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With the development of modern railway transportation, the diagnosis of train bearing defects plays a significant role to maintain the safety of it and the higher speed, the more reliable detection we need. Among various defect detection techniques, acoustic diagnosis is widely used for detecting incipient defects of a train bearing as well as being suitable for wayside monitoring. But as we know, the acoustic signal we acquire from wayside is corrupted by the Doppler Effect and surrounding heavy noise including the noise of train body vibration, the noise of wheels, aerodynamic noise, etc. Besides, as the signal acts as a mixture of many bearings of the train, if we want to get the feature of one of them, we also need to have method to separate the signal. These are all quite difficult works. This paper will show us a new way to identify the conditions of bearings from a running machine. In this paper, we mainly describe the design of a software framework based on C# and the whole data transportation system. Ubiquitous computing technologies offer excitingly new possibilities for monitoring and analyzing of the train bearing conditions in real time. In our system, we put forward a whole serial port communication protocol which insures the data’s accuracy during the wireless transmission process. We also get a thorough logic between the PC and wireless-terminals. In the software, we make it possible for engineers to monitor the bearings’ condition in real time, check the parameters calculated from original data to identify the fault and set the communication parameters. Above all, the signals we acquire here are the vibration signal collected from the train bearings directly. It will make up most of the shortcomings compared to the acoustic diagnosis.

A Data-Collection and Fault Diagnosis System of Train Bearing Based on the C# and Multi-Wireless-Terminal