Reliable wireless communication is a key requirement for railway axle-box condition monitoring, particularly in electromagnetically harsh environments where electromagnetic interference (EMI) may degrade diagnostic data transmission. This study proposes an Electromagnetic Compatibility Design Framework (EMCDF) for receiver-oriented assessment of electromagnetic exposure, equivalent EMC mitigation, and wireless-link performance. The framework integrates frequency-domain electromagnetic characterization with analytical radio-link, receiver-noise, residual-interference, and communication-performance models, establishing a physically traceable pathway from prescribed electromagnetic exposure to residual receiver-level interference and the resulting communication degradation. Prescribed in-band EMI scenarios and equivalent EMC-mitigation conditions are evaluated using the signal-to-interference-plus-noise ratio (SINR), theoretical channel capacity, and two proposed normalized electromagnetic robustness metrics based on SINR and theoretical capacity. Under the prescribed analytical scenarios, equivalent in-band EMC attenuation values of 15–20 dB correspond to interference-power reduction factors of approximately 31.6–100. For the adopted 433 MHz radio-link parameters, the model-derived SINR under the severe-EMI scenario decreases from approximately 37.83 dB at 1 km to 17.83 dB at 10 km, while the capacity-based robustness coefficient decreases from approximately 0.474 to 0.299 over the same distance range. The model-based results show that propagation loss and residual EMI influence receiver-level communication performance through physically distinct mechanisms and can therefore be evaluated separately within the proposed framework. The quantitative results represent comparative model-derived estimates rather than experimental validation over the investigated distance range. The proposed EMCDF provides a receiver-oriented analytical methodology for EMC-aware assessment and comparative evaluation of wireless railway condition-monitoring systems.
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Irgashev et al. (2026) studied this question.
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