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Land Transport

Power Transformer Temperature Field Monitoring and Flame Detection System

 

Solution Background

Large power transformers are primarily used as main step-down transformers for power transmission and transformation in substations. They are a core part of substations, have large capacities, and operate in harsh environments. Inspections by operation and maintenance personnel pose certain safety risks. Once a failure or fire occurs, it can cause significant personnel and property losses and affect the normal operation of the transmission system in the region. Currently, the main faults of power transformers include: clogged radiators causing the main transformer oil temperature to rise, and insulation aging of solid insulation materials, all of which are accompanied by abnormal temperatures. Therefore, to take effective protective measures, monitoring the temperature of power transformers is an effective method. Analyzing their temperature data can infer the operating condition of the transformer, and for any abnormal phenomena, it can provide corresponding decision-making services for operation and maintenance personnel.

Solution Introduction

Solution Overview

The system mainly consists of front-end infrared dual-spectrum cameras, temperature, and flame detection software. For equipment detected by cameras, 24-hour infrared temperature field detection is performed. When an anomaly occurs, based on the actual measured temperature values on-site, maintenance level suggestions are provided, such as advising a power outage for inspection if there is a significant temperature jump; when a fire occurs, it automatically reports the fire situation, displays the on-site handling progress in real-time through 3D panorama and live video, guiding safe and orderly fire emergency response on-site; achieving monitoring and perception of fire hazards in converter stations.

Applicable Scenarios

  • Conventional Power Transformers: Applicable to oil-immersed and dry-type power transformers of different voltage levels (10kV - 1000kV), enabling daily operating temperature and fire hazard monitoring.
  • High-Load Operating Transformers: During peak power consumption in the grid or under special operating conditions, focus monitoring on high-load operating transformers to timely detect abnormal temperatures and fire risks caused by overload.
  • Aging Transformers: For transformers with long service life and degraded insulation performance, accurately monitor temperature fields and detect flames to grasp equipment health status in real-time and prevent sudden failures.
  • Outdoor Substation Transformers: Adapts to complex outdoor environments, ensuring stable operation of the transformer monitoring system under climatic conditions such as high temperatures, heavy rain, and sandstorms.

Core Functions

Functional Modules Description
Data Acquisition and Parameter Settings Real-time acquisition of temperature data and image data within the monitoring field of view from infrared thermal imaging devices. Parameter settings include infrared camera parameter configuration, etc.
Temperature Field Monitoring and Analysis Module Real-time analysis of temperature information in the monitoring area, monitoring for temperature fluctuations or continuous increases, and providing warning signals.
Data Analysis In flame detection, the dynamics, contour, and temperature information of the flame must be combined for judgment. Combining these three reduces false alarms. The system uses the random forest method, with samples reaching the tens of thousands level; the algorithm adopts a feature-based method using flame contours and utilizes temperature information to filter out flame background information.
Image Display Enables refreshing and displaying thermal image distribution information within the monitoring field of view. When a fire occurs, it can display location coordinate information on the image (up to 3 locations).
Alarm Module If flames are detected within the monitoring field of view, an alarm signal is issued.
Data Storage Automatically stores reports from the detection of an alarm event until the alarm is effectively suppressed and cleared.

Technical Advantages

  • Highly Reliable Flame Recognition: Deep learning-based flame detection algorithm, trained with a large number of samples, possesses high anti-interference capability, can effectively distinguish between flames and interfering factors like lights, reflections, etc., with a false alarm rate <0.1%.
  • All-Weather Operation Capability: The system equipment has an IP66 protection rating, adapts to a wide temperature environment of -40℃ - 85℃, supports electromagnetic interference prevention and salt spray corrosion resistance design, and can operate stably in harsh environments.

Application Cases

Case One: A New Energy Substation

  • Project Background: This substation is equipped with multiple dry-type transformers, operates in a complex environment, and has high requirements for temperature and fire monitoring.
  • Solution Implementation: Implemented a temperature field monitoring and flame detection system, combined with the automation management needs of new energy power stations, to achieve data docking and interlinked control with the power station monitoring system.
  • Application Effects: The system real-time monitors transformer temperature changes, automatically adjusts the operating status of cooling fans, reducing energy consumption by 15%; successfully warned of minor fires caused by insulation material aging 2 times, ensuring the safe and stable operation of the new energy power station.

 

 

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Solution Introduction

Application Cases

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