关键词: 道路载荷谱采集；采样频率；高通滤波；物理规则校验

Abstract: The quality of road load spectrum data is crucial for vehicle reliability research and development. This paper systematically expounds core processing methods based on engineering practice, typical working conditions are screened through multi-dimensional user surveys (driving routes, load, failure modes, etc.) and big data technology to determine acquisition routes. Measurement points are selected by balancing sensitivity and economy, covering key positions such as wheels, frames, and cabs to collect multi-type load signals. Sampling frequency setting is optimized based on the Nyquist sampling theorem and engineering experience, with anti-aliasing filters configured and signal integrity verified. In the preprocessing stage, data is purified through high-pass filtering (zero drift correction), shear replacement (spike correction), and physical rule verification (multi-signal correlation validation) to ensure signal consistency and usability. This study provides a replicable solution for load spectrum acquisition under complex working operating conditions, contributing to improve data reliability and vehicle research and development efficiency.

Key words: road load spectrum acquisition; sampling frequency; high pass filtering; physical rule verification