Citation: | ZHANG Yanfei, SHAO Yang, GONG Weiwei, ZHANG Zhaowei, WU Jianwen. Depth Diagnosis of Spring Mechanical Faults of High Voltage Circuit Breakers Considering Wavelet Packet-Gray Level Co-occurrence Matrix Method[J]. Mechanical Science and Technology for Aerospace Engineering, 2024, 43(2): 274-281. doi: 10.13433/j.cnki.1003-8728.20220199 |
[1] |
段传宗, 鄢志平, 鄢志辉. 高压断路器故障检测与诊断技术[M]. 北京: 中国电力出版社, 2014: 24-28.
DUAN C Z, YAN Z P, YAN Z H. Fault detection and diagnosis technology of high voltage circuit breaker[M]. Beijing: China Electric Power Press, 2014: 24-28.
|
[2] |
HEISING C R, JANSSEN A L J, LANZ W, et al. Summary of CIGRE 13.06 working group world wide reliability data and maintenance cost data on high voltage circuit breakers above 63KV[C]//Proceedings of 1994 IEEE Industry Applications Society Annual Meeting. Denver: IEEE, 1994: 2226-2234.
|
[3] |
刘永超. 高压真空断路器振动特征提取及故障诊断方法研究[D]. 焦作: 河南理工大学, 2017.
LIU Y C. Research on vibration characteristic extraction and fault diagnosis of high voltage vacuum circuit breaker[D]. Jiaozuo: Henan Polytechnic University, 2017. (in Chinese)
|
[4] |
刘明亮. 高压断路器机械振动信号特征提取及故障诊断研究[D]. 哈尔滨: 东北林业大学, 2017.
LIU M L. Research of mechanical vibration signal feature extraction and fault diagnosis of high voltage circuit breaker[D]. Harbin: Northeast Forestry University, 2017. (in Chinese)
|
[5] |
赵国栋. 高压断路器在线监测与智能故障诊断方法研究[D]. 南京: 东南大学, 2017.
ZHAO G D. Research on on-line monitoring and intelligent fault diagnosis method for HVCB[D]. Nanjing: Southeast University, 2017. (in Chinese)
|
[6] |
孙韬. 基于加权证据理论的高压断路器机械故障智能诊断技术[D]. 南京: 东南大学, 2017.
SUN T. Intelligent mechanical fault diagnosis of high voltage circuit breaker based on weighted evidence theory[D]. Nanjing: Southeast University, 2017. (in Chinese)
|
[7] |
黄建. 特征评估高压断路器机械故障诊断方法的研究[J]. 高压电器, 2015, 51(12): 89-95.
HUANG J. Research on machinery fault diagnosis of high voltage circuit breaker based on feature evaluation[J]. High Voltage Apparatus, 2015, 51(12): 89-95. (in Chinese)
|
[8] |
CIABATTONI L, FERRACUTI F, FREDDI A, et al. Statistical spectral analysis for fault diagnosis of rotating machines[J]. IEEE Transactions on Industrial Electronics, 2018, 65(5): 4301-4310. doi: 10.1109/TIE.2017.2762623
|
[9] |
袁建虎, 韩涛, 唐建, 等. 基于小波时频图和CNN的滚动轴承智能故障诊断方法[J]. 机械设计与研究, 2017, 33(2): 93-97.
YUAN J H, HAN T, TANG J, et al. An approach to intelligent fault diagnosis of rolling bearing using wavelet time-frequency representations and CNN[J]. Machine Design and Research, 2017, 33(2): 93-97. (in Chinese)
|
[10] |
须颖, 李昊东, 安冬. 基于GLCM-SDAE的滚动轴承故障诊断方法[J]. 沈阳建筑大学学报(自然科学版), 2020, 36(4): 720-728.
XU Y, LI H D, AN D. Fault diagnosis of rolling bearing based on GLCM-SDAE[J]. Journal of Shenyang Jianzhu University (Natural Science), 2020, 36(4): 720-728. (in Chinese)
|
[11] |
尚洁. 基于LTP灰度共生矩阵和SVM的织物疵点检测分类算法研究[D]. 成都: 成都理工大学, 2020.
SHANG J. Research on fabric defect detection and classification algorithm based on LTP gray-level co-occurrence matrix and SVM[D]. Chengdu: Chengdu University of Technology, 2020. (in Chinese)
|
[12] |
PALIWAL M, KUMAR U A. Neural networks and statistical techniques: a review of applications[J]. Expert Systems with Applications, 2009, 36(1): 2-17. doi: 10.1016/j.eswa.2007.10.005
|
[13] |
ZHANG J F, LIU M L, WANG K Q, et al. Mechanical fault diagnosis for HV circuit breakers based on ensemble empirical mode decomposition energy entropy and support vector machine[J]. Mathematical Problems in Engineering, 2015, 2015: 101757.
|
[14] |
HUANG N T, CHEN H J, ZHANG S X, et al. Mechanical fault diagnosis of high voltage circuit breakers based on wavelet time-frequency entropy and one-class support vector machine[J]. Entropy, 2015, 18(1): 7. doi: 10.3390/e18010007
|
[15] |
王英英, 罗毅, 涂光瑜. 基于粗糙集与决策树的配电网故障诊断方法[J]. 高电压技术, 2008, 34(4): 794-798.
WANG Y Y, LUO Y, TU G Y. Fault diagnosis method for distribution networks based on the rough sets and decision tree theory[J]. High Voltage Engineering, 2008, 34(4): 794-798. (in Chinese)
|
[16] |
顾礼斌, 李勇刚. 基于模糊 k近邻的变电站主接线类型自动识别方法[J]. 广东电力, 2018, 31(2): 130-135. doi: 10.3969/j.issn.1007-290X.2018.002.021
GU L B, LI Y G. Automatic identification method for substation main wiring modes based on fuzzy k-nearest neighbor algorithm[J]. Guangdong Electric Power, 2018, 31(2): 130-135. (in Chinese) doi: 10.3969/j.issn.1007-290X.2018.002.021
|
[17] |
宁可, 孙同晶, 赵浩强. 基于属性关联的朴素贝叶斯分类算法[J]. 计算机工程, 2018, 44(6): 18-23. doi: 10.3969/j.issn.1000-3428.2018.06.004
NING K, SUN T J, ZHAO H Q. Naive Bayesian classification algorithm based on attribute association[J]. Computer Engineering, 2018, 44(6): 18-23. (in Chinese) doi: 10.3969/j.issn.1000-3428.2018.06.004
|
[18] |
张伟, 王志海, 原继东, 等. 一种局部属性加权朴素贝叶斯分类算法[J]. 北京交通大学学报, 2018, 42(2): 14-21.
ZHANG W, WANG Z H, YUAN J D, et al. A locally attribute weighted naive Bayes classifier[J]. Journal of Beijing Jiaotong University, 2018, 42(2): 14-21. (in Chinese)
|