Recognition of cylinder pressure based on LTSA-LSSVM
CHANG Chun1, MEI Jianmin1,ZHAO Huimin1,SHEN Hong1,LI Xiaohui2
1.Department of Military Vehicle Engineering, Army Military Transportation College, Tianjin 300161, China;
2.Fifth Team of Cadets, Army Military Transportation University, Tianjin 300161, China
Abstract:In order to improve the recognition accuracy of cylinder head vibration signal recovery cylinder pressure, a recognition method based on local tangent space arrangement (LTSA) and least squares support vector machine (LSSVM) is proposed. Firstly, the multi-dimensional features of the cylinder head vibration signals were extracted on time-domain, frequency-domain and wavelet packet energy-domain, and the dimension of feature set was reduced by LTSA method. Feature set reduced was used as the input of LSSVM model, and cylinder pressure was used as the output. Then a model for recognition of cylinder pressure was obtained by training the LSSVM model with plurality of samples. The results show that the cylinder pressure recognition method based on local tangent space arrangement and least squares support vector machine has the advantages of high precision and strong generalization ability.
常春1,梅检民1,赵慧敏1,沈虹1,李晓辉2. 基于局部切空间排列和最小二乘支持向量机的气缸压力识别[J]. 振动与冲击, 2020, 39(13): 16-21.
CHANG Chun1, MEI Jianmin1,ZHAO Huimin1,SHEN Hong1,LI Xiaohui2. Recognition of cylinder pressure based on LTSA-LSSVM. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(13): 16-21.
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