Sensor dan Kalibrasi Partial Discharge untuk Diagnosis dan Pemantauan Kondisi Peralatan Tegangan Tinggi: Analisis Kritis
Bilah Samping Artikel
Isi Artikel Utama
Abstrak
Tantangan krusial dalam Pemantauan Kondisi (Condition Monitoring, CM) dan Pemeliharaan Prediktif peralatan tegangan tinggi (TT) adalah mencapai deteksi yang andal serta lokalisasi sumber Partial Discharge (PD) yang presisi. PD merupakan indikator vital dari degradasi isolasi. Tantangan ini diperberat oleh lingkungan operasional yang kompleks dan non-homogen, di mana struktur internal seperti belitan dan inti transformator secara signifikan mendis-torsi dan melemahkan sinyal, sekaligus menciptakan fenomena multipath akustik. Analisis kritis ini mengkaji konvergensi perkembangan teknologi sensor, teknik kalibrasi, dan algoritma canggih dalam upaya mengatasi tantangan lokalisasi PD tersebut. Ulasan ini menyoroti kemajuan signifikan pada berbagai jenis sensor, mencakup sensor Emisi Akustik (AE) yang telah dioptimalkan dengan Model KLM guna meningkatkan sensitivitas, sensor UHF yang menawarkan imunitas terhadap kebisingan yang superior, dan sensor akustik serat optik inovatif (pressure-balanced) yang dirancang khusus untuk mendeteksi PD ganda. Untuk mencapai akurasi lokalisasi yang lebih tinggi, teknik pemrosesan sinyal telah berevolusi melampaui metode dasar Time Difference of Arrival (TDOA). Kini, diterapkan algoritma yang kuat, seperti Generalized Cross-Correlation with Phase Transformation (GCC-PHAT), yang efektif meredam kebisingan dan pantulan, serta Particle-Swarm-Optimization Route-Searching (PSORS) untuk secara cerdas memodelkan jalur perambatan sinyal akustik di sekitar struktur internal yang menghalangi. Pendekatan alternatif juga mencakup lokalisasi online berbasis analisis Fungsi Transfer elektrik. Integrasi teknologi sensor yang sangat sensitif dengan algoritma pathfinding yang cerdas merupakan kunci untuk mewujudkan diagnosis multimetode yang akurat, sehingga mampu mendukung operasional peralatan TT yang lebih andal dan efisien.
Rincian Artikel
Bagian
Cara Mengutip
Referensi
[2] S. Li and J. Li, “Condition monitoring and diagnosis of power equipment: review and prospective,” High Volt., vol. 2, no. 2, pp. 69–82, Jun. 2017.
[3] A. Hekmati and R. Hekmati, “Optimum acoustic sensor placement for partial discharge allocation in transformers,” IET Sci. Meas. Technol., vol. 11, no. 5, pp. 586–593, Aug. 2017.
[4] F. Witos et al., “Calibration and Laboratory Testing of Computer Measuring System 8AE-PD Dedicated for Analysis of Acoustic Emission Signals Generated by Partial Discharges Within Oil Power Transformers,” Arch. Acoust., vol. 42, no. 2, pp. 297–311, 2017.
[5] H. Chai, B. T. Phung, and S. Mitchell, “Application of UHF Sensors in Power System Equipment for Partial Discharge Detection: A Review,” Sensors, vol. 19, no. 5, p. 1029, Feb. 2019.
[6] W. Sikorski, “Development of Acoustic Emission Sensor Optimized for Partial Discharge Monitoring in Power Transformers,” Sensors, vol. 19, no. 8, p. 1826, Apr. 2019.
[7] C. Gao et al., “Partial Discharge Localization inside Transformer Windings via Fiber-Optic Acoustic Sensor Array,” IEEE Trans. Power Deliv., vol. 34, no. 3, pp. 1198–1205, Jun. 2019.
[8] M. Ghorat et al., “High-Resolution FBG-Based Fiber-Optic Sensor with Temperature Compensation for PD Monitoring,” Sensors, vol. 19, no. 23, p. 5240, Nov. 2019.
[9] N. A. Akashah et al., “A review: Partial discharge detection using acoustic sensor on high voltage transformer,” J. Phys.: Conf. Ser., vol. 1432, p. 012004, 2020.
[10] H. Karami et al., “Partial Discharge Localization Using Time Reversal: Application to Power Transformers,” Sensors, vol. 20, no. 6, p. 1655, Mar. 2020.
[11] G. Ma et al., “Optical sensors for power transformer monitoring: A review,” High Volt., vol. 5, no. 6, pp. 642–659, Dec. 2020.
[12] F. Witos, A. Olszewska, Z. Opilski, A. Lisowska-Lis, and G. Szerszeń, “Application of Acoustic Emission and Thermal Imaging to Test Oil Power Transformers,” Energies, vol. 13, no. 22, p. 5955, Nov. 2020.
[13] H. Besharatifard et al., “Detection and Analysis of Partial Discharges in Oil-Immersed Power Transformers Using Low-Cost Acoustic Sensors,” Appl. Sci., vol. 12, no. 6, p. 3010, Mar. 2022.
[14] H. Besharatifard, S. Hasanzadeh, E. Heydarian-Forushani, and S. M. Muyeen, “Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers,” IEEE Access, vol. 10, pp. 55288–55297, 2022.
[15] W. Al-Masri et al., “Partial Discharge Localization in Power Transformers Using Invariant Extended Kalman Filter,” IEEE Trans. Instrum. Meas., vol. 72, 2023.
[16] Y. Otake and K. Tajiri, “Study of Localization of Partial Discharges in Oil-filled Transformers using Acoustic Emission Signals,” in 4th Asia Pacific Conference of the Prognostics and Health Management, Tokyo, Japan, Sep. 2023.
[17] J. Q. Chan, W. J. K. Raymond, H. A. Illias, and M. Othman, “Partial Discharge Localization Techniques: A Review of Recent Progress,” Energies, vol. 16, no. 1, p. 302, Dec. 2023.
[18] C. P. Beura, J. Wolters, and S. Tenbohlen, “Application of Pathfinding Algorithms in Partial Discharge Localization in Power Transformers,” Sensors, vol. 24, no. 3, p. 892, Jan. 2024.
[19] Y. Wang et al., “Acoustic Sensors for Monitoring and Localizing Partial Discharge Signals in Oil-Immersed Transformers under Array Configuration,” Sensors, vol. 24, no. 14, p. 4704, Jul. 2024.
[20] C. P. Beura, M. Beltle, S. Tenbohlen, and M. Siegel, “Quantitative Analysis of the Sensitivity of UHF Sensor Positions on a 420 kV Power Transformer Based on Electromagnetic Simulation,” Energies, vol. 13, no. 1, p. 3, Dec. 2019.
[21] Y. B. Wang et al., “Acoustic Localization of Partial Discharge Sources in Power Transformers Using a Particle-Swarm-Optimization-Route-Searching Algorithm,” IEEE Trans. Dielectr. Electr. Insul., vol. 24, no. 6, pp. 3647–3654, Dec. 2017.
[22] H. D. Ilkhechi and M. H. Samimi, “Applications of the Acoustic Method in Partial Discharge Measurement: A Review,” Open Eng., vol. 11, no. 1, pp. 42-49, Jan. 2021.
[23] F. Liu, Y. Shi, S. Zhang, and W. Wang, “Localization for Dual Partial Discharge Sources in Transformer Oil Using Pressure-Balanced Fiber-Optic Ultrasonic Sensor Array,” Sensors, vol. 24, no. 14, p. 4450, Jul. 2024.
[24] A. Rodrigo-Mor, F. A. Muñoz, and L. C. Castro-Heredia, “Principles of Charge Estimation Methods Using High-Frequency Current Transformer Sensors in Partial Discharge Measurements,” Sensors, vol. 20, no. 9, p. 2489, Apr. 2020.
[25] J. Zbojovský, A. Hyseni, and J. Petráš, “Partial Discharge Activity Inductive Sensors and the Application of Magnetic Materials,” Sensors, vol. 25, no. 2, p. 5896, Feb. 2025.
[26] Z. Xu et al., “Passive Wireless Partial Discharge Sensors with Multiple Resonances,” Micromachines, vol. 15, no. 5, p. 656, May 2024.
[27] A. N. Hamoodi, S. A. Hamoodi, and R. A. Mohammed, “Partial discharge calibrator of a cavity inside high-voltage insulator,” Open Eng., vol. 12, no. 1, pp. 468–476, 2022.
[28] Y. Otake and K. Tajiri, “Enhanced Method for Localization of Partial Discharges in Oil-Filled Transformers Using Acoustic Emission Signals,” in 4th Asia Pacific Conference of the Prognostics and Health Management, Tokyo, Japan, Sep. 2023.
[29] A. Hamidi, M. Salehi, A. Setayeshmehr, and J. M. Maritz, “Electrical Modeling of High Voltage Windings of Power Transformers for Online Partial Discharge Localization,” IEEE Access, vol. 13, pp. 3549634, Mar. 2025.
[30] [M. Mondal and G. B. Kumbhar, “Partial Discharge Localization in a Power Transformer: Methods, Trends, and Future Research,” IETE Tech. Rev., vol. 33, no. 6, pp. 589–598, 2016.