Partial Discharge Tester (PD Tester) is the "stethoscope" and "microscope" in the field of power equipment insulation diagnostics. It is used to detect tiny partial discharge phenomena in the insulation systems of high-voltage electrical equipment. Partial Discharge (PD) refers to electrical breakdown that occurs only in a part of the insulation inside or on its surface. Although it does not immediately cause complete equipment failure, long-term partial discharge will gradually corrode insulation materials and eventually lead to catastrophic insulation breakdown accidents. Therefore, PD testing is a core means of assessing the health status of high-voltage equipment and predicting its remaining life. Given that the current time is 2026, modern partial discharge testers are highly integrated and intelligent, and widely adopt multi-dimensional detection technologies such as Ultra-High Frequency (UHF), Acoustic Emission (AE), and High-Frequency Current Transformer (HFCT).



1. Core Working Principle

When partial discharge occurs, it produces various physical effects. The tester captures these signals to locate and quantify defects:

Electrical pulse signals: High-frequency current pulses generated at the moment of discharge (main detection method).

Electromagnetic wave radiation: UHF (300MHz-3GHz) electromagnetic waves generated by discharge.

Acoustic wave vibration: Ultrasonic signals generated by discharge (frequency typically 20kHz-300kHz).

Optical radiation: Weak light accompanying some gas discharges (less commonly used in routine testing).

Testing process: Sensor acquisition → Preamplifier filtering and amplification → High-speed A/D sampling → Digital signal processing (denoising, feature extraction) → Pattern recognition (AI algorithm determines defect type) → Report generation.

2. Main Detection Technologies and Methods

A. Electrical Method (Pulse Current Method - IEC 60270 Standard)

Principle: Measures the pulse current generated across the test object using coupling capacitors and detection impedance.

Advantages: Quantitatively accurate (unit: pC), and is the benchmark method for factory and type tests.

Disadvantages: Weak anti-interference capability, requiring shielding rooms or complex on-site noise reduction; limited transmission distance for low-frequency signals.

Applicable to: Factory tests and laboratory precision measurements of transformers, instrument transformers, and cables.

B. Ultra-High Frequency Method (UHF Method)

Principle: Uses built-in or external antennas to receive 300MHz-3GHz electromagnetic waves generated by PD.

Advantages: Extremely strong anti-interference capability (avoids low-frequency grid noise), very high sensitivity, suitable for online monitoring and GIS (Gas-Insulated Switchgear) detection.

Disadvantages: Difficult to directly calibrate to pC values (usually expressed in dBm or relative amplitude), requiring the establishment of correlation models.

Applicable to: GIS/GIL, transformers, high-voltage cable terminations.

C. Acoustic Emission Method (AE Method)

Principle: Uses piezoelectric sensors in contact with the equipment enclosure to receive mechanical vibration waves generated by PD.

Advantages: Precise location (via time-difference of arrival), immune to electromagnetic interference, and can distinguish internal discharge from surface discharge.

Disadvantages: Signals attenuate quickly in solids/liquids, short detection distance, requiring multi-point deployment.

Applicable to: Transformer tanks, GIS enclosures, cable joint location.

D. High-Frequency Current Transformer Method (HFCT Method)

Principle: Clamp-on sensors are attached to grounding wires to sense high-frequency current signals.

Advantages: Non-invasive, easy installation, no power outage required (online detection), suitable for cables and rotating machines.

Applicable to: High-voltage cables, generator/motor stator windings.

3. Technology Development Trends and Characteristics in 2026

Current partial discharge testers have evolved significantly compared to a few years ago:

Multi-sensor Fusion: Single methods are prone to misjudgment; modern instruments integrate UHF + AE + HFCT + TEV (Transient Earth Voltage) modules simultaneously.

The system automatically synthesizes multiple signal characteristics, greatly improving the accuracy of defect identification (>95%).

AI Intelligent Diagnosis and Pattern Recognition: Built-in deep learning algorithms automatically analyze PRPD patterns (Phase-Resolved Partial Discharge patterns).

It can automatically identify typical defect types: internal void discharge, corona discharge, floating potential discharge, surface discharge, and provide confidence scores.

It has a "self-learning" function, and its recognition capability continuously improves as the database updates.