|
|
|
| Surface Vibration Measurement and Compensation Algorithm of Power Equipment Based on Laser Doppler Vibration |
| Lai Zekai1, Guan Xiangyu1, Tu Jiayi1, Lin Jiangang1,2, Xu Xinling1 |
1. School of Electrical Engineering and Automation Fuzhou University Fuzhou 350108 China;
2. CHINALCO Shandong Advanced Material Co. Ltd Zibo 255052 China |
|
|
|
Abstract The electromagnetic force generated by the internal discharge defects of power equipment will trigger an abnormal vibration source, which is transmitted to the surface of the equipment through the internal rigid components and gas-liquid insulating medium. As a result, potential mechanical defects within the equipment can be detected by vibration characteristics on the surface of the equipment. Laser Doppler vibration (LDV) is a non-contact vibration measurement technology widely used in various fields. However, the application of commercially available general-purpose LDV vibration measurement devices on power equipment has many shortcomings, such as insufficient optical coupling and weak resistance to strong magnetic interference. This paper proposes a comprehensive compensation algorithm for the unadaptable surface roughness of electrical materials and unbalanced amplitude-phase of IQ signals, which exist in the detection of LDV in the charged operation of power equipment.
Firstly, the 1 550 nm all-fiber heterodyne interferometric vibration measurement system is designed and constructed according to the principle of LDV vibration measurement. The vibration signal reduction is realized using the baseband signal quadrature demodulation algorithm. Second, the surface roughness of different electrical materials is obtained by a roughness tester, and a three-dimensional ray optical compensation model is established considering the combination of rough electrical material surfaces and lenses. Third, the mirror image suppression algorithm is used to correct the effect of IQ amplitude-phase imbalance on the demodulation results, and the effectiveness of the correction algorithm is discussed. Finally, the vibration test platforms and the actual vibration measurement experiment platform of Gas Insulated Switchgear (GIS) are constructed.
The results show that the average coupling efficiency of the LDV is increased by 21.92% for different electrotechnical materials after adding the proposed optical antenna compensation, which verifies the feasibility of the optical antenna structure design. Under strong magnetic environmental interference, the IQ signal has an image interference ratio (IIR) of 25.04 dB and an orthogonality imbalance of 0.012. The signal-to-noise ratio of the demodulated signal is improved by 25.8 dB after the compensation of the IQ signal.
The calibration test of LDV for electrical materials shows that the developed equipment has accurate measurement results and high signal-to-noise ratios. The stability of distance response for different electrical materials can be satisfied in long-distance energized detection of electrical equipment. In the actual power equipment charged operation, the improved LDV system is easy to install and avoids the transmission loss caused by reflective stickers. Compared with traditional acceleration sensors, the measured time domain waveforms are closer to sinusoidal, and the frequency domain graphs are less noisy. Thus, the vibration component caused by defects can be clearly seen. The following work will improve the LDV equipment by adding vibration mirrors to realize multi-point scanning vibration measurement, obtain the full-field data of vibration on the surface of the power equipment, and carry out the subsequent inverse analysis of the internal structure.
|
|
Received: 08 March 2024
|
|
|
|
|
|
[1] 刘会兰, 许文杰, 赵书涛, 等. 面向高压断路器故障分类的电流-振动信号类聚几何敏感特征优选方法[J]. 电工技术学报, 2023, 38(1): 26-36.
Liu Huilan, Xu Wenjie, Zhao Shutao, et al.Opti- mization method of clustering geometric sensitive features of current vibration signals for fault classification of high voltage circuit breakers[J]. Transactions of China Electrotechnical Society, 2023, 38(1): 26-36.
[2] 豆龙江, 何玉灵, 万书亭, 等. 基于振动信号的高压断路器弹簧疲劳程度检测方法[J]. 电工技术学报, 2022, 37(24): 6420-6430.
Dou Longjiang, He Yuling, Wan Shuting, et al.Detecting method of high voltage circuit breaker spring fatigue based on vibration signal[J]. Transa- ctions of China Electrotechnical Society, 2022, 37(24): 6420-6430.
[3] 钟尧, 郝建, 丁屹林, 等. GIS设备典型机械缺陷的非线性振动行为表征参量分析和诊断模型研究[J]. 中国电机工程学报, 2022, 42(19): 7248-7260.
Zhong Yao, Hao Jian, Ding Yilin, et al.Nonlinear vibration behavior characterization parameter analysis and diagnosis model of typical mechanical defects of GIS equipment[J]. Proceedings of the CSEE, 2022, 42(19): 7248-7260.
[4] Liu Baowen, Ma Hongzhong, Ju Ping.Partial dis- charge diagnosis by simultaneous observation of discharge pulses and vibration signal[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2017, 24(1): 288-295.
[5] 王扬程, 关向雨, 陈志鹏, 等. 基于结构声强法的GIS机械振动传递特性[J]. 电工技术学报, 2024, 39(16): 5162-5171.
Wang Yangcheng, Guan Xiangyu, Chen Zhipeng, et al.Energy transfer characteristics of GIS mechanical vibration based on structural intensity method[J]. Transactions of China Electrotechnical Society, 2024, 39(16): 5162-5171.
[6] 王青, 李怡, 林焱, 等. 电力变压器铁心振动特性分析[J]. 电气工程学报, 2022, 17(1): 114-121.
Wang Qing, Li Yi, Lin Yan, et al.Analysis on vibration problems in transformer core[J]. Journal of Electrical Engineering, 2022, 17(1): 114-121.
[7] 杜厚贤, 刘昊, 雷龙武, 等. 基于振动信号多特征值的电力变压器故障检测研究[J]. 电工技术学报, 2023, 38(1): 83-94.
Du Houxian, Liu Hao, Lei Longwu, et al.Power transformer fault detection based on multi- eigenvalues of vibration signal[J]. Transactions of China Electrotechnical Society, 2023, 38(1): 83-94.
[8] 赵莉华, 徐立, 刘艳, 等. 基于点对称变换与图像匹配的变压器机械故障诊断方法[J]. 电工技术学报, 2021, 36(17): 3614-3626.
Zhao Lihua, Xu Li, Liu Yan, et al.Transformer mechanical fault diagnosis method based on symmetrized dot patter and image matching[J]. Transactions of China Electrotechnical Society, 2021, 36(17): 3614-3626.
[9] 马宏忠, 肖雨松, 颜锦, 等. 基于多特征提取和麻雀搜索算法优化XGBoost的变压器绕组松动诊断方法[J]. 电机与控制学报, 2024, 28(6): 87-97.
Ma Hongzhong, Xiao Yusong, Yan Jin, et al.Transformer winding looseness diagnosis method based on multiple feature extraction and sparrow search algorithm optimized XGBoost[J]. Electric Machines and Control, 2024, 28(6): 87-97.
[10] 刘云鹏, 来庭煜, 刘嘉硕, 等. 特高压直流换流阀饱和电抗器振动声纹特性与松动程度声纹检测方法[J]. 电工技术学报, 2023, 38(5): 1375-1389.
Liu Yunpeng, Lai Tingyu, Liu Jiashuo, et al.Vibration voiceprint characteristics and looseness detection method of UHVDC converter valve saturable reactor[J]. Transactions of China Elec- trotechnical Society, 2023, 38(5): 1375-1389.
[11] 高璐, 汲胜昌, 祝令瑜, 等. 高压换流站干式空心电抗器的振动产生机理及影响因素研究[J]. 中国电机工程学报, 2022, 42(16): 5960-5970, 6170.
Gao Lu, Ji Shengchang, Zhu Lingyu, et al.Study on vibration mechanism and impact factors of dry-type air-core reactor in HVDC converter stations[J]. Proceedings of the CSEE, 2022, 42(16): 5960-5970, 6170.
[12] 张驰, 王顺, 关向雨, 等. 激光多普勒测振技术应用的新进展[J]. 激光与光电子学进展, 2022, 59(19): 85-91.
Zhang Chi, Wang Shun, Guan Xiangyu, et al.New progress in application of laser Doppler vibration measurement technology[J]. Laser & Optoelectronics Progress, 2022, 59(19): 85-91.
[13] 芮小博, 孔欣玥, 李磊霞, 等. 激光远距离语音探测技术进展[J]. 激光与光电子学进展: 1-18.
Rui Xiaobo, Kong Xinyue, Li Leixia, et al.Advances in remote laser speech signal detection technology[J]. Laser & Optoelectronics Progress: 1-18.
[14] Zadeh A R, Heredia L C.Partial discharge detection in high-voltage gas insulated switchgear using fiber optic based acoustic sensors[C]//2023 INSUCON- 14th International Electrical Insulation Conference (INSUCON), Birmingham, United Kingdom, 2023: 216-220.
[15] Peng Shuping, Wu Shisong, Li Yuanyang, et al.All-fiber monostatic pulsed laser Doppler vibrometer: a digital signal processing method to eliminate cochannel interference[J]. Optics & Laser Technology, 2020, 124: 105952.
[16] Li Yan, Wang Yu, Xiao Lin, et al.Phase demo- dulation methods for optical fiber vibration sensing system: a review[J]. IEEE Sensors Journal, 2022, 22(3): 1842-1866.
[17] 彭明金, 李智. 基于希尔伯特-黄变换的激光微多普勒信号分析与特征提取[J]. 中国激光, 2013, 40(8): 0809004.
Peng Mingjin, Li Zhi.Analysis and feature extraction of laser micro-Doppler signatures based on Hilbert- Huang transforms[J]. Chinese Journal of Lasers, 2013, 40(8): 0809004.
[18] Kroschel K.Laser Doppler vibrometry for non- contact diagnostics[M]. Cham: Springer International Publishing, 2020.
[19] 梁冬梅. 基于空气耦合超声和激光测振的板材损伤检测研究[D]. 天津: 天津大学, 2020.
Liang Dongmei.Research on damage detection in plate based on air-coupled ultrasound and laser vibrometer[D]. Tianjin: Tianjin University, 2020.
[20] Zhang Wen, Lü Zhenzhen, Xiong Shuangli.Non- destructive quality evaluation of agro-products using acoustic vibration methods-a review[J]. Critical Reviews in Food Science and Nutrition, 2018, 58(14): 2386-2397.
[21] 肖遥, 熊鑫, 汲胜昌, 等. 干式空心电抗器振动的测试方法研究[J]. 高压电器, 2019, 55(11): 165-170, 183.
Xiao Yao, Xiong Xin, Ji Shengchang, et al.Research on vibration test method of dry-type air-core reactor[J]. High Voltage Apparatus, 2019, 55(11): 165-170, 183.
[22] Zheng Jing, Pan Jie, Huang Hai.An experimental study of winding vibration of a single-phase power transformer using a laser Doppler vibrometer[J]. Applied Acoustics, 2015, 87: 30-37.
[23] Gu Chunhui, Mo Wenxiong, Lu Weifeng, et al.Study on vibration distribution characteristics of a three- phase three-limb transformer core[C]//2018 IEEE International Conference on High Voltage Engin- eering and Application (ICHVE), Athens, Greece, 2018: 1-4.
[24] Khattak M M, Sugino C, Erturk A.Concurrent vibration attenuation and low-power electricity generation in a locally resonant metastructure[J]. Journal of Intelligent Material Systems and Structures, 2022, 33(15): 1990-1999.
[25] 吕博, 冯睿, 寇伟, 等. 折反射式空间相机光学系统设计与杂散光抑制[J]. 中国光学, 2020, 13(4): 822-831.
Lü Bo, Feng Rui, Kou Wei, et al.Optical system design and stray light suppression of catadioptric space camera[J]. Chinese Optics, 2020, 13(4): 822-831.
[26] 赵猛, 颜昌翔, 吴从均. 激光通信地面测试终端间隔离度的仿真分析[J]. 中国光学, 2020, 13(3): 472-481.
Zhao Meng, Yan Changxiang, Wu Congjun.Simu- lation analysis of isolation between laser com- munication ground test equipments[J]. Chinese Optics, 2020, 13(3): 472-481.
[27] Nam W, Roh H, Lee J, et al.Blind adaptive I/Q imbalance compensation algorithms for direct- conversion receivers[J]. IEEE Signal Processing Letters, 2012, 19(8): 475-478.
[28] Nayebi E, Dayal P, Song K B.Adaptive IQ mismatch compensation in time-domain using frequency- domain observations[J]. IEEE Transactions on Signal Processing, 2021, 69: 655-668.
[29] Neelam S G, Sahu P R.Joint estimation and compensation of CFO, IQ imbalance and channel parameters for zero padded OTSM systems[J]. IEEE Wireless Communications Letters, 2023, 12(11): 1871-1875.
[30] 张楠, 孟洲, 饶伟, 等. 干涉型光纤水听器数字化外差检测方法动态范围上限研究[J]. 光学学报, 2011, 31(8): 0806011.
Zhang Nan, Meng Zhou, Rao Wei, et al.Analysis on upper limit of dynamic range of fiber optic interferometric hydrophone using digital heterodyne detection scheme[J]. Acta Optica Sinica, 2011, 31(8): 0806011.
[31] 陈章霖, 谢洋洋, 王渊, 等. 基于双鉴相器相位解调的光纤干涉型局放超声传感方法[J]. 电工技术学报, 2023, 38(23): 6514-6524.
Chen Zhanglin, Xie Yangyang, Wang Yuan, et al.Optical fiber interferometric sensing technology for partial discharge ultrasound based on dual phase detectors phase demodulation method[J]. Transa- ctions of China Electrotechnical Society, 2023, 38(23): 6514-6524.
[32] 唐世刚, 龚克, 潘长勇, 等. 数字接收机I/Q支路不平衡的时域补偿[J]. 清华大学学报(自然科学版), 2007, 47(1): 49-52.
Tang Shigang, Gong Ke, Pan Changyong, et al.Time domain compensation of I/Q imbalance in digital receivers[J]. Journal of Tsinghua University (Science and Technology), 2007, 47(1): 49-52.
[33] Ohshita Y, Hashimoto A, Kurosawa Y.A diagnostic technique to detect abnormal conditions of contacts measuring vibrations in metal enclosures of gas insulated switchgear[J]. IEEE Transactions on Power Delivery, 1989, 4(4): 2090-2094. |
|
|
|
2025, Vol. 40 
