[1]Chen Hua, Zhang Qing, Xu Guanghua,et al. Performance Reliability Estimation Method Based on Adaptive Failure Threshold[J]. Mechanical Systems and Signal Processing, 2013, 36(2): 505-519.
[2]杨帆,汤宝平,尹爱军. 小波包能谱构建综合评估函数的轴承退化评估[J]. 中国机械工程,2015,26(17): 2355-2368.
Yang Fan, Tang Baoping, Yin Aijun.Early Performance Degradation Assessment of Rolling Bearing Based on Comprehensive Evaluation Function Constructing Wavelet Packet Energy Spectrum[J]. China Mechanical Engineering, 2015,26(17): 2355-2368.
[3]Tan Xiaohui, Bi Weihua, Hou Xiaoliang, et al. Reliability Analysis Using Radial Basis Function Networks and Support Vector Machines[J]. Computers and Geotechnics, 2011, 38(2):178-186.
[4]王冰, 李洪儒, 许葆华. 基于多尺度形态分解谱嫡的电机轴承预测特征提取及退化状态评估[J]. 振动与冲击, 2013, 32(22):124-128.
Wang Bing, Li Hongru, Xu Baohua. Motor Bearing Forecast Feature Extracting and Degradation Status Identification Based on Multi-scale Morphological Decomposition Spectral Entropy[J]. Journal of Vibration and Shock, 2013, 32(22):124-128.
[5]申中杰, 陈雪峰, 何正嘉, 等. 基于相对特征和多变量支持向量机的滚动轴承剩余寿命预测[J]. 机械工程学报, 2013,49(2) :183-189.
Shen Zhongjie, Chen Xuefeng, He Zhengjia, et al. Remaining Life Predictions of Rolling Bearing Based on Relative Features and Multivariable Support Vector Machine[J]. Journal of Mechanical Engineering, 2013,49(2) :183-189.
[6]霍军周,王亚杰,欧阳湘宇,等.基于BP神经网络的TBM主轴承载荷谱预测[J].哈尔滨工程大学学报,2015,36(7):1-6.
Huo Junzhou, Wang Yajie, Ouyang Xiangyu, et al. Load Spectrum Prediction Based on BP Neural Network of Main Drive Bearing of Tunnel Boring Machine[J]. Journal of Harbin Engineering University, 2015, 36(7):1-6.
[7]徐东, 徐永成, 陈循, 等. 基于EMD的灰色模型的疲劳剩余寿命预测方法研究[J]. 振动工程学报, 2011,24(1) :104-110.
Xu Dong, Xu Yongcheng, Chen Xun, et al. Residual Fatigue Life Prediction Based on Grey Model and EMD[J]. Journal of Vibration Engineering, 2011, 24(1):104-110.
[8]Chen Fafa, Tang Baoping, Chen Runxiang. A Novel Fault Diagnosis Model for Gearbox Based on Wavelet Support Vector Machine with Immune Genetic Algorithm[J]. Measurement, 2013, 46: 220-232.
[9]Duygu C, Esin D. An Automatic Diabetes Diagnosis System Based on LDA-wavelet Support Vector Machine Classifier [J]. Expert Systems with Applications, 2011, 38(7): 8311-8315.
[10]Li Cong, Duan Haibin. Information Granulation-based Fuzzy RBFNN for Image Fusion Based on Chaotic Brain Storm Optimization[J]. Optik, 2015, 126:1400-1406.
[11]Lin Yaojin, Li Jinjin, Lin Peirong, et al. Feature Selection Via Neighborhood Multi-granulation Fusion[J]. Knowledge-based Systems, 2014, 67(5):162-168.
[12]Wang Weina, Witold P, Liu Xiaodong. Time Series Long-term Forecasting Model Based on Information Granules and Fuzzy Clustering[J]. Engineering Applications of Artificial Intelligence, 2015, 41(5):17-24.
[13]Wu Qi. The Forecasting Model Based on Wavelet V-support Vector Machine[J]. Expert Systems with Applications, 2009, 36(4):604-7610.
[14]Chen Fafa, Tang Baoping, Song Tao. Multi-fault Diagnosis Study on Roller Bearing Based on Multi-kernel Support Vector Machine with Chaotic Particle Swarm Optimization[J]. Measurement, 2014, 47(1): 576-590.
[15]Zhu Keheng, Song Xigeng, Xue Dongxin. A Roller Bearing Fault Diagnosis Method Based on Hierarchical Entropy and Support Vector Machine with Particle Swarm Optimization Algorithm [J]. Measurement, 2014, 47(1): 669-675.
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