基于振动分析的液驱往复式氢气压缩机压缩周期参数非直接测量方法

Indirect Measurement Method of Compression Cycle Parameters of Liquid-driven Reciprocating Hydrogen Compressor Based on Vibration Analysis

针对氢气压缩机的振动信号成分相对复杂、易受噪声干扰以及压缩周期难以自动提取的问题,本文提出了基于变分时域分解、Hilbert变换和自相关函数相结合的液驱往复式氢气压缩机的压缩周期参数非直接测量方法。首先建立了液驱往复式压缩机活塞冲击仿真信号的数学模型,模拟活塞撞击气缸左、右极限位置时的振动信号,利用变分时域分解算法将模拟的活塞冲击信号从整个仿真信号中分离出来,然后利用Hilbert变换对分离的活塞冲击仿真信号进行包络解调并绘制包络谱,对包络谱的幅值序列进行自相关运算,最后自动检索自相关函数曲线最大峰值对应的延迟点数,计算压缩周期参数值。仿真信号分析结果表明:该方法可以自动提取获得正确的压缩周期参数值,当冲击信号受噪声影响时仍然具有高鲁棒性,其对9种不同信噪比仿真信号的提取成功率为88.89%。最后,将该方法应用到真实的液驱往复式氢气压缩机上,分别采集了不同电机转频、进气压力和二级排气压力共12种稳态运行工况下的排气阀振动信号。实验台数据分析结果表明,该方法提取的成功率为100%,与频谱、倒频谱、包络谱以及自相关函数的结果对比表明,该方法在所有5种方法中的提取成功率最高,进而验证了本文所提方法的有效性和优越性,为氢气压缩机状态监测、故障诊断与寿命预测提供了基础运行工况参数。

Objective This study aims to address significant challenges associated with the complex vibration signals in hydrogen compressors,which are susceptible to noise interference.This interference complicates the extraction of accurate compression cycle parameters.It develops and validates a novel non-direct measurement method that enhances the reliability and efficiency of parameter extraction in liquid-driven reciprocating hydrogen compressors,which are crucial for operational efficiency and diagnostic accuracy in hydrogen fuel systems.Methods The proposed method integrates Variational Time-Domain Decomposition(VTDD),Hilbert transform,and autocorrelation functions to enhance signal analysis and parameter extraction in noisy environments.The approach commences with developing an elaborate mathematical model that simulates dynamic interactions within the compressor,specifically focusing on piston impacts at cylinder limit positions.This simulation is pivotal for determining the intrinsic mechanical behaviors characteristic of the compression cycle.The model facilitates the extraction of clean piston impact signals from a noisy background using the VTDD algorithm,isolating pure signal components essential for subsequent analyses.The next step involves applying the Hilbert transformation to these isolated signals for envelope demodulation,enhancing signal clarity by amplifying its amplitude modulations,which are pivotal for accurately identifying cycle parameters.The amplitude sequences derived from the envelope are then examined using autocorrelation functions.This assists in precisely identifying piston impact periodicity and enables the accurate calculation of compression cycle parameters.Results and Discussions The effectiveness of the proposed method is rigorously validated through simulations and real-world applications in a liquid-driven reciprocating hydrogen compressor under various operational conditions.The method in simulation tests demonstrated an 88.89%success rate in precisely extracting compression cycle parameters across nine different signal-to-noise ratios,exemplifying its robustness against environmental noise and precision in signal analysis.In practical applications on actual compressor setups,the method achieves a 100%success rate in parameter extraction,confirming its effectiveness and reliability.In addition,a comparative analysis with traditional methods such as spectral,cepstral,envelope spectra,and autocorrelation indicated that the novel method surpasses these conventional techniques in terms of extraction success rates and computational efficiency,establishing it as a superior choice for real-time monitoring and diagnostics in critical hydrogen energy applications.Conclusions This study successfully develops and validates a non-direct measurement method that significantly enhances the process of extracting compression cycle parameters in hydrogen compressors.The method provides a comprehensive and effective solution for monitoring the operational status of hydrogen compressors,which is vital for ensuring system reliability and safety by integrating VTDD,Hilbert transform,and autocorrelation functions.The high accuracy and robustness of the method under diverse operational conditions underscore its applicability across different sectors within the hydrogen energy industry,offering a dependable tool for proactive maintenance and efficient operation of energy systems.Finally,this advancement promotes the broader adoption and optimization of hydrogen technologies,contributing to sustainable energy solutions and the advancement of green technology initiatives.