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基于高分辨率谱估计的早期转子断条故障诊断
Alternative TitleHigh-resolution spectral analysis for incipient broken rotor bar diagnosis
贾朱植; 杨理践; 祝洪宇; 张吉龙
Department数字工厂研究室
Source Publication仪器仪表学报
ISSN0254-3087
2017
Volume38Issue:2Pages:279-287
Indexed ByEI ; CSCD
EI Accession number20172103692983
CSCD IDCSCD:5939115
Contribution Rank4
Funding Organization中国科学院重点部署项目(KGZD-EW-302) ; 辽宁省科学技术计划(2015020140)项目资助
Keyword鼠笼电机 Hilbert变换 小波变换 扩展prony算法 故障诊断
Abstract以快速傅里叶变换(FFT)为基础的电机电流信号特征分析(MCSA)具有频率分辨率低的固有缺陷,从而严重影响了鼠笼电机早期转子断条故障的诊断性能。为解决这一问题,提出基于高分辨率谱估计的早期转子断条故障诊断方法。首先利用Hilbert变换和离散小波变换对单相定子电流信号预处理,然后采用扩展Prony算法对预处理后的信号进行定性/定量分析。运用该方法对不同故障严重程度、不同负载条件下的3 k W电机稳态定子电流信号进行分析,并与FFT分析结果做对比。实验结果表明,即使在短时数据条件下所提方法仍然能够准确诊断出早期转子断条故障,验证了该方法的有效性和优越性。
Other AbstractMotor current signal analysis (MCSA) based on fast Fourier transform (FFT) has its inherent drawback such as low resolution in frequency domain,thus,the detection performance becomes inaccurate for incipient broken rotor bar in squirrel-cage induction motor. In this paper,a high-resolution spectral analysis method is proposed to solve this issue. Firstly,data pre-processing for single phase stator current is achieved by Hilbert transform and discrete wavelet transform (DWT). Then,extended Prony algorithm is utilized for pre-processed signal qualitative and quantitative analysis. The steady-state stator current of 3kw squirrel-cage induction motor can be analyzed under different fault degrees and different operating conditions. The comparison is conducted with FFT. The experimental results shows the effectiveness and superiority on incipient broken rotor bar fault diagnosis even for short-time data sequence.
Language中文
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20360
Collection数字工厂研究室
Corresponding Author贾朱植
Affiliation1.沈阳工业大学信息科学与工程学院
2.辽宁科技大学应用技术学院
3.辽宁科技大学电子与信息工程学院
4.中国科学院沈阳自动化研究所
Recommended Citation
GB/T 7714
贾朱植,杨理践,祝洪宇,等. 基于高分辨率谱估计的早期转子断条故障诊断[J]. 仪器仪表学报,2017,38(2):279-287.
APA 贾朱植,杨理践,祝洪宇,&张吉龙.(2017).基于高分辨率谱估计的早期转子断条故障诊断.仪器仪表学报,38(2),279-287.
MLA 贾朱植,et al."基于高分辨率谱估计的早期转子断条故障诊断".仪器仪表学报 38.2(2017):279-287.
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