Data acquisition is a crucial stage in the execution of condition monitoring (CM) of rotating machinery, by means of vibration analysis. However, the major challenge in the execution of this technique lies in the features of the recording equipment (accuracy, resolution, sampling frequency and number of channels) and the cost they represent. The present work proposes a low-cost data acquisition system, based on Raspberry-Pi, with a high sampling frequency capacity in the recording of up to three channels. To demonstrate the effectiveness of the proposed data acquisition system, a case study is presented in which the vibrations registered in a bearing are analyzed for four degrees of failure.

Increasing industrial competitiveness has led to an increased global interest in condition monitoring. In this sector, rotating machinery plays an important role, where the bearing is one of the most critical components. Many vibration-based signal treatments are already being used to identify features associated with bearing faults. The information embedded in such features are employed in the construction of health indicators, which allow for evaluation of the current operating status of the machine. In this work, the use of contour maps to represent the diagnosis map of a bearing, used as a health map, is presented for the first time. The results show that the proposed method is promising, allowing for the satisfactory detection and evaluation of the severity of bearing damage. In this initial stage of the research, our results suggest that this method can improve the classification of bearing faults and, therefore, optimise maintenance processes.

The diagnosis of the state of machinery is becoming increasingly important in a more competitive industrial sector. Therefore, maintenance strategies are essential to ensure the correct and continuous operation of equipment. In the last decade, the application of condition based monitoring (CBM) has increased significantly in the detection of bearing faults. CBM is based on the characterisation of equipment behaviour and focuses on preventing a machine from failing. Therefore, fault characterisation and the construction of health indicators is a fundamental issue in CBM. This study evaluates the performance of the diagnostic methodology based on the construction of contour maps from envelope spectra. This allows the construction of visual maps that characterise the evolution of the amplitude of a fault frequency and its harmonics. They also serve as a reference to establish health indicators of future equipment conditions. The results suggest that the methodology holds promise for bearing condition classification. Furthermore, the use of contour maps is a visually intuitive tool for the analyst.

Vibration is a main factor in the driving comfort contribution and can affect the human body by being transmitted through the seats and backrests. The vibrations produced in transport are transferred to the human body, affecting passenger comfort in terms of physical health (amplitude, duration, frequency range) and psychological health (type of population, sex, age). Transport comfort is governed by evaluation tests, ISO 2631-1:1997 standard evaluates human exposure to vibrations, UNE EN 12299 standard is based on the previous one, allowing the evaluation of user comfort by calculating the average and continuous comfort index. Acquisition of acceleration data on the x,y,z axes is weighted in frequency with respect to its direction and weighting curves as a rule. Root mean square values (continuous comforts) are obtained, and the 50th and 95th percentiles for the subsequent calculation of mean comfort. The Sperling method obtains the ride quality and users comfort according to weights. The data has been extracted by the Freematics One+ device at various tram locations. The EN 12299 standard studies the acceleration behaviour (x,y,z), time, latitude, longitude, speed. It is possible to calculate the comfort index of the tram by means of norms and the Sperling method. The data was processed in Matlab obtaining favourable values in the two experimental trials, indicating that the tram in the city of Cuenca, Ecuador is very comfortable and the vibrations produced are slightly perceived by users.

The development of low-cost data acquisition equipment is relevant in the increasingly automated industry of today. This study presents the optimization of low-cost data acquisition equipment performance to achieve acquisition speeds of 200 kHz. This was possible by evaluating two essential aspects: considering the influence of the power supplied by the power source and changing the type of data used from “Double” to “uint”. This equipment was validated through the acquisition of known waves and vibration signals from a bearing test bench. The frequency component was satisfactorily identified in each case, for both the known waves and the damaged bearing components. This demonstrated the viability of developing low-cost data acquisition equipment that can be implemented to monitor bearing condition.