Transformer Thermal Monitoring Using Relative Temperature Alarms
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Solution Overview
Problem
Conventional methods for monitoring high-voltage electrical transformers require expensive and intrusive sensors, labor-intensive oil sampling, or temperature readings that are difficult to calibrate accurately, limiting real-time failure detection.
Innovation Solution
A method and system for remote monitoring that uses raw sensor data without converting to temperature values, grouping data points into multiple groups with independent alarm metrics for real-time, multi-view analysis, allowing comparison of relative temperatures to predict equipment failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If voltage, current, or temperature sensors are attached to the transformer, then real-time monitoring capability is improved, but cost and system complexity increase
Solution Approach 1:
The patent replaces physical contact sensors (voltage, current, temperature sensors attached to the transformer) with an optical detection system using a camera to capture thermal images. This substitution eliminates the need for electrical connections and physical sensor attachments, thereby reducing system complexity and maintenance requirements while maintaining real-time monitoring capability.
Solution Approach 2:
The patent introduces thermal imaging technology as an intermediary between the transformer and the monitoring system. Instead of directly measuring electrical parameters with contact sensors, the system uses infrared radiation detection to obtain thermal images, which serve as an intermediate representation of the transformer's thermal state, enabling indirect but effective monitoring.
2Reliability
If periodic oil sampling is performed, then transformer health analysis is improved, but labor intensity and time consumption increase
Solution Approach 1:
The patent replaces manual oil sampling and laboratory analysis with automated optical imaging. The camera-based system continuously captures thermal images, automatically processing the data to monitor transformer health in real-time, eliminating the need for periodic manual intervention and laboratory testing.
Solution Approach 2:
The system transitions from periodic discrete measurements (oil sampling) to continuous monitoring through automated thermal imaging. The camera continuously captures images and the system continuously processes thermal data, providing uninterrupted real-time health assessment without requiring periodic manual sampling events.
3Ease of operation
If infrared cameras are used to determine exact temperature readings, then remote monitoring capability is improved, but measurement precision deteriorates due to calibration requirements
Solution Approach 1:
The patent changes the measurement parameter from absolute temperature values to relative temperature differences. Instead of attempting to measure exact temperatures that require precise calibration, the system measures temperature differentials between components, which are inherently more robust to calibration drift and environmental variations, thereby maintaining measurement precision without stringent calibration requirements.
Solution Approach 2:
The patent focuses on local temperature differences between specific components rather than global absolute temperature measurements. By comparing temperatures of adjacent or related components (e.g., transformer windings, core, cooling systems), the system identifies localized anomalies that indicate potential failures, making the measurement less sensitive to overall calibration accuracy.
4Reliability
If multiple groups with independent alarm metrics are used, then detection reliability is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the thermal image data into multiple regions of interest, each corresponding to different transformer components or operational parameters. Each segment is analyzed independently with its own alarm metrics, allowing targeted monitoring of critical areas while simplifying the overall processing by dividing the complex task into manageable independent analyses.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable and cost-effective real-time monitoring of transformer health by detecting relative temperature differences, eliminating the need for precise temperature readings and expensive sensors, and providing robust failure prediction.
Implementation Method 1
remote monitoring of the temperature of a transformer using infrared cameras
Data Source
AI summary
According to one aspect, a method for remote monitoring of electrical equipment includes acquiring a set of data points, each data point representing a temperature associated with a piece of electrical equipment or a component thereof, assigning each data point to one or more groups of data points, and defining an alarm metric for each group. Each group's alarm metric may be defined independently of other group's metrics. The defined alarm metrics are used to determine the health of the electrical equipment. The data may be determined from virtual probes within an infrared sensor and/or received from RFID devices containing temperature sensor, which are attached to or near the equipment to be monitored, for example. The methods described herein do not require conversion of sensor data into temperature values, and thus obviate the need for expensive sensors and/or computationally demanding conversion, compensation, and calibration routines.