Abstract
The railway occupies a fairly important position in transportation due to its high speed and strong transportation capability. As a consequence, it is a key issue to guarantee continuous running and transportation safety of trains. Meanwhile, time consumption of the diagnosis procedure is of extreme importance for the detecting system. However, most of the current adopted techniques in the wayside acoustic defective bearing detector system (ADBD) are offline strategies, which means that the signal is analyzed after the sampling process. This would result in unavoidable time latency. Besides, the acquired acoustic signal would be corrupted by the Doppler effect because of high relative speed between the train and the data acquisition system (DAS). Thus, it is difficult to effectively diagnose the bearing defects immediately. In this paper, a new strategy called online Doppler effect elimination (ODEE) is proposed to remove the Doppler distortion online by the introduced unequal interval sampling scheme. The steps of proposed strategy are as follows: The essential parameters are acquired in advance. Then, the introduced unequal time interval sampling strategy is used to restore the Doppler distortion signal, and the amplitude of the signal is demodulated as well. Thus, the restored Doppler-free signal is obtained online. The proposed ODEE method has been employed in simulation analysis. Ultimately, the ODEE method is implemented in the embedded system for fault diagnosis of the train bearing. The results are in good accordance with the bearing defects, which verifies the good performance of the proposed strategy.
Highlights
Due to rapid development of the national economy and society, requirement for transportation capability has been increased considerably
To accomplish the online Doppler effect elimination (ODEE) strategy, an embedded system composed by a self-designed embedded data acquisition system (SEDAS) and a digital signal processing (DSP) system is designed
The Doppler effect including the frequency shift, frequency band expansion and amplitude modulation can be eliminated real-time, and both the simulation study and the real train bearing fault diagnosis proved that a satisfactory performance is achieved by the proposed ODEE method in removing the Doppler effect of the acoustic signal and diagnosing the bearing fault type
Summary
Due to rapid development of the national economy and society, requirement for transportation capability has been increased considerably. A set of OTDS can only monitor one train, which makes the system uneconomic When it comes to the ADBD, the acoustic signal analysis method [17,18] is included in the system as this method can detect the incipient defect of the train bearing. Motivated by the above analysis, an online fault diagnosis strategy called online Doppler effect elimination (ODEE) based on acoustic signal analysis technique is proposed in this paper for the ADBD. The procedure of the proposed ODEE strategy can be achieved online, which means the time consumption is less than that of the traditional offline strategy Both simulation study and real train defective bearing signal process demonstrate that a remarkable performance is achieved by using the proposed ODEE method in the restoration of the Doppler distortion signal.
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