DOI:
https://doi.org/10.14483/22484728.17058Published:
2020-11-17Issue:
Vol. 14 No. 2 (2020)Section:
A Case-Study VisionDistributed Fault Diagnosis System based on Wireless Sensor Networks
Sistema de diagnóstico distribuido de fallas basado en redes inalámbricas de sensores
Keywords:
Análisis distribuido, Diagnóstico de fallas, Motor de Inducción, Motor-Current Signature Analysis, Corriente de estator, Redes inalámbricas de sensores, ZigBee (es).Keywords:
Distributed Analysis, Fault Diagnosis, Induction Motor, Motor-Current Signature Analysis, Stator Current, Wireless Sensor Networks, ZigBee (en).Downloads
Abstract (en)
This article presents the development of a distributed fault diagnosis and monitoring system whose remote nodes are responsible for data collection and distributed analysis to identify problems that could lead to critical faults in industrial processes or systems. The developed intelligent remote node was implemented with MCU LPCXpresso54114 connected to a ZigBee protocol wireless sensor network through XBee communication module. The gateway node is a Raspberrry PI with HTTP communication and JSON format to the PI System industrial monitoring system database. Motor Current Signature Analysis (MCSA) was implemented and validated to identify interturn faults of induction motors. The developed platform is a tool to perform comparison and validation of analysis techniques, indicators, and fault classification, because there are different combinations that can be applied to improve diagnosis reliability, fault observability, differentiation between fault conditions, classification accuracy, tolerance to transients, sensitivity, among others.
Abstract (es)
En este artículo presenta el desarrollo de un sistema de monitoreo y diagnóstico distribuido cuyos nodos remotos se encarguen de la recolección de datos y su posterior análisis para la identificación de anomalías que representen fallas críticas para el proceso o sistema industrial. El dispositivo desarrollado como nodo remoto inteligente se implementó con MCU LPCXpresso54114 con conexión a una red inalámbrica de sensores basada en protocolo ZigBee mediante tarjetas de comunicación XBee. El nodo concentrador está compuesto de una tarjeta Raspberrry PI con comunicación mediante protocolo HTTP y formato JSON a la base de datos del sistema de monitoreo industrial PI System. Se implementó y validó el acondicionamiento de señal para la medición de corrientes de estator (MCSA) que permitió identificar fallas entre espiras de motores de inducción tipo jaula de ardilla. La plataforma presentada finalmente es una herramienta para realizar comparación y validación de técnicas de análisis, indicadores y de clasificación de fallas, puesto que existen diversas combinaciones que pueden ser aplicadas con el fin de mejorar la confiabilidad del diagnóstico, la observación de la falla, la diferenciación entre condiciones de falla, la precisión de la clasificación, la tolerancia a transitorios, sensibilidad, entre otros.
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