Abstract: The monitoring data acquisition of power switch mechanical characteristics faces challenges including inconsistent parameter systems, insufficient measurement accuracy, and severe signal interference. Based on mechanical kinematics theory and signal processing techniques, a hierarchical parameter classification framework was established, defining precision standards for core parameters such as opening/closing time and contact speed, with displacement measurement error controlled within ±0.12 mm and current sampling rate reaching 9.6 kHz. Multi-stage filtering and adaptive notch algorithms were employed to enhance the signal-to-noise ratio to 46 dB, while a secure data interaction system was constructed using TLS 1.3 protocol and RBAC model. Test results demonstrate that the standard deviation of opening time measurement was reduced to 0.38 ms, the diagnostic accuracy of buffer degradation reached 91%, and data storage timeliness met the 82 ms real-time requirement, providing standardized data support for power switch condition assessment.