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.

This article presents diagnostic tests of wire ropes using passive magnetic methods. The study used two types of wire ropes with different constructions and diameters. Defects of various depths were modeled in the ropes, which reflected the degree of loss of metallic cross-section. After a series of measurements, a correlation was observed between the amplitude of the module signal and the degree of damage to the rope. The signals were recorded with the advantage of the SpinMeter-3D magnetometer. The obtained results were subjected to the extraction of features, the analysis of which allowed the damage to be identified.

Steel wire ropes used in transport and aerospace applications are critical components whose failure can lead to significant safety, operational, and environmental consequences. Current diagnostic practices based on magnetic rope testing (MRT) often suffer from signal misalignment and subjective interpretation, particularly under varying operational conditions or in polymer-impregnated ropes with delayed damage indicators. This study explores the application of the Dynamic Time Warping (DTW) algorithm to enhance the reliability of MRT diagnostics. The research involved analyzing long-term MRT recordings of wire ropes used in mining operations, including different scanning resolutions and signal acquisition methods. A mathematical formulation of DTW is provided along with its implementation code in R and Python. The DTW algorithm was applied to synchronize diagnostic signals with their baseline recordings, as recommended by ISO 4309:2017 and EN 12927:2019 standards. Results show that DTW enables robust alignment of time series with slowly varying spectra, thereby improving the comparability and interpretation of MRT data. This approach reduces the risk of unnecessary rope discard and increases the effectiveness of degradation monitoring. The findings suggest that integrating DTW into existing diagnostic protocols can contribute to safer operation, lower maintenance costs, and reduced environmental impact.

Steel wire rope is essential to many rope transport devices. As steel ropes are used, they become damaged, the identification of which is often very difficult or time-consuming. The criteria for retiring steel wire ropes are rigorous—sometimes, ropes that remain fit for further operation are replaced. This article aims to define a novel method of identifying the condition of steel ropes based on their residual magnetic field measurements and their potential use in other industries in the event of damage. This article presents a methodology for detecting discontinuities in steel ropes, which allows for determination of their suitability for further operation. The work uses a rope as a load-bearing element of a personal lift. The initial signal was recorded with a SpinMeter-3D magnetometer. The obtained results were subjected to the extraction of features, the analysis of which allowed identifying the damage. The obtained results enable us to conclude that this procedure is crucial in the context of sustainable development.

This study explores the potential application of the wavelet analysis to the assessment of the working condition of compact ropes (qualitative assessment). The assessment procedure is a key aspect in the decision- making during the non-destructive testing. This is the first study on diagnostics of the new-design ropes, summarising the results of the analysis of signals from novel compact ropes, based on the defect models. Selection of the wavelet type and of the decomposition detail is a key element of the diagnostic procedure. A major step in the assessment procedure involves the replicas of the rope’s surface. The data provided in this paper will be useful in developing new specialist equipment for magnetic inspection of compact ropes.

The early identification of micro-defects in ferromagnetic elements such as steel wire ropes significantly impacts structures’ in-service reliability and safety. This work investigated the possibility of detecting mechanically introduced discontinuities using different magnetic sensors without magnetization of the tested object with a strong external field. This is called the passive magnetic testing method, and it is becoming increasingly popular. This research used differential sensors (measuring differences in field values at the nanotesla level) and absolute sensors (enabling the measurement of the magnetic field vector module or its components at the microtesla level). Each measurement result obtained from the sensors allowed for detecting discontinuities in the line. The problem to be solved is the quantitative identification of changes in the metallic cross-section of a rope.