Dynamic Responses of a Metro TrainBridge System under TrainBraking: Field Measurements and Data Analysis This paper focuses on the dynamic responses of a metro trainxe2x80x93bridge system under trainbraking. Experiments were performed on the elevated Metro Line 21 of Guangzhou (China). A continuous, threespan, rigidframe bridge (42 m  65 m  42 m) and a standard Btype metro train were selected. The acceleration signals were measured at the centerpoints of the main span and one sidespan, and the acceleration signals of the car body and the bogie frame were measured simultaneously. The trainxe2x80x93bridge systemxe2x80x99s vibration characteristics and any correlations with time and frequency were investigated. The Choixe2x80x93Williams distribution method and wavelet coherence were introduced to analyze the obtained acceleration signals of the metro trainxe2x80x93bridge system. The results showed that the Choixe2x80x93Williams distribution provided a more explicit understanding of the timexe2x80x93frequency domain. The correlations between different parts of the bridge and the trainxe2x80x93bridge system under braking conditions were revealed. The present study provides a series of measured dynamic responses of the metro trainxe2x80x93bridge system under trainbraking, which could be used as a reference in further investigations.

DataDriven Bias Correction and Defect Diagnosis Model for InService Vehicle Acceleration Measurements Track quality instruments use lowcost accelerometers placed on or attached to the floors of operating trains, and these instruments collect substantial amounts of data over short inspection periods. The measurements collected by the instruments are the main data source for track irregularity evaluation. However, considerable measurement bias exists in the vertical and lateral vibration data obtained from such instruments. False positive track vibration defects detected by track quality instruments occur frequently. This results in considerable time and effort being expended needlessly because maintenance workers have to visit the railway track sites to check and review the track vibration defects. Therefore, we propose a model for datadriven bias correction and defect diagnosis for inservice vehicle acceleration measurements based on track degradation characteristics. Substantial amounts of historical track measurement data from different inspection methods were mined extensively to eliminate the false positive detection of track vibration defects and diagnose the causes of track vibration defects. Actual measurement data from the Lanxin Railway were used to validate our proposed model. The success rate achieved in identifying false positive track vibration defects was 84.1%, and that in track vibration defect diagnosis was 75.8%. These high success rates suggest that the proposed model can be of practical use in improving railway track maintenance management.