首页|基于DPCA的涡旋压缩机主轴故障信号调制特性研究

基于DPCA的涡旋压缩机主轴故障信号调制特性研究

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为了揭示涡旋压缩机的振动和噪声的机制与调制特性,通过搭建实验平台,模拟主轴磨损故障。利用信号解调方法对振动及噪声信号特性进行讨论,探究此类故障对涡旋压缩机的影响。通过与循环平稳分析方法对比,验证了基于时频分析与主成分分析(DPCA)的信号解调方法处理涡旋压缩机信号的优越性。利用DPCA方法提取涡旋压缩机的信号调制特征,讨论了不同工况下的信号特性及产生机制。结果表明:周期性变化的电磁力与压力增强了主成分中调制频率的幅值,x和y方向的振动对噪声的变化起主导作用。
Research on Spindle Fault Signal Modulation Characteristics of the Scroll Compressor Based on DPCA
In order to reveal the mechanism and modulation characteristics of vibration and noise in scroll compressors,an experi-mental platform was established to simulate spindle wear faults.The signal demodulation methods were used to discuss the characteristics of vibration and noise signals,and the impact of such faults on scroll compressors were explored.By comparing with the cyclostationary analysis method,the superiority of the signal demodulation method based on time-frequency analysis and principal component analysis(DPCA)in processing scroll compressor signals was verified.Through the DPCA method,the signal modulation feature of the scroll compressor was extracted.The signal characteristics and generation mechanism under different operating conditions were discussed.The result shows that the amplitude of the modulation frequency in the principal component is enhanced by the periodically changing electro-magnetic force and pressure.The vibration in the x and y directions plays a leading role in the change of noise.

scroll compressorsignal demodulationfault diagnosis

马桤政、张彤赫、宋永兴、于跃平、李奉誉

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山东建筑大学热能工程学院,山东济南 250101

压缩机技术国家重点实验室(压缩机技术安徽省实验室),安徽合肥 230031

涡旋压缩机 信号解调 故障诊断

压缩机技术国家重点实验室(压缩机技术安徽省实验室)开放基金项目

SKL-YSJ202108

2024

机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
年,卷(期):2024.52(10)