In the field of insulation state detection of power equipment, the sensitivity index of partial discharge detection system is becoming the core consideration factor. With the acceleration of the construction of new power systems, the high proportion of new energy access and the continuous improvement of voltage levels of power grid equipment have put forward higher requirements for the sensitivity, anti-interference and accuracy of partial discharge detection.

Sensitivity: Not just for numerical games

Partial discharge is an early sign of insulation degradation in power equipment, which is weak and difficult to detect, and can only be detected by very sensitive measuring instruments. The sensitivity index seems intuitive -the smaller the value, the weaker the discharge signal can be detected. However, industry experts point out that higher sensitivity is not necessarily better. Excessive sensitivity may introduce more interference signals and mistake environmental noise for partial discharge signals; Insufficient sensitivity may result in missed detection of early insulation defects and loss of warning significance.

Sensitivity differences among different technological routes

When partial discharge occurs, multiple physical field signals such as electromagnetic waves, ultrasonic waves, and high-frequency currents are generated synchronously. Different detection techniques have their own characteristics in sensitivity.

Ultra high frequency (UHF) detection technology captures electromagnetic wave signals in the frequency range of 300MHz to 3GHz, effectively avoiding power frequency and low-frequency electromagnetic interference. It can identify weak discharges at the lowest level of 0.1pC and is currently the core technology for partial discharge detection of ultra-high voltage and ultra-high voltage equipment. High frequency current (HFCT) detection technology uses a Roche coil clamped to the equipment grounding wire, which has high efficiency in capturing partial discharge signals from the cable body and joints. HFCT sensors exhibit the highest sensitivity in most tests. Ultrasonic detection technology is naturally immune to electromagnetic interference and has high sensitivity to surface discharge and suspended discharge, but its sensitivity is greatly affected by the propagation path.

The engineering case of Wuhan UHV Power Technology Co., Ltd. shows that it successfully located a small discharge of 0.5pC level in 500kV GIS equipment by using ultra-high frequency and ultrasonic joint detection technology, effectively avoiding potential accidents.

Selection requires comprehensive consideration of multidimensional factors

In practical selection, sensitivity needs to be considered in conjunction with factors such as signal-to-noise ratio, anti-interference ability, and applicable scenarios. Industry practice has shown that in actual on-site use, instrument sensitivity may be more than 20dB lower than the nominal value. Therefore, the true performance of equipment in complex electromagnetic environments is more valuable as a reference than laboratory data.

The partial discharge testing system launched by Wuhan UHV adopts ultra-high frequency sensors and digital filtering technology. Through a unique AI noise separation algorithm combined with a fully shielded chassis design, the system's signal-to-noise ratio is increased by 300%, and the false alarm rate is controlled below 0.1%. The system has built-in PRPD and PRPS spectrum analysis functions, which can automatically identify discharge types and accurately locate fault points, improving detection efficiency by 60% compared to traditional detection methods.

Trends in Intelligence and Digitization

Currently, partial discharge detection is developing towards intelligence and multi-sensor fusion. The software copyright of the handheld partial discharge detector recently obtained by Wuhan UHV reflects the technical direction of "intelligent noise reduction+one click recognition" - the entire system can work stably at a sensitivity of 0.1pC, and automatically identify typical discharge types such as corona, suspension, and surface through machine learning models. The detection data is transmitted back to the cloud operation and maintenance platform in seconds through 4G/5G or Wi Fi, realizing the full chain digital management of "on-site detection remote diagnosis closed-loop defect elimination".

The selection of partial discharge detection system should not only focus on sensitivity as a single indicator, but should comprehensively consider factors such as sensor type, frequency response range, anti-interference ability, data analysis function, and manufacturer's technical service ability. It is recommended to combine the specific type of tested equipment and operating environment, and have a professional technical team provide customized selection solutions.