Featured Application This study contributes to the timely detection of track defects, helping to prevent safety incidents during train operations. Abstract Railway turnout is a critical railway infrastructure that guides trains in switching tracks. Over time, uneven rail wear can lead to switch rail reduction value (SRRV) deviation, a typical structural defect that compromises turnout functionality and jeopardizes train operation safety. Current SRRV deviation detection methods rely primarily on inefficient manual inspections, making it difficult to ensure operational safety. To address this issue, the study carried out a comprehensive investigation combining numerical and experimental analyses. First, a rigid–flexible coupled dynamics model of a vehicle-turnout system was developed to analyze the wheel–rail dynamic interaction forces and contact relationships under various SRRV deviation conditions. The results revealed that SRRV deviation significantly affects both wheel–rail interaction forces and the turnout structural irregularity wavelength. Thus, based on discrete wavelet transform (DWT), a wheel–rail force trend component was derived that can effectively analyze the turnout structural irregular wavelength, and the mapping relationship between SRRV deviation and the wheel–rail force trend component was then established. Finally, an efficient and accurate method for identifying SRRV deviation based on wheel–rail force trend component was proposed and validated using field-measured data from trains passing through turnouts. This study contributes to the timely detection of track defects, helping to prevent safety incidents during train operations. Keywords: turnout; switch rail reduction value; vehicle-turnout coupled dynamics model; wheel–rail force trend component; discrete wavelet transform