Infrared Switchgear Monitoring With Adaptive Event Rules
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Solution Overview
Problem
Existing thermal monitoring systems for high-voltage electrical switchgear are costly to retrofit and limited in thermal coverage, requiring expensive equipment and certified technicians for periodic inspections, lacking real-time monitoring and predictive capabilities.
Innovation Solution
A non-contact, cost-effective thermal monitoring system with local thermal imaging sensors and a gateway device that learns from environmental data to update event triggering rules, centralizing data processing to improve accuracy and reduce sensor costs, and includes a cloud management system for further analysis and rule updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RFID tags and reader devices are installed on junction screws and power elements, then temperature information can be transmitted, but retrofitting older deployments is difficult and costly requiring power shutdown
Solution Approach 1:
The patent replaces contact-based RFID tags with non-contact thermal imaging sensors that detect temperature through infrared radiation. This eliminates the need to physically attach devices to power elements during retrofitting, allowing installation without power shutdown and reducing retrofitting complexity while maintaining temperature monitoring capability
Solution Approach 2:
The patent introduces thermal imaging sensors as an intermediary device that indirectly measures temperature through thermal radiation rather than direct contact with power elements. This intermediary approach enables temperature monitoring without modifying existing power components, facilitating easier retrofitting of older deployments
2Reliability
If thermal imaging sensors are used for periodic inspection, then temperature data can be collected, but real-time monitoring and prevention is not possible
Solution Approach 1:
The patent implements continuous real-time temperature monitoring using thermal imaging sensors that continuously capture thermal data from power elements. This continuous action replaces periodic manual inspections, enabling immediate detection of temperature anomalies and real-time prevention of thermal runaway events
Solution Approach 2:
The patent establishes a feedback loop where thermal imaging sensors continuously monitor temperature, the system analyzes the data in real-time, and automatically triggers alerts or shutdown protocols when abnormal temperature patterns are detected. This closed-loop feedback system enables real-time response to thermal issues
3Area of stationary object
If multiple thermal monitoring devices are deployed locally, then real-time monitoring coverage is improved, but data processing costs and complexity increase
Solution Approach 1:
The patent merges data from multiple distributed thermal imaging sensors into a centralized cloud-based processing system. This consolidation allows extensive monitoring coverage through multiple devices while reducing local processing complexity by transferring data analysis to centralized cloud infrastructure with advanced algorithms
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 real-time monitoring and predictive failure detection, reducing costs by centralizing data processing and improving event detection accuracy over time, with the system capable of operating independently or connected to a cloud management system.
Implementation Method 1
local thermal monitoring devices equipped with thermal imaging sensors monitor elements of the electrical switchgear
Data Source
AI summary
A thermal monitoring system includes thermal monitoring devices that generate sensor data including thermal images depicting monitored elements (e.g. of an electrical switchgear system). The sensor data for all monitoring devices installed at a local deployment is collected by a gateway device, and relevant data from multiple local deployments is further aggregated by a cloud management system for further analysis. New event triggering rules determining how the thermal monitoring devices filter or record the sensor data are generated based on the aggregated data during a continuous learning process. The system detects patterns in the sensor data for the monitoring devices and/or local deployments as a whole and tracks deviations from these patterns, improving the accuracy of the event detection over time.