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.536 智能系统学报 第12卷 通过计算焦元距离得到各焦元的信任度,提出了一 BAI Jianlin,WANG Yu.Efficient combination approach to 种新的D-S证据理论组合规则。利用该组合规则将 conflict evidence for D-S theory[J].Systems engineering 不同神经网络的证据体和加权证据体进行融合,可 and electronics,2009,31(9):2106-2109. 以成功诊断出电动汽车电池系统的所有故障,诊断 [8]韩德强,邓勇,韩崇昭,等.基于证据距离与不确定度的 精度不仅高于单一的故障诊断方法,而且优于已有 证据组合方法[J].红外与毫米波学报,2011,30(5): 396-400. 的部分D-S融合诊断方法,提高了诊断的准确性,得 HAN Deqiang,DENG Yong,HAN Chongzhao,et al. 到了符合事实的诊断结果,从而对电动汽车锂电池 Weighted evidence combination based on distance of 故障状态的准确判断。 evidence and uncertainty measure[J].Journal of infrared 参考文献: millim waves,.2011,30(5):396-400. [9]郭雷雷智能环境下基于视频多特征融合的单说话人跟 [1]王一卉,姜长泓模糊神经网络专家系统在动力锂电池组 踪方法研究[D].兰州:兰州理工大学,2014. 故障诊断中的应用[J].电测与仪表,2015,52(14): GUO Leilei.The research of single speaker tracking 118-123 algorithm based on video multi-feature fusion in meeting WANG Yihui,JIANG Changhong.Fuzzy neural network ex- room environment[D].Lanzhou:Lanzhou university of tech- pert system for fault diagnosis in power lithium battery appli- nology,2014. cation J].Electrical measurement instrumentation, [10]牛强军,黄家成.基于改进的D-S决策融合的航电设备 2015,52(14):118-123. 故障诊断[J].计算机工程与设计,2015,36(8): [2]卿平勇.混合动力汽车电池管理系统故障诊断与健康管 2255-2259. 理研究「D].北京:北京理工大学,2015. NIU Qiangjun,HUANG Jiacheng.Avionics equipment QING Pingyong.Reserch on fault diagnosis and health man- fault diagnosis based onimproved dempster-shafe decision agement of battery management system for hybrid electric ve- fusion method [J].Computer engineering and design, hicle[D].Beijing:Beijing Institute of Technology,2015. 2015,36(8):2255-2259. [3]檀斐.车用动力锂离子电池故障诊断研究与实现[D].北 [11]Mengmeng Ma,Jiyao An.Combination of evidence with dif- 京:北京理工大,2015. ferent weighting factors:a novel probabilistic-based dissim- TAN Fei.Fault diagnosis and implementation of electric ve- ilarity measure approach[J].Journal of sensors,2015:1 hicle lithiumion battery system[D].Beijing:Beijing Institute -9 of Technology,2015. [12]费翔,周健.一种处理冲突证据的D-S证据权重计算方 [4]付家才,万遂.基于DS证据理论和BP神经网络的多传 法[J].计算机工程,2016,42(2):142-145 感器信息融合[J].自动化与仪器仪表,2011,1(153): FEI Xiang,ZHOU Jian.A D-S evidence weight computing 22-24. method for conflict evidence[J].Computer engineering, FUJiacai,WAN Sui.Multisensor information fusion based on 2016,42(2):142-145. D-S evidence theory and BP neural network[J].Automation [13]胡海亮,钟求喜.基于证据可信度的D-S理论改进方法 instrumentation,2011,1(153):22-24. [J].计算机应用与软件,2016,33(6):13-19. [5]程加堂,段志梅.基于QPSO-BP和改进D-S的水电机组 HU Hailiang,ZHONG Qiuxi.An improved method for d-s 振动故障诊断[J].电力系统保护与控制,2015,43(19): theory based on evidence credibility[J].Computer applica- 66-71. tions and software,2016,33(6):13-19. CHENG Jiatang,DUAN Zhimei,AI Li,et al.Vibration [14]RONALD R Y.On the dempster-shafer framework and new fault diagnosis for hydroelectric generating unit based on combination rules J].Information sciences S1007- QPSO-BP and modified D-S theory[J].Power system pro- 7634),1987,41(2):93-137. tection and control,2015,43(19):66-71. [15]孙全,叶秀清,顾伟康.一种新的基于证据理论的合成 [6]徐春梅,彭道刚,张悦.基于集成法的汽轮机组智能故障 公式[J].电子学报,2000(08):117-119. 诊断仿真研究[J刀.计算机仿真,2015(07):408-412. SUN Quan,YE Xiuqing,GU Weikang.A new combination XU Chunmei,PENG Daogang,ZHANG Yue.simulation re- rules of evidence theory[J].Acta electronica sinica,2000 search on intelligent fault diagnosis for turbine generator unit (08):117-119 based on integrated method J.Computer simulation,2015 [16]李弼程,王波,魏俊,等.一种有效的证据理论合成公 (07):408-412. 式[J].数据采集与处理,2002,17(1):33-36. [7]白剑林,王煜.一种解决DS理论证据冲突的有效方法 LI Bicheng,WANG Bo,WEI Jun,et al.An efficient com- [J].系统工程与电子技术,2009,31(9):2106-2109. bination rule of evidence theory[].Joumal of data acqui-通过计算焦元距离得到各焦元的信任度,提出了一 种新的 D⁃S 证据理论组合规则。 利用该组合规则将 不同神经网络的证据体和加权证据体进行融合,可 以成功诊断出电动汽车电池系统的所有故障,诊断 精度不仅高于单一的故障诊断方法,而且优于已有 的部分 D⁃S 融合诊断方法,提高了诊断的准确性,得 到了符合事实的诊断结果,从而对电动汽车锂电池 故障状态的准确判断。 参考文献: [1]王一卉,姜长泓.模糊神经网络专家系统在动力锂电池组 故障诊断中的应用 [ J]. 电测与仪表, 2015, 52 ( 14): 118-123. WANG Yihui, JIANG Changhong. Fuzzy neural network ex⁃ pert system for fault diagnosis in power lithium battery appli⁃ cation [ J ]. Electrical measurement & instrumentation, 2015, 52(14): 118-123. [2]卿平勇.混合动力汽车电池管理系统故障诊断与健康管 理研究[D].北京:北京理工大学,2015. QING Pingyong. Reserch on fault diagnosis and health man⁃ agement of battery management system for hybrid electric ve⁃ hicle[D].Beijing: Beijing Institute of Technology,2015. [3]檀斐.车用动力锂离子电池故障诊断研究与实现[D].北 京:北京理工大,2015. TAN Fei. Fault diagnosis and implementation of electric ve⁃ hicle lithiumion battery system[D].Beijing: Beijing Institute of Technology,2015. [4]付家才,万遂.基于 D⁃S 证据理论和 BP 神经网络的多传 感器信息融合[ J].自动化与仪器仪表, 2011, 1(153): 22-24. FUJiacai,WAN Sui. Multisensor information fusion based on D⁃S evidence theory and BP neural network[J]. Automation & instrumentation, 2011, 1(153): 22-24. [5]程加堂,段志梅.基于 QPSO⁃BP 和改进 D⁃S 的水电机组 振动故障诊断[J].电力系统保护与控制, 2015,43(19): 66-71. CHENG Jiatang, DUAN Zhimei, AI Li, et al. Vibration fault diagnosis for hydroelectric generating unit based on QPSO⁃BP and modified D⁃S theory[ J]. Power system pro⁃ tection and control, 2015, 43(19): 66-71. [6]徐春梅,彭道刚,张悦. 基于集成法的汽轮机组智能故障 诊断仿真研究[J]. 计算机仿真, 2015(07): 408-412. XU Chunmei,PENG Daogang,ZHANG Yue. simulation re⁃ search on intelligent fault diagnosis for turbine generator unit based on integrated method[J]. Computer simulation, 2015 (07): 408-412. [7]白剑林,王煜.一种解决 D⁃S 理论证据冲突的有效方法 [J].系统工程与电子技术,2009,31(9): 2106-2109. BAI Jianlin, WANG Yu. Efficient combination approach to conflict evidence for D⁃S theory [ J]. Systems engineering and electronics, 2009,31(9): 2106-2109. [8]韩德强,邓勇,韩崇昭,等. 基于证据距离与不确定度的 证据组合方法[ J]. 红外与毫米波学报, 2011, 30( 5): 396-400. HAN Deqiang, DENG Yong, HAN Chongzhao, et al. Weighted evidence combination based on distance of evidence and uncertainty measure [ J]. Journal of infrared millim waves, 2011, 30(5): 396-400. [9]郭雷雷.智能环境下基于视频多特征融合的单说话人跟 踪方法研究[D].兰州:兰州理工大学,2014. GUO Leilei. The research of single speaker tracking algorithm based on video multi⁃feature fusion in meeting room environment[D].Lanzhou: Lanzhou university of tech⁃ nology, 2014. [10]牛强军,黄家成.基于改进的 D⁃S 决策融合的航电设备 故障 诊 断 [ J]. 计 算 机 工 程 与 设 计, 2015, 36 ( 8 ): 2255-2259. NIU Qiangjun, HUANG Jiacheng. Avionics equipment fault diagnosis based onimproved dempster⁃shafe decision fusion method [ J ]. Computer engineering and design, 2015, 36(8): 2255-2259. [11]Mengmeng Ma, Jiyao An.Combination of evidence with dif⁃ ferent weighting factors: a novel probabilistic⁃based dissim⁃ ilarity measure approach[ J].Journal of sensors, 2015: 1 -9. [12]费翔,周健.一种处理冲突证据的 D⁃S 证据权重计算方 法[J]. 计算机工程, 2016, 42(2): 142-145. FEI Xiang, ZHOU Jian. A D⁃S evidence weight computing method for conflict evidence [ J]. Computer engineering, 2016, 42(2): 142-145. [13]胡海亮,钟求喜.基于证据可信度的 D⁃S 理论改进方法 [J].计算机应用与软件, 2016, 33(6): 13-19. HU Hailiang, ZHONG Qiuxi. An improved method for d⁃s theory based on evidence credibility[J]. Computer applica⁃ tions and software, 2016, 33(6): 13-19. [14]RONALD R Y. On the dempster⁃shafer framework and new combination rules [ J ]. Information sciences ( S1007 - 7634), 1987, 41(2): 93-137. [15]孙全,叶秀清,顾伟康. 一种新的基于证据理论的合成 公式[J]. 电子学报, 2000(08): 117-119. SUN Quan, YE Xiuqing, GU Weikang. A new combination rules of evidence theory[J]. Acta electronica sinica, 2000 (08): 117-119. [16]李弼程, 王波, 魏俊,等. 一种有效的证据理论合成公 式[J]. 数据采集与处理, 2002, 17(1): 33-36. LI Bicheng, WANG Bo, WEI Jun,et al. An efficient com⁃ bination rule of evidence theory[J]. Journal of data acqui⁃ ·536· 智 能 系 统 学 报 第 12 卷
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