Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 Polish Maritime Research

2 2025

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Fault diagnosis based on improved information entropy and 1DCNN for marine turbocharger rotor with variable speed

Hu Lei, Hu Haoran, Hu Nao, Liu Luyuan, Dong Fei, Yang Jianguo, Zhong Jiahong

Polish Maritime Research

2025

nr 3

118--130

Due to the lack of a standardised method for determining representative locations for measuring points, it is difficult to select sensitive data on turbocharger rotor faults. In addition, the uncertainty in the feature parameters used for diagnosis under variable rotational speeds leads to low accuracy in fault identification. To address these issues, vibration signals from a turbocharger rotor under various conditions are obtained in this study via a fault simulation test, and a fault diagnosis method for rotor faults under variable speed conditions is proposed based on a sensitivity and multi-dimensional feature analysis of measurement points. The sensitivity of the improved and traditional information entropy is evaluated using a variance analysis across the measurement points, and the most effective vibration measurement points are selected based on the improved information entropy. The effective characteristic parameters of the vibration signals at multiple measurement points are analysed and extracted, and the numer of dimensions of the feature parameters is reduced using the t-distributed stochastic neighbour embedding (t-SNE) method. Faults in the turbocharger rotor at the different speeds are classified using a one-dimensional convolutional neural network (1DCNN), and the arithmetic ability of the diagnostic algorithm is evaluated. The results demonstrate that the proposed methods of selecting measurement points and fault diagnosis can effectively identify rotor faults at different degrees and various speeds: the accuracy of fault diagnosis is 99.85%, and the arithmetic ability is markedly enhanced compared with that of traditional methods.

A Knock Detection Method for a Marine Micro-Ignition Dual-Fuel Engine Based on Vibration Signals

Hu Nao, Zhao He, Yang Jianguo, Zheng Xianquan, Li Hongmei, Xie Liangtao, Liu Fuze, Chen Gang

Polish Maritime Research

2025

nr 1

111--120

A simple and unified index is proposed to achieve knock detection under various engine loads. Maximum amplitude vibration oscillation (MAVO) and maximum amplitude pressure oscillation (MAPO) were compared and were found to have no consistency. This means that MAVO cannot accurately reflect knocks inside the engine cylinder in the time domain. However, a knocking index built with MAVO can effectively detect engine knocking under various engine loads, which implies that some important information connected to the knock may be hidden within it. In this circumstance, a frequency domain analysis and a wavelet transform were conducted to study the energy changes of vibration signals during engine knocking. The energy proportion of the D1 frequency band during knocking increased drastically. Therefore, it was used to build a knocking judgment index, which builds the relationship between MAVO and MAPO. The judgment index has good applicability under different engine loads and a value greater than 0.5 can be used effectively for knock detection.