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第6期 崔铁军,等:线性熵的系统故障嫡模型及其时变研究 ·1141· fault diagnosis method for train axle box bearing based on [13]KUMAR A,GANDHI C P,ZHOU Yuqing,et al.Fault modified multiscale permutation entropy[J].Journal of diagnosis of rolling element bearing based on symmet- the China railway society,2020,42(1):33-39 ric cross entropy of neutrosophic sets[J].Measurement, [6]张龙,吴荣真,雷兵,等.基于多尺度嫡的滚动轴承故障 2020,152:107318. 可拓智能识别[J】.噪声与振动控制,2019,39(6): [14]MINHAS A S.SINGH G.SINGH J.et al.A novel meth- 200-205. od to classify bearing faults by integrating standard devi- ZHANG Long,WU Rongzhen,LEI Bing,et al.Extens- ation to refined composite multi-scale fuzzy entropy[J]. ible intelligent identification for rolling bearing faults us- Measurement,.2020,154:107441. ing multiscale entropy[J].Noise and vibration control, [15]TRUONG M T N,KIM S.Automatic image threshold- 2019,39(6):200-205. ing using Otsu's method and entropy weighting scheme [7]张雅丽,刘永姜,张航,等.基于ITD信息嫡与PNN的 for surface defect detection[J].Soft computing,2018, 轴承故障诊断.煤矿机械,2019,40(12):167-169. 22(13):4197-4203 ZHANG Yali,LIU Yongjiang,ZHANG Hang,et al. [16]MINHAS A S,SINGH S,MALHOTRA J,et al.Ma- Bearing fault diagnosis based on ITD information en- chine deterioration identification for multiple nature of tropy and PNN[J].Coal mine machinery,2019,40(12): faults based on autoregressive-approximate entropy ap- 167-169 proach[J].Life cycle reliability and safety engineering. [8]赵书涛,李云鹏,王二旭,等.基于电一振信号嫡权特征 2018,7(3):185-192 的断路器储能机构故障诊断方法).高压电器,2019, [17刀刘天寿,匡海波,刘家国,等.区间数嫡权TOPSIS的港 55(11):204-210 口安全管理成熟度评价[】.哈尔滨工程大学学报, ZHAO Shutao,LI Yunpeng,WANG Erxu,et al.Fault 2019,40(5):1024-1030. diagnosis method of circuit breaker energy storage mech- LIU Tianshou,KUANG Haibo,LIU Jiaguo,et al.Evalu- anism based on electro-vibration signal entropy weight ation on maturity of port safety management based on feature[J].High voltage apparatus,2019,55(11): interval entropy weight TOPSIS[J].Journal of Harbin 204-210. Engineering University,2019,40(5):1024-1030. [9]张国辉,冯俊栋,徐丙立,等.基于故障特征信息量的诊 [18]杜鑫,邱庆刚,丁雅倩,等.超临界水冷堆子通道中嫡 断策略优化仿真研究).计算机仿真,2019,36(11): 产行为数值研究[.哈尔滨工程大学学报,2018, 317-321. 398):1290-1295. ZHANG Guohui,FENG Jundong,XU Bingli,et al.Re- DU Xin,QIU Qinggang,DING Yaqian,et al.Numeric- search on DMFT test method based on hybrid diagnostic al research on entropy generation in a sub-channel of model[J].Computer simulation,2019,36(11):317-321. SCWR[J].Journal of Harbin Engineering University, [10]戴邵武,陈强强,戴洪德,等.基于平滑先验分析和模 2018.398):1290-1295. 糊嫡的滚动轴承故障诊断几.航空动力学报,2019, [19列赵宏伟,王也然,刘萍萍,等.利用位置信息熵改进 3410:2218-2226. VLAD的图像检索方法[].哈尔滨工程大学学报 DAI Shaowu,CHEN Qiangqiang,DAI Hongde,et al. 2018,398):1376-1381 Rolling bearing fault diagnosis based on smoothness pri- ZHAO Hongwei,WANG Yeran,LIU Pingping,et al. ors approach and fuzzy entropy[J].Journal of aerospace Improved VLAD using location information entropy in power,.2019,3410):2218-2226. image retrieval[J].Journal of Harbin Engineering Uni- [11]王志,李有儒,田品,等.基于EMD模糊熵与会诊决策 versity,2018,39(8):1376-1381. 融合模型的中介轴承故障诊断技术.航空发动机, [20]崔铁军,马云东.基于多维空间事故树的维持系统可 2019,45(5):76-81 靠性方法研究[.系统科学与数学,2014,34(6): WANG Zhi,LI Youru,TIAN Jing,et al.Fault diagnosis 682-692. technology of inter-shaft bearing based on EMD fuzzy CUI Tiejun,MA Yundong.Research on the mainten- entropy and consultative decision fusion model[J].Aer- ance method of system reliability based on multi-dimen- oengine,2019,45(5):76-81 sional space fault tree[J].Journal of systems science and [12]赵小强,张和慧.基于交叉嫡的改进NPE间歇过程故 mathematical sciences,2014,34(6):682-692 障检测算法).控制与决策,2021,36(2):411-417. [21]崔铁军,马云东.基于SFT理论的系统可靠性评估方 ZHAO Xiaogiang,ZHANG Hehui.Improved NPE batch 法改造研究[J].模糊系统与数学,2015,29(5): process fault detection algorithm based on cross 173-182 entropy[J].Control and decision,2021,36(2):411-417. CUI Tiejun,MA Yundong.Reliability assessment meth-fault diagnosis method for train axle box bearing based on modified multiscale permutation entropy[J]. Journal of the China railway society, 2020, 42(1): 33–39. 张龙, 吴荣真, 雷兵, 等. 基于多尺度熵的滚动轴承故障 可拓智能识别 [J]. 噪声与振动控制, 2019, 39(6): 200–205. ZHANG Long, WU Rongzhen, LEI Bing, et al. Extens￾ible intelligent identification for rolling bearing faults us￾ing multiscale entropy[J]. Noise and vibration control, 2019, 39(6): 200–205. [6] 张雅丽, 刘永姜, 张航, 等. 基于 ITD 信息熵与 PNN 的 轴承故障诊断 [J]. 煤矿机械, 2019, 40(12): 167–169. ZHANG Yali, LIU Yongjiang, ZHANG Hang, et al. Bearing fault diagnosis based on ITD information en￾tropy and PNN[J]. Coal mine machinery, 2019, 40(12): 167–169. [7] 赵书涛, 李云鹏, 王二旭, 等. 基于电—振信号熵权特征 的断路器储能机构故障诊断方法 [J]. 高压电器, 2019, 55(11): 204–210. ZHAO Shutao, LI Yunpeng, WANG Erxu, et al. Fault diagnosis method of circuit breaker energy storage mech￾anism based on electro-vibration signal entropy weight feature[J]. High voltage apparatus, 2019, 55(11): 204–210. [8] 张国辉, 冯俊栋, 徐丙立, 等. 基于故障特征信息量的诊 断策略优化仿真研究 [J]. 计算机仿真, 2019, 36(11): 317–321. ZHANG Guohui, FENG Jundong, XU Bingli, et al. Re￾search on DMFT test method based on hybrid diagnostic model[J]. Computer simulation, 2019, 36(11): 317–321. [9] 戴邵武, 陈强强, 戴洪德, 等. 基于平滑先验分析和模 糊熵的滚动轴承故障诊断 [J]. 航空动力学报, 2019, 34(10): 2218–2226. DAI Shaowu, CHEN Qiangqiang, DAI Hongde, et al. Rolling bearing fault diagnosis based on smoothness pri￾ors approach and fuzzy entropy[J]. Journal of aerospace power, 2019, 34(10): 2218–2226. [10] 王志, 李有儒, 田晶, 等. 基于 EMD 模糊熵与会诊决策 融合模型的中介轴承故障诊断技术 [J]. 航空发动机, 2019, 45(5): 76–81. WANG Zhi, LI Youru, TIAN Jing, et al. Fault diagnosis technology of inter-shaft bearing based on EMD fuzzy entropy and consultative decision fusion model[J]. Aer￾oengine, 2019, 45(5): 76–81. [11] 赵小强, 张和慧. 基于交叉熵的改进 NPE 间歇过程故 障检测算法 [J]. 控制与决策, 2021, 36(2): 411–417. ZHAO Xiaoqiang, ZHANG Hehui. Improved NPE batch process fault detection algorithm based on cross entropy[J]. Control and decision, 2021, 36(2): 411–417. [12] KUMAR A, GANDHI C P, ZHOU Yuqing, et al. Fault diagnosis of rolling element bearing based on symmet￾ric cross entropy of neutrosophic sets[J]. Measurement, 2020, 152: 107318. [13] MINHAS A S, SINGH G, SINGH J, et al. A novel meth￾od to classify bearing faults by integrating standard devi￾ation to refined composite multi-scale fuzzy entropy[J]. Measurement, 2020, 154: 107441. [14] TRUONG M T N, KIM S. Automatic image threshold￾ing using Otsu’s method and entropy weighting scheme for surface defect detection[J]. Soft computing, 2018, 22(13): 4197–4203. [15] MINHAS A S, SINGH S, MALHOTRA J, et al. Ma￾chine deterioration identification for multiple nature of faults based on autoregressive-approximate entropy ap￾proach[J]. Life cycle reliability and safety engineering, 2018, 7(3): 185–192. [16] 刘天寿, 匡海波, 刘家国, 等. 区间数熵权 TOPSIS 的港 口安全管理成熟度评价 [J]. 哈尔滨工程大学学报, 2019, 40(5): 1024–1030. LIU Tianshou, KUANG Haibo, LIU Jiaguo, et al. Evalu￾ation on maturity of port safety management based on interval entropy weight TOPSIS[J]. Journal of Harbin Engineering University, 2019, 40(5): 1024–1030. [17] 杜鑫, 邱庆刚, 丁雅倩, 等. 超临界水冷堆子通道中熵 产行为数值研究 [J]. 哈尔滨工程大学学报, 2018, 39(8): 1290–1295. DU Xin, QIU Qinggang, DING Yaqian, et al. Numeric￾al research on entropy generation in a sub-channel of SCWR[J]. Journal of Harbin Engineering University, 2018, 39(8): 1290–1295. [18] 赵宏伟, 王也然, 刘萍萍, 等. 利用位置信息熵改进 VLAD 的图像检索方法 [J]. 哈尔滨工程大学学报, 2018, 39(8): 1376–1381. ZHAO Hongwei, WANG Yeran, LIU Pingping, et al. Improved VLAD using location information entropy in image retrieval[J]. Journal of Harbin Engineering Uni￾versity, 2018, 39(8): 1376–1381. [19] 崔铁军, 马云东. 基于多维空间事故树的维持系统可 靠性方法研究 [J]. 系统科学与数学, 2014, 34(6): 682–692. CUI Tiejun, MA Yundong. Research on the mainten￾ance method of system reliability based on multi-dimen￾sional space fault tree[J]. Journal of systems science and mathematical sciences, 2014, 34(6): 682–692. [20] 崔铁军, 马云东. 基于 SFT 理论的系统可靠性评估方 法改造研究 [J]. 模糊系统与数学, 2015, 29(5): 173–182. CUI Tiejun, MA Yundong. Reliability assessment meth- [21] 第 6 期 崔铁军,等:线性熵的系统故障熵模型及其时变研究 ·1141·
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