基于音频特征的交流接触器电寿命预测方法

doi:10.19595/j.cnki.1000-6753.tces.201554

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Abstract In this paper, the electrical life prediction method of AC contactor based on audio characteristics is studied. The audio characteristics of AC contactor under three states of abnormal coil voltage, contact wear and shell looseness are analyzed by using fast Fourier transform method. Compared with the normal AC contactor, the results show that the audio characteristics of AC contactor in abnormal state are significantly different from that in normal state. In order to further study the vibration and sound generation mechanism of contactor when closing, a sound field model is established based on vibration equation and sound pressure fluctuation equation. The simulation results show that the amplitude of the audio frequency spectrum generated by the acoustic field model increases with the increase of the working voltage of the coil, and the spectrum distribution changes with the change of the contact shape. BP neural network and convolutional neural network (CNN) are used to build the correlation model between AC contactor closing audio characteristics and electrical life. Four BP network learning algorithms, L-M algorithm, quasi Newton method, momentum BP method and adaptive gradient descent method, are compared. The verification results show that the performance of L-M algorithm is the best, and the prediction error is less than 10%; CNN can learn and extract audio features online, but its prediction error is more than 20%.

Key words： AC contactor audio features Mel frequency cepstrum coefficient neural network electric life prediction

Received: 24 November 2020

PACS:

TM572.2

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	You Yingmin
	Wang Jingqin
	Shu Liang
	Ni Kan
	Zhou Xincheng

Cite this article:

You Yingmin,Wang Jingqin,Shu Liang等. The Method of Electrical Life Prediction Considering the Audio Characteristics of AC Contactor[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1986-1998.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.201554 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I9/1986

[1] 李奎, 李晓倍, 郑淑梅, 等. 基于BP神经网络的交流接触器剩余电寿命预测[J]. 电工技术学报, 2017, 32(15): 120-127.
Li Kui, Li Xiaobei, Zheng Shumei, et al.Residual electrical life prediction for AC contactor based on BP neural network[J]. Transactions of China Electrote-chnical Society, 2017, 32(15): 120-127.
[2] Alexander R, Neuhaus W F, Rieder M H.The effects of material transfer in relays diagn-osed by force and/or voltage measurement[J]. IEEE Transactions on Components and Packaging Technologies: a Publication of the IEEE Components, Packaging, and Manufacturing Technology Society, 2004, 27(1): 12-18.
[3] 付饶, 梁慧敏, 叶雪荣, 等. 接触器触点超程分析及其退化状态的诊断[J]. 电工技术学报, 2020, 35(1) : 125-133.
Fu Rao, Liang Huimin, Ye Xuerong, et al.Analysis of the contact overtravel of contactor and its degradation state evaluation[J]. Transactions of China Electrote-chnical Society, 2020, 35(1): 125-133.
[4] Cui Hechen, Wu Ziran, Wu Guichu, et al.Convolutional neural networks for electrical endurance prediction of alternating current contactors[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2019, 9(9): 1785-1793.
[5] Wu Ziran, Wu Guichu, Huang Hailan, et al.A novel residual electrical endurance prediction method for low-voltage electromagnetic alternating current contactors[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2015, 5(4): 465-473.
[6] Wu Ziran, You Yingmin, Wu Guichu, et al.Research on arcing characteristics of AC contactor breaking processes based on statistics[C]// Proceedings of 5th International Conference on Reliability of Electrical Products and Electrical Contacts, Wenzhou, 2014: 70-75.
[7] 翟国富, 王淑娟, 许峰, 等. 基于超程时间和吸合时间建模的继电器双变量寿命预测方法的研究[J]. 中国电机工程学报, 2002, 22(7): 76-80.
Zhai Guofu, Wang Shujuan, Xu Feng, et al.Research on double-variable life forecasting based on model-building of super-path time and pick-up time for relays[J]. Proceedings of the CSEE, 2002, 22(7): 76-80.
[8] 孙曙光, 纪学玲, 杜太行, 等. 机械振动下交流接触器电寿命预测失效特征量提取[J]. 仪器仪表学报, 2019, 40(3): 114-125.
Sun Shuguang, Ji Xueling, Du Taihang, et al.Failure feature extraction for electrical life prediction of AC contactor under mechanical vibration[J]. Chinese Journal of Scientific Instrument, 2019, 40(3): 114-125.
[9] 杜太行, 安建鹏, 孙曙光, 等. 基于LabVIEW的振动条件下交流接触器电寿命试验系统[J]. 仪表技术与传感器, 2018(8): 113-117.
Du Taihang, An Jianpeng, Sun Shuguang, et al.Electric life test system of AC contactor under vibration condition based on labVIEW[J]. Instrument Technique and Sensor, 2018(8): 113-117.
[10] 魏梅芳, 李震彪, 宋晓亮, 等. 开关触头电寿命预测方法分析[J]. 低压电器, 2006(1): 11-15.
Wei Meifang, Li Zhenbiao, Song Xiaoliang, et al.Analysis of the contacts for switches[J]. Low Voltage Apparatus, 2006(1): 11-15.
[11] 易琳, 沈琦, 王锐, 等. 无人值守变电站电力设备音频监测及故障诊断系统[J]. 计算机测量与控制, 2017, 25(11): 9-12.
Yi Lin, Shen Qi, Wang Rui, et al.Fault diagnosis and condition monitoring of smart substation equipment based on acoustic signals[J]. Computer Measurement & Control, 2017, 25(11): 9-12.
[12] Mao Kunli, Wu Yunxin.Fault diagnosis of rolling element bearing based on vibration frequency analysis[C]//2011 Third International Conference on Measuring Technology and Mechatronics Automation, Shangshai, 2011: 198-201.
[13] 李伟鑫. 基于音频识别的防爆电机故障监测研究[D]. 大庆:东北石油大学, 2015.
[14] 杨林顺,杨明锦. 基于音频的皮带机托辊故障诊断系统设计[J]. 仪表技术, 2019(7): 18-21.
Yang Linshun, Yang Mingjin.Design of fault diagnosis system for the roller of belt conveyor based on the audio frequency[J]. Instrumentation Technology, 2019(7): 18-21.
[15] 王玉芳, 童忠钫. 圆柱撞击发声机理的研究[J]. 振动、测试与诊断, 1991, 11(1): 16-22.
Wang Yufang, Tong Zhongfang.Research on the sound mechanism of cylinder impact[J]. Vibration, Testing and Diagnosis, 1991, 11(1): 16-22.
[16] 李应刚, 陈天宇, 王小鹏, 等. 圆柱碰撞冲击噪声理论分析与数值仿真[J]. 振动与冲击,2014,33(15): 162-166.
Li Yinggang, Chen Tianyu, Wang Xiaopeng, et al.Theoretical analysis and numerical simulation for impact noise due to collision of two cylinders[J]. Journal of Vibration and Shock, 2014, 33(15): 162-166.
[17] 廖旭晖, 李舜酩, 戴旭东, 等. 多点耦合系统中与耦合点有关的频响函数测量[J]. 振动与冲击, 2020, 39(22): 76-81.
Liao Xuhui, Li Shunming, Dai Xudong, et al.Measurement of frequency response functions related to coupling points in multipoint coupled systems[J]. Journal of Vibration and Shock, 2020, 39(22): 76-81.
[18] 马跃洲, 马春伟, 张鹏贤, 等. 基于电弧声波特征的CO₂焊接飞溅预测[J]. 焊接学报, 2002, 23(3): 19-22.
Ma Yuezhou, Ma Chunwei, Zhang Pengxian, et al.CO₂ welding spatter prediction based on arc acoustic characteristics[J]. Transactions of the China Welding Institution, 2002, 23(3): 19-22.
[19] Girin L.Joint matrix quantization of face parameters and LPC coefficients for low bit rate audiovisual speech coding[J]. IEEE Transactions on Speech and Audio Processing, 2004, 12(3): 265-276.
[20] 赵升, 舒亮, 吴自然, 等. 电磁-永磁复合型接触器数值仿真与控制方法[J]. 电工技术学报, 2020, 35(5): 1083-1092.
Zhao Sheng, Shu Liang, Wu Ziran, et al.Numerical simulation and control method of electromagnetic-permanent composite contactor[J]. Transactions of China Electrotechnical Society, 2020, 35(5): 1083-1092.
[21] 游颖敏, 王景芹, 舒亮, 等. 断路器保护特性测试电流的自适应控制策略[J]. 电工技术学报, 2020, 35(15): 3203-3213.
You Yingmin, Wang Jingqin, Shu Liang, et al.Research on adaptive current control method in circuit breaker protection characteristic test[J]. Transactions of China Electrotechnical Society, 2020, 35(15): 3203-3213.
[22] Gubin M V.Using convolutional neural networks to classify audio signal in noisy sound scenes[C]//2018 Global Smart Industry Conference(GloSIC), Chelya-binsk, 2018: 1-6.