A Comparison of Residual-based Methods on Fault Detection

An important initial step in fault detection for complex industrial systems is gaining an understanding of their health condition. Subsequently, continuous monitoring of this health condition becomes crucial to observe its evolution, track changes over time, and isolate faults. As faults are typically rare occurrences, it is essential to perform this monitoring in an unsupervised manner. Various approaches have been proposed not only to detect faults in an unsupervised manner but also to distinguish between different potential fault types. In this study, we perform a comprehensive comparison between two residual-based approaches: autoencoders, and the input-output models that establish a mapping between operating conditions and sensor readings. We explore the sensor-wise residuals and aggregated residuals for the entire system in both methods. The performance evaluation focuses on three tasks: health indicator construction, fault detection, and health indicator interpretation. To perform the comparison, we utilize the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dynamical model, specifically a subset of the turbofan engine dataset containing three different fault types. All models are trained exclusively on healthy data. Fault detection is achieved by applying a threshold that is determined based on the healthy condition. The detection results reveal that both models are capable of detecting faults with an average delay of around 20 cycles and maintain a low false positive rate. While the fault detection performance is similar for both models, the input-output model provides better interpretability regarding potential fault types and the possible faulty components.Comment: 10 pages, submitted to the 15th Annual Conference of the Prognostics and Health Management Societ

Predicting the Remaining Useful Life of Rolling Element Bearings

Condition monitoring of rolling element bearings is of vital importance in order to keep the industrial wheels running. In wind industry this is especially important due to the challenges in practical maintenance. The paper presents an attempt to improve the capability of prediction of remaining useful life of rolling bearings. The approach is based on the understanding of the wear of bearings i.e. wear modelling is briefly discussed. A simulation model has been built to produce vibration data of the monitoring of rolling bearings taking into account typical vibration excitations in addition to the wear. The simulation model is used to develop signal analysis methods and means of prognosis of the remaining useful life. One complete example of the above described process is shown and discussed in the paper.</p

Implementación de un módulo de simulación para el diagnóstico vibracional de fallas en rodamientos para el rotor kit del laboratorio de diagnóstico técnico y eficiencia energética de la Facultad de Mecánica

El presente trabajo tuvo como objetivo implementar un módulo de simulación para el diagnóstico vibracional de fallas en rodamientos para el rotor kit del laboratorio de diagnóstico técnico y eficiencia energética, para lo cual se realizó cálculos a fin de seleccionar los elementos y posteriormente realizar la comparación de los valores de frecuencia y amplitud de envolvente, con rodamientos en buen y mal estado. Primero, se procedió a la selección de las piezas mecánicas, mediante ciertas consideraciones técnicas, seguidamente, se comenzó con la construcción del módulo, para realizar los ensayos mediante análisis vibracional, usando el rodamiento 6208-2RS1; posteriormente se realizó un plan de mantenimiento, en base a la metodología de recomendaciones de los fabricantes, seguido por una guía de laboratorio y un manual de operación, tomando en cuenta criterios como la seguridad de los estudiantes, la facilidad para relacionarse con el módulo y el fortalecimiento de conceptos. Se hizo la comparación de mediciones, dando como resultado que el valor más alto de amplitud de envolvente para un rodamiento con frecuencias BPFO es de 0,386 gE, en presencia de frecuencias BPFI, el valor más prominente de amplitud de envolvente es de 0,116 gE, y los valores de amplitud más elevados ante frecuencias BPFO y BPFI, son de 0,292 y 0,486 gE; los valores más bajos se obtuvieron en el plano axial. Se concluye que para el rodamiento con la frecuencia BPFO, el mejor punto de medición es el horizontal, para la frecuencia BPFI, la mejor dirección es el vertical; y teniendo las frecuencias de BPFO y BPFI los mejores planos de medición son el vertical y horizontal, resulta más complicado detectar fallas en el plano axial. Se recomienda inducir fallas en otros tipos de rodamientos para estudiar el comportamiento que tienen al someterlos a un trabajo continuo.The objective of this research work was to implement a simulation module for the vibrational diagnosis of faults in rotor bearings for the kit of the technical diagnosis and energy efficiency laboratory, for which calculations were made in order to select the elements and subsequently carry out the comparison of the frequency values, and amplitude envelope with bearings in good and bad condition. First, the selection of the mechanical parts was carried out, based on certain technical considerations, then the construction of the module began, to carry out the tests by means of vibrational analysis, using the 6208-2RS1 bearing; Subsequently, a maintenance plan was carried out, based on the manufacturers' recommendations methodology, followed by a laboratory guide and an operation manual, taking into account criteria such as the students’ safety, the ease of interacting with the module and strengthening concepts. The comparison of measurements was made, giving as a result that the highest value of amplitude envelope for a bearing with BPFO frequencies is 0,386 gE, in the presence of BPFI frequencies. The most prominent value of envelope amplitude is 0,116 gE, and the highest amplitude values at BPFO and BPFI frequencies are 0,292 and 0,486 gE; the lowest values were obtained in the axial plane. It is concluded that for the bearing with the BPFO frequency, the best measurement point is the horizontal, for the BPFI frequency, the best direction is the vertical; and having the BPFO and BPFI frequencies, the best measurement planes are the vertical and horizontal. It is more difficult to detect faults in the axial plane. It is recommended to induce faults in other types of bearings to study their behavior when subjected to continuous work