Grid Asset Monitoring Using RF Event and Asset Clustering
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Solution Overview
Problem
Current methods for detecting deteriorating electric equipment in power transmission and distribution systems, such as visual inspection, infrared sensing, and ultrasonic testing, fail to detect radio-frequency (RF) emissions that indicate equipment degradation before it leads to failure, resulting in potential power outages.
Innovation Solution
A system that uses sensor measurements to monitor grid devices, clustering data to identify probable emission sources, and prioritizing assets based on potential impact, allowing for early detection of equipment degradation through RF signal analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual inspection, infrared sensing, or ultrasonic testing is used to detect equipment degradation, then the inspection methods are simple and widely applicable, but RF emissions from degraded equipment cannot be detected
Solution Approach 1:
The system employs a universal sensor platform capable of detecting multiple types of emissions including RF, acoustic, and thermal signals from grid equipment. This multi-functional approach allows the same system to detect various failure modes across different equipment types (transformers, switches, insulators, conductors) without requiring separate specialized inspection systems for each equipment category.
Solution Approach 2:
The patent replaces traditional mechanical inspection methods (visual inspection, physical contact testing) with electromagnetic field-based detection using RF sensors and acoustic sensors. This substitution enables non-contact, remote detection of equipment degradation through emitted RF signals and acoustic emissions, eliminating the need for physical proximity or direct contact with the equipment.
2Measurement precision
If traditional inspection methods are used, then the equipment can be inspected with existing technologies, but detection of RF emissions indicating early-stage degradation is not possible
Solution Approach 1:
The system introduces RF sensors and acoustic sensors as intermediary detection devices that capture RF emissions and acoustic signals emitted by degraded equipment. These sensors act as mediators between the equipment and the inspection system, converting electromagnetic and acoustic energy into electrical signals that can be processed and analyzed to detect early-stage degradation before it becomes visible through traditional methods.
Solution Approach 2:
The system monitors changes in RF emission parameters (signal strength, frequency, temporal patterns) and acoustic emission parameters over time to detect degradation trends. By tracking parameter changes rather than relying on static threshold measurements, the system can identify early-stage degradation and predict potential failures before they occur.
3Reliability
If equipment is inspected using existing technologies, then inspection can be performed with current tools, but power outages may still occur due to undetected degradation
Solution Approach 1:
The system performs preliminary detection of equipment degradation by continuously monitoring RF emissions and acoustic signals to identify early signs of deterioration. This preliminary action enables utilities to take preventive maintenance actions before equipment failure occurs, avoiding power outages and allowing scheduled maintenance during non-critical periods rather than emergency repairs during outages.
Solution Approach 2:
The system establishes a feedback loop where sensor data is continuously collected, analyzed, and used to update the status of grid assets. This real-time feedback enables dynamic adjustment of maintenance schedules and prioritization of assets based on actual degradation levels, allowing utilities to respond to degradation as it occurs rather than relying on fixed inspection schedules.
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 early detection of equipment deterioration, reducing the likelihood of power outages by identifying potential issues before they cause significant disruptions.
Implementation Method 1
a pre-failure signature in the form of a radio-frequency (RF) signal may be broadcast into the airwaves due to arcing
Data Source
AI summary
A computer monitors a status of grid devices using sensor measurements. Sensor data is clustered using a predefined grouping distance value to define one or more sensor event clusters. A plurality of monitored devices is clustered using a predefined clustering distance value to define one or more asset clusters. A location is associated with each monitored device of the plurality of monitored devices. A distance is computed between each sensor event cluster and each asset cluster. When the computed distance is less than or equal to a predefined asset/sensor distance value for a sensor event cluster and an asset cluster, an asset identifier of the asset cluster associated with the computed distance is added to an asset event list. For each asset cluster included in the asset event list, an asset location of an asset is shown on a map in a graphical user interface presented in a display.