquisition. The proposed methodology efficiently identifies incipient localized bearing faults during inverter-fed machine start-up when the fault signature is not highly attenuated. |
|---|