- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Railway wheelsets consist of three main components; the wheel, axle and axle bearing. Faults can develop on any of the aforementioned components, but the most common are related to wheel and axle bearing damages. The continuous increase in train operating speeds means that failure of an axle bearing can lead to very serious derailments, potentially causing human casualties, severe disruption in the operation of the network, damage to the tracks, unnecessary costs, and loss of confidence in rail transport by the general public. The rail industry has focused on the improvement of maintenance and online condition monitoring of rolling stock to reduce the probability of failure as much as possible. This paper discusses the results of onboard acoustic emission measurements carried out on freight wagons with artificially damaged axle bearings in Long Marston, UK. Acoustic emission signal envelope analysis has been applied as a means of effective tool to detect and evaluate the damage in the bearings considered in this study. From the results obtained it is safe to conclude that acoustic emission signal envelope analysis has the capability of detecting and evaluating faulty axle bearings along with their characteristic defect frequencies in the real-world conditions.
A number of laboratory and field tests were carried out to establish a simple and effective approach in detecting faulty axle bearings using a customised onboard AE condition monitoring system. Defective axle bearings increase the amplitude of the peaks in the power spectrum after FFT is carried out which indicates the presence of the defect. Using envelope analysis it is possible to establish the type of defect by finding the characteristic frequencies and their harmonics provided that the kinematics of the bearing are known. The set of the laboratory tests carried out on the customised test rig developed at the University of Birmingham show effectively that the AE technique can be used together with envelope signal analysis to successfully distinguish between the defect-free and defective sample bearings considered herewith by establishing the characteristic frequencies. The same has been proven to be possible to achieve under field operational conditions as shown in the results obtained from the tests carried out at the Long Marston test track. It is shown that in the case of the mildly damaged bearing, due to the low signal to noise ratio, AE is only able to detect the existence of the defect and in slightly severe damage it can also identify the fault.