A Hybrid Prognostic Approach Based on Deep Learning for the Degradation Prediction of Machinery

Remaining useful life (RUL) prediction is of great significance for prognostic and health management (PHM) as it can achieve more reliable and effective maintenance strategies. With the advances in the field of deep learning, data-driven methods have provided promising prognostic prediction results. Hence, this research presents a data-driven prognostic approach based on deep learning models for predicting the RUL of mechanical systems effectively. Multiple separable convolution layers, a bidirectional Long Short-Term Memory (LSTM) layer, and fully-connected layers (FCL) are included in the proposed network, named the SC-BLSTM, to accomplish more accurate prognostic prediction from the raw degradation data acquired by different sensors. The proposed SC-BLSTM approach aims to learn complex and nonlinear features from the input data and capture temporal dependencies from the learned features. The presented approach in this research is tested and verified on the degradation data of turbofan engines (C-MAPSS dataset) from NASA. The result demonstrated that the SC-BLSTM is able to achieve more effective RUL prediction compared with some existing prognostic models

Analysis of Quality based on the life of bearings mounted on an accelerated life test module

Los rodamientos son elementos ampliamente usados en las industrias, cuyo fallo implica un gran impacto en  la producción de toda la empresa de manufactura. Su funcionamiento es vital para equipos electromecánicos con elementos rotativos, ya sea en ejes o en las chumaceras de máquinas industriales. El presente estudio plantea la implementación de un control de calidad mediante un diagrama tipo np a los rodamientos SKF 6204-2RSH, los cuales serán sometidos a elevadas cargas en un módulo de prueba de vida acelerada reduciendo significativamente la vida útil de los mismos y  tomar muestras de cantidades determinadas de rodamientos determinando la cantidad de defectuosos por lote analizado, con el objetico de conocer si es posible determinar el control de calidad de estos elementos por el número de defectos. Los resultados conseguidos mostraron una reducción significativamente en la vida útil de los rodamientos, mostrando defectos que pudieron ser cuantificados y registrados en las tablas por atributos np, para posteriormente ser analizados en la gráfica característica de control de calidad. Después de realizar el análisis de la gráfica de  control se observó un desgaste prudente de los 10 lotes analizados a excepción del número 7, que se muestra un desfase de la línea central y un excedente de los rangos, determinados por la línea inferior y superior respectivamente, conduciendo el estudio a suponer que los rodamientos parte de este lote pudiesen se rechazados antes de su operación en el caso hipotético de ingresar a producción y manufactura.  Cabe señalar que en el presente análisis hubieron factores de lubricación que no fueron considerados y que puede ser objeto para futuras investigaciones enfocadas en los cambios que pueden surgir bajo cambios en las condiciones del lubricante aplicado a los rodamientosThe bearings are elements used in the industries, whose failure implies a great impact on the production of the entire manufacturing company. Its operation is vital for electromechanical equipment with rotating elements, either on shafts or in the bearings of industrial machines. The present study proposes the implementation of a quality control by means of an np-type diagram to SKF 6204-2RSH bearings, which will sometimes be elevated to high loads in an accelerated life test module reducing their useful life and taking samples of determined quantities of bearings determining the amount of defects per lot analyzed, with the aim of knowing if it is possible to determine the quality control of these elements by the number of defects. The results achieved with reduced frequency in the useful life of the bearings, showing the defects that can be quantified and recorded in the np tables, to later be analyzed in the characteristic quality control chart. After carrying out the analysis of the control graph, prudent wear of the 10 lots analyzed was observed with the exception of the number 7, which shows a lag of the central line and a surplus of the ranges, accessories along the lower line and exceeded respectively , leading the study to suppose that the bearings part of this lot could be rejected before its operation in the hypothetical case of entering production and manufacturing. It should be noted that in the present analysis there were lubrication factors that were not selected and that may be subject to future research focused on changes that may be surgical under changes in the conditions of the lubricant applied to the bearings

Data Requirements to Enable PHM for Liquid Hydrogen Storage Systems from a Risk Assessment Perspective

Quantitative Risk Assessment (QRA) aids the development of risk-informed safety codes and standards which are employed to reduce risk in a variety of complex technologies, such as hydrogen systems. Currently, the lack of reliability data limits the use of QRAs for fueling stations equipped with bulk liquid hydrogen storage systems. In turn, this hinders the ability to develop the necessary rigorous safety codes and standards to allow worldwide deployment of these stations. Prognostics and Health Management (PHM) and the analysis of condition-monitoring data emerge as an alternative to support risk assessment methods. Through the QRA-based analysis of a liquid hydrogen storage system, the core elements for the design of a data-driven PHM framework are addressed from a risk perspective. This work focuses on identifying the data collection requirements to strengthen current risk analyses and enable data-driven approaches to improve the safety and risk assessment of a liquid hydrogen fueling infrastructure