Predictive asset management for transmission and distribution
Aerial drone inspection with computer vision AI/ML processing enable predictive asset management
Emerging importance of predictive asset management for electric utilities
Power utility assets, which are often distributed across hundreds of square miles, often pose unique challenges when it comes to inspection and maintenance. New drone powerline inspection software capabilities combined with AI/ML image processing are making predictive asset management, an evolution beyond preventative maintenance, an attainable possibility for utilities.
Drones equipped with advanced sensors and high-resolution cameras can efficiently inspect geographically dispersed transmission and distribution networks, capturing asset component details with unparalleled precision. Drones can reach areas that are often inaccessible to humans, enabling comprehensive inspections without the associated risks and costs of traditional methods, and offer several advantages:
- Speed: What once took days can now be accomplished in hours, allowing for more frequent inspections and real-time data gathering.
- Safety: Drones eliminate the need for human technicians to navigate potentially hazardous areas, significantly reducing safety concerns.
- Cost-efficiency: Reduced manpower, lesser equipment, and quicker inspections translate to considerable cost savings for utilities.
Beyond visual imagery, drones can also gather additional predictive inspection data when outfitted with more sensors— from thermal imaging that detects overheating components to LiDAR that penetrates vegetation for seeing through the tree canopy. When integrated with Optelos’s platform, this data offers contextualized insights on the status of key equipment, facilitating more informed decision-making and predictive failure calls.
Complete the form to download our white paper, or follow the link below to request a personalized demo, program consultation or ask a question.
Download white paper
“Optelos delivered a solution that greatly improved our complex asset inspection and maintenance program across the entire organization and allowed us to manage and analyze our asset data like never before”
Matt Rachford Innovation Leader, Georgia Pacific
Visual AI and Machine Learning: Predicting Asset Failures
Inspection data processed and analyzed with the capabilities of visual AI and machine learning offers immediately actionable insights, offering the ability to predict failure based on decay modeling.
- Optelos’s platform, powered by advanced visual AI algorithms, processes drone-captured imagery to detect early signs of wear, degradation, and potential component failures. This allows utilities to identify and address issues before they escalate into service-impacting downtime, wildfires or safety incidents. The ability to pinpoint anomalies, from minor insulator cracks to worn conductors, provides a proactive approach to maintenance and repair.
- Machine learning thrives on data. As drones undertake more inspections and feed the system with more data, machine learning models evolve and improve their accuracy. This iterative learning ensures that predictions become sharper with every cycle, highlighting for maintenance organizations areas that require attention before failure, optimizing resource allocations, ensuring timely interventions and reducing systemic risks.
Integration with Existing Databases
A successful transition to predictive asset management hinges on seamless systems integrations, ensuring that utilities can leverage the full potential of drone-derived insights, SCADA and IoT data without overhauling their foundational data management infrastructure.
- Supervisory control and data acquisition (SCADA), diagnostic sensors and smart meters are effective predictive metrics for asset failures. Combining this data with AI-processed visual imagery can dramatically improve the accuracy of predictive models by adding physical assessments to performance metrics.
- Optelos’ open data APIs enable bidirectional interfaces with other Enterprise systems such as SAP, IBM Maximo and ServiceNow trouble ticketing, and many more. Optelos’ APIs provide access to AI/ML analyzed data to a wide variety of BI systems, enhancing enterprise decision support and improving organizational efficiency through automated workflows and actions.
Ticketing & Dispatch Integration
Use built in ticketing dashboards or integrate with your existing ticketing and dispatch systems through the Optelos Open Data APIs
- Seamlessly integrate with ticketing and dispatch systems to automate prioritized actions identified through vision AI predictive modeling.
- Automatically route detected issues to internal teams for further evaluation and prioritization.
- Optelos patented solution provides precise geolocation of all detected faults, speeding issue resolution.