I. Definition and Core Objectives
Power equipment live detection refers to the on-site inspection of equipment status parameters (such as partial discharge, temperature, gas composition, etc.) using portable instruments while the equipment is in operation. It involves real-time measurement of these parameters as well as sampling and analysis of oil or gas samples. The core objective of this process is:
1. Timely detection of potential hazards: Through short-term and high-sensitivity testing, capture abnormal signals during equipment operation (such as partial discharge, overheating, insulation deterioration, etc.), and identify latent faults.
2. Prevention of accidents: Avoid power outages or safety incidents caused by equipment defects, ensuring the continuous power supply capacity of the power grid.
3. Optimization of maintenance strategies: Provide data support for condition-based maintenance, reduce unnecessary power-off tests, and improve maintenance efficiency.
4. Economic advantages: Compared with online monitoring systems, live detection has the characteristics of low investment and high flexibility, and is suitable for large-scale promotion.
II. Common Detection Methods and Technical Principles
1. Partial Discharge Detection Technology
Ultra High Frequency (UHF) Method: Detects electromagnetic wave signals in the 300-3000 MHz frequency band, with strong anti-interference capability, suitable for internal discharge location in GIS, transformers, etc.
Ultrasonic Method: Captures acoustic wave signals generated by partial discharge through pressure wave sensors, suitable for internal defect diagnosis in equipment such as transformers, switch cabinets, etc.
High Frequency Current Method (HFCT): Detects current signals in the 3-30 MHz frequency band, commonly used for discharge monitoring of cable joints, lightning arresters, etc.
Transient Ground Voltage Method (TEV): Detects transient pulse voltages on the surface of switch cabinets to locate internal discharge.
2. Thermal Imaging and Optical Detection
Infrared Thermal Imaging: Identifies issues such as joint loosening, overload, insulation aging through abnormal temperature distribution on equipment surfaces, suitable for transmission lines, switch cabinets, etc.
Ultraviolet Imaging: Detects ultraviolet wavelengths generated by discharge, used for surface defect detection such as wire injuries, insulator contamination.
3. Chemical and Gas Analysis
Oil Dissolved Gas Analysis (DGA): Detects gas components such as H₂, CH₄, C₂H₂ in transformer oil through chromatography, to determine the degree of insulation material thermal decomposition or discharge.
SF₆ Gas Detection: Analyzes the humidity, purity, and decomposition products (such as SO₂, H₂S) of SF₆ gas in GIS equipment, indirectly diagnosing internal discharge or sealing defects.
4. Vibration and Acoustic Detection
Vibration Signal Analysis: Monitors mechanical vibrations of equipment such as transformers, reactors through acceleration sensors, identifying loose components or winding deformation.
Acoustic Fingerprint Technology: Records acoustic signals during the operation of on-load tap changers of transformers to assess mechanical conditions.
5. Other Specialized Technologies
Frequency Domain Dielectric Spectroscopy (FDS): Analyzes the dielectric loss frequency characteristics of oil-paper insulation to assess moisture or aging degree.
X-ray Imaging: Penetrates to detect internal structural defects (such as contact wear) in GIS and other equipment.
III. Typical Application Scenarios and Equipment Coverage
Device type
Applicable detection technology
Detection target
Transformer
Oil chromatography analysis, infrared thermography, high-frequency current method, vibration detection
Winding deformation, multiple grounding of the core, partial discharge, deterioration of oil-paper insulation
GIS equipment
Ultra-high frequency method, SF₆ gas analysis, ultrasonic method, X-ray imaging
Internal discharge, gas leakage, poor contact of contacts
Switch cabinet
Transient voltage method, ultrasonic method, infrared thermography
Internal discharge, overheating of contacts, mechanical jamming
Power transmission cable
High-frequency current method, oscillation wave partial discharge test, optical fiber temperature measurement
Joint defects, local discharge, insulation aging
Fuses
Infrared thermography, leakage current detection
Valve plate deterioration, moisture absorption, and sealing failure
Insulator
Ultraviolet imaging, infrared thermography, harmonic electric field method
Surface dirtiness, cracks, and internal insulation defects
IV. Industry Standards and Regulatory Frameworks National Standard
DL/T 2277-2021: Specifies the general technical requirements for live detection instruments, covering working conditions, test methods, and marking and packaging, etc.
GB/T 2900.50-2008: Defines electrical engineering terms and provides basic standards for detection technologies.
2. Grid enterprise standards
Q/GDW 11304 series: Technical specifications for live detection instruments formulated by the State Grid, divided into 21 parts to detail the requirements for equipment such as infrared thermography instruments and high-frequency partial discharge instruments.
Southern Power Grid New Technology Catalog (2023): Promotes new live detection technologies such as digital wireless zinc oxide arrester testing and GIS contact impedance testing.
3. Application guidelines and implementation rules
DL/T 664-2008 (Infrared Diagnosis), DL/T 345-2010 (Ultraviolet Diagnosis): Provide operational guidelines for specific detection methods.
Local documents such as Lu Dengyun Jian [2015] No. 45: Formulate live detection cycles and processes based on regional characteristics.
V. Typical Cases and Effect Analysis
GIS Equipment Discharge Location
Case: An abnormal signal was detected during the ultrasonic inspection of a 500kV substation's GIS. Combined with the ultrasonic method, it was identified as suspended discharge inside the bus duct. After disassembly, it was confirmed that the shielding cover was loose.
Effect: Avoided insulation breakdown caused by the continuous development of discharge, reducing direct economic losses of over 10 million yuan.
2. Abnormal Transformer Oil Chromatography
Case: The analysis of dissolved gases in the oil showed that the concentration of C₂H₂ exceeded the standard, indicating internal arc discharge. Timely shutdown for maintenance revealed that the contactors of the tap changer were burned out.
Effect: Prevented transformer explosion accidents and ensured the stability of the regional power grid.
3. Distribution Network Cable Partial Discharge Detection
Case: The oscillation wave partial discharge test detected a defect in the intermediate joint of a 10kV cable. The positioning accuracy reached 0.5 meters. After replacement, the partial discharge amount was reduced to the safe range.
Effect: Reduced user outage time and improved power supply reliability indicators.
VI. Technical Challenges and Development Trends
1. Current Challenges
Threshold Ambiguity: Some detection methods (such as TEV) lack a unified judgment standard and rely on experience.
Interference Suppression: Signal separation in complex electromagnetic environments is difficult (such as the impact of substation background noise on UHF detection).
Data Integration: The integration analysis and intelligent diagnosis of multi-source detection data still need to be overcome.
2. Future Directions
Intelligent Upgrade: Combine AI algorithms to achieve automatic classification of defects and risk assessment.
Non-contact Detection: Promote new technologies such as Laser Induced Breakdown Spectroscopy (LIBS) and Terahertz Imaging.
Internet of Things Integration: Build a cloud platform for detection data, supporting remote diagnosis and predictive maintenance.
