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| Angular domain intensity feature extraction method for fault vibration signals of hydraulic pump under variable rotating speed condition |
| LIU Siyuan1,2,3, WANG Zhiwei1,2, JIANG Wanlu1,2, LI Xiaoming4, LU Mingli3, LU Zhengdian3 |
1.Hebei Provincial Key Lab of Heavy Machinery Fluid Power Transmission and Control, Yanshan University, Qinhuangdao 066004, China;
2.MOE Key Lab of Advanced Forging & Stamping Technology and Science, Yanshan University, Qinhuangdao 066004, China;
3.Jiangsu Tianming Machinery Co., Ltd., Lianyungang 222300, China;
4.China Railway Construction Heavy Industry Group Co., Ltd.， Changsha 221116, China |
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Abstract Extracting feature information sensitive to faults is the key to improve the correctness of hydraulic pump condition assessment, due to severe lack of sensitive feature information of hydraulic pump faults under variable rotating speed condition, the assessment correctness rate is much low. Here, a new concept of angular domain intensity feature and a new feature extraction method for hydraulic pump slipper wear faults were proposed. Non-stationary vibration signals in time domain were converted into stationary ones in angular domain with the order analysis method. According to the definition of vibration intensity and the calculation method in frequency domain, unilateral amplitude value spectra and harmonic frequencies of stationary vibration signals in angular domain were obtained, and then calculation formulas of angular domain intensity feature factors for three vibration signals including displacement, velocity and acceleration were derived. Taking inner edge wear fault of hydraulic pump slipper as an example, the angular domain intensity feature factor of fault vibration signals was extracted under variable rotating speed condition. Qualitative and quantitative contrastive analyses were performed for this feature factor and the order energy one. It was shown that the angular domain intensity feature factor is more sensitive to deterioration development of hydraulic pump slipper wear fault.
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Received: 12 February 2019
Published: 28 August 2020
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