# Detection Method of Partial Discharge on Transformer and Gas-Insulated Switchgear: A Review
## 2 Method of PD Detection Based on Different Types of Signals Emitted during PD Activities
### Combinational Method  
The combination of dissolved gas analysis (DGA) and acoustic emission (AE) practices has been employed to identify and localize the partial discharge (PD) anomalies that occur inside power transformers. This integration enables the detection and pinpointing of PD anomalies by using both DGA and AE methods. The detection process involves initially conducting offline dissolved gas analysis (DGA) to assess the gas content, followed by implementing acoustic emission (AE) detection for a duration of 24 h to identify the sources of PD. This approach aims to replicate the daily load cycle and has been documented in reference [95]. An example of the integration of acoustic emission (AE) and dissolved gas analysis (DGA) methods is photo-acoustic spectroscopy (PAS). The operational concept of PAS is illustrated in Figure 6, as described in reference [96]. In this technique, fault gases interact with an infrared source, receiving kinetic energy. The pressure signals are detected by a microphone and converted into electrical signals. By analyzing the amplitude of the sound waves generated and filtering them through optical filters, different gases can be identified.  
The integration of electromagnetic (EM) and acoustic techniques has also been employed. Ultrasonic and ultra-high-frequency (UHF) sensors, configured in various geometries, have shown remarkable effectiveness in detecting the origin of partial discharge (PD) within a specific range, as reported in reference [97]. A proposed approach involves the use of a hybrid PD detection system that combines acoustic emission sensors plus transient earth wire voltage (TEV) [98]. Novel techniques for detecting acoustic emission (AE) involve the use of AE sensors to identify the presence of partial discharge (PD) based on a reference time obtained from electrical equipment (EE) signals. This approach enables the localization and validation of the detected signal, ensuring it is not attributed to external noise [99].  
The technique for identifying PD by combining acoustic emission (AE), electrical equipment (EE), and dissolved gas analysis (DGA) to evaluate the transformer's entire insulating state, as reported in reference [100]. A noise rejection system for PD detection might be created by combining AE and EE approaches. The information gathered via EE detection could be utilized to pinpoint the PD's origin. The sensitivity of the AE  
Figure 5: Fiber Bragg grating principle operation, with refractive index profile and spectral response [92].  
method can be enhanced by integrating using the EE technique, where the latter serves to initiate events.  
A combination of AE and optical techniques involves the use of a Fabry-Perot fiber as an AE sensor for localizing PD. In addition, a fluorescent optical fiber acts as an optical sensor to verify signal of reference originates from a PD source, as documented in reference [101]. Table 1 provides a comparative analysis of the advantages and limitations of various techniques used for detecting PD inside power transformers.