During the long-time working circle, the wheels will be damaged to a certain degree caused by the wearing, the impact, the loads, the climate and so on. In order to evaluate the health of the wheels and reduce the potential losses, many effective methods are used in railway health monitoring, such as laser method or ultrasonic method. But few of them can reach the demand of the real-time online detection, and integrate more comprehensive inspection function at the same time. A composite detection scheme for wheel-tread defects based on FBG sensing technique has been investigated in this paper. By collecting and analyzing the data from the sensors which are distributed on tracks and rails, we can precisely evaluate the Wheel-flats and also measure some other parameters used in rail health monitoring scheme such as speed, loads and axle counting measurement.