Abstract
The magnetic field created by technical devices is a source of information. This information could be used in contactless diagnostics and predictive maintenance or for resolving problems along with standard NDT (nondestructive testing) methods, especially if we consider large, slow-speed devices, such as electromotors, transmissions, or generators. Identification of causalities of device failure processes with near magnetic field is one of the suitable NDT methods improving sustainability of systems. The measurements presented in the article were performed with the VEMA 04 fluxgate vector magnetometer with the DC-250 Hz bandwidth and 2 nT sensitivity. Postprocessing of the results was performed in the means of standard methods of discrete Fourier Transform, spectrogram creation and Wavelet Transform. The article presents data gathered during the measurement of a pair of extraction fans with power of 140 kW each and maximum revolutions up to 740 rev/min controlled by frequency converters and a single semi-Kaplan water power plant with 400 kW peak power at 1005 rev/min maximum generator speed. The measurements were performed before and after repairs of one of the ventilators in the ventilation system at 60% and 100% of maximal output power. The rotating magnetic fields of the fan electromotor stator, fan rotor revolutions, rotor slip frequency and ball-bearing frequencies were identified in frequency spectrums in the distance of 700 mm from fan electromotor axis in both cases. During the measurements on the semi-Kaplan turbine, the changes in states of mechanical and electrical components of the machine were monitored in the magnetic fields with increase of the power in the range of 0–95%, before and after phasing to the electrical grid. Standard processing methods, Discrete Fourier Transform, spectrograms and Discrete Wavelet Transform were used. In the spectrograms of the measured magnetic fields, the 1st–4th harmonics of the turbine shaft, generator shaft and also their side frequencies were identified. Significant changes of magnetic fields in time were identified in the area of 60–95% power. With the help of the Wavelet, transform intervals were identified where it is desirable to operate the turbine. The analyses of magnetic fields measurements performed on the power plant were compared with vibro-diagnostic principles.
Highlights
The methods used in evaluation of the recorded magnetic field data used windowing because the measurements were performed with dynamic changes/processes in the systems
The data were processed and visualized with scripts written in Python programming language with the help of Scipy and Matplotlib libraries; the Wavelet Transform was computed with the National Instruments LabView software
The results are accompanied with discussion of their representation and usability in diagnostics to improve the sustainability of systems
Summary
Sustainability 2021, 13, 9197 often contactless nowadays and utilizing different physical fields and the encing with the tested objects. The NDT methods are used in a broad area of appl from the construction engineering [1] up to the aerospace area [2,3]; the factors are the knowledge and technical equipment. The limiting factors magnetic fields, properties, and ongoing dynamic It can be sta are the knowledge and technical equipment. The use of the methods depends on the each object “transmits” signals carrying information about its state on development of materials, sensors, sensing principles, visualization and interpretation of face, and aboutand thevalues internal the measured quantities [4,5,6]. The NDT methods based magnetic allow us toaround identify information
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