Two-stroke, low-speed diesel engines are widely used in large ships due to their good performance and fuel economy. However, there have been few studies of the effects of lubricating oils on the vibration of two-stroke, low-speed diesel engines. In this work, the effects of three different lubricating oils on the vibration characteristics of a low-speed engine are investigated, using the frequency domain, time-frequency domain, fast Fourier transform (FFT) and short-time Fourier transform (STFT) methods. The results show that non-invasive condition monitoring of the wear to a cylinder liner in a low-speed marine engine can be successfully achieved based on vibration signals. Both the FFT and STFT methods are capable of capturing information about combustion in the cylinder online in real time, and the STFT method also provides the ability to visualise the results with more comprehensive information. From the online condition monitoring of vibration signals, cylinder lubricants with medium viscosity and medium alkali content are found to have the best wear protection properties. This result is consistent with those of an elemental analysis of cylinder lubrication properties and an analysis of the data measured from a piston lifted from the cylinder after 300 h of engine operation.
W pracy przedstawiono bezstykową metodę pomiaru drgań transformatora w stanie ustalonym. Standardowe podejście do tego zagadnienia opiera się na analizie widma amplitudowego wibracji zarejestrowanych przy pomocy akcelerometru przytwierdzonego do kadzi transformatora. Proponowana nowa metoda pomiaru polega na wykorzystaniu zamiast akcelerometru – matrycy czterech mikrofonów.
EN
The paper presents a non – contact method for vibroacoustic measurements of a transformer in a steady – state. The standard approach to this issue is based on analysis of the vibration frequency spectrum recorded with an accelerometer attached to the transformer tank. The proposed new method consists in using a microphone array (soundfield microphone) instead of the accelerometer. The soundfield microphone comprises four capsules having cardioid response characteristics. An example of such a microphone (TetraMic Single Point Surround Sound Microphone) is shown in Fig. 2a. The microphone capsules are mounted in configuration resembling walls of a regular tetrahedron oriented as in Fig. 2b. Fig. 3 presents mutual location of directivity patterns of the capsules. A linear combination of signals (B - format) from these capsules enables determining the acoustic signal emitted by a sound source (5). At the same time the background noise is strongly attenuated. The soundfield microphone produces effects similar to the accelerometer.
3
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Characteristic parameters of blasting vibration (BVCP) have great effects on its damage level. The prediction of BVCP is helpful to study blasting vibration effect. In this paper, an attempt has been made to predict blast-induced ground vibration using support vector machine (SVM) to avoid the limitation of the prediction with only one index and to improve the prediction precision. A Grid search method-based SVM prediction model for BVCP was established on the basis of nonlinear model-based SVM. To construct the model, nine factors affecting blasting vibration characteristic variables are taken as input parameters, whereas, peak particle velocity (PPV), dominant frequency (Df) and its time duration (Dt) are considered as output parameters. A database consisting of 108 datasets was collected from Tonglvshan copper mine in China. From the prepared database, 93 datasets were used for the training of the model, whereas 15 randomly selected datasets were used for the validation of the SVM model. To compare the performance of the developed SVM model with that of artificial neural network (ANN) model, the same database was applied. Superiority of the proposed SVM model over ANN model was examined by calculated coefficient of determination for predicted and measured values of PPV, Df and Dt. Concluded remark is that the prediction’s BVCP can reliably be estimated from the indirect methods using SVM analysis.
PL
Przy przewidywaniu efektów i szkód wibracji wybuchowych ważny jest parametr BVCP – blasting vibration characteristic parameter. W artykule przedstawiono model matematyczny do prognozowania efektów drgań wybuchowych z wykorzystaniem metody SVM.
W pracy przedstawiono metodę analizy drgań wibroakustycznych transformatora w stanie ustalonym. Standardowe podejście do tego zagadnienia opiera się na analizowaniu widma częstotliwości wibracji rejestrowanego przy pomocy akcelerometru przytwierdzonego do kadzi transformatora. W celu poprawienia czytelności wyników pomiarów wibroakustycznych w artykule proponuje się metodę analizy względnego współczynnika zawartości częstotliwości harmonicznych h norm(f). Jak stwierdzono, na bazie przeprowadzonego eksperymentu, duże wartości hnorm w szerokim zakresie częstotliwości świadczą o odkształceniu uzwojeń i degradacji izolacji stałej.
EN
The paper presents a method for vibroacoustic analysis of a transformer in the steady-state. The standard approach to this problem is based on analysis of the vibration frequency spectrum recorded with an accelerometer attached to the transformer tank. Four transformers (A, B, C and D) were tested with this method. The recorded vibration spectra are shown in Fig. 1. The analysis of the presented data may be ambi-guous, as there are not many differences in vibration spectra of the tested transformers. There are significant changes in some harmonic frequencies, but it is difficult to state whether the mechanical construction condition of e.g. transformer A varies from that of C (Fig. 1). To improve legibility of measurement results the paper suggests (in Section 3) the analysis method for the relative coefficient of harmonic frequency contents hnorm(f). On the basis of experiments (Figs. 2 and 3) one can state that high values of hnorm within the wide frequency range mean that windings are deformed and solid insulation is degraded.
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