Introducing TOAN: Qualitrol's transformer oil analysis and notification system
TOAN - Transformer Oil Analysis and Notification - is the first entirely new DGA diagnostic tool to emerge in recent years. It allows the user to move away from alarming on DGA gas levels or rate of change and towards alarming only when an actual fault is developing.
Automatically creates ACTIONABLE INFORMATION from large volumes of data
Notifies the users only when a fault is present, thereby filtering out FALSE ALARMS
Uses DATA MINING techniques to let the data tell you the trends
Advanced fault alarming and diagnostics for your critical assets
The concepts that underline TOAN have been developed around advanced computational techniques to solve the “big data” issues associated with wide scale deployment of online DGA monitors.
Developed by an expert team at an electrical utility in the USA, Serveron now offer TOAN as an optional plug-in to the groundbreaking TM View™ software suite. TOAN has been specifically designed for utilities where availability of me and or DGA expertise is inadequate. It provides a platform to move away from day to day analysis of DGA data and towards automatic alarming on real faults.
Virtually eliminating false alarms, TOAN simplifies the task of supervision of DGA monitors. TOAN can analyse data from large or small populations of online DGA monitors, automatically detecting faults and providing accurate diagnosis while minimising the false alarms often associated with Rate of Change and PPM alarm settings.
TOAN is available as a plug-in application in Serveron’s DGA monitoring platform TM View. TM View provides a broad range of diagnostic and trending capabilities as standard and free of charge with all Serveron DGA monitors. TOAN may be activated within TM View on purchase of a license key.
TOAN DGA diagnostic tool allows asset managers to:
Automate
Automate the monitoring of DGA data.
Notify
Receive notification of abnormalities in near-real time.
Prevent
Take actions necessary to prevent outages or more transformer failure.
4 fault conditions are identified by TOAN
The severity of the fault category is assigned and rated within a 6-level scale, with 1 being the most severe. The four fault conditions identified are:
HEDA: High Energy Discharge
LED: Low Energy Discharge
OHO: Over Heated Oil
CD: Cellulose Decomposition
The application window shows the final score and recommendation for the monitor, then the individual scores for each fault types.
The weight values represent the ANN scores for each fault type. These values are between 0 and 1 and represent likeliness for that type of fault, as determined by the neural network analysis.
Notifications can be customised by fault category and severity to enable exception-based analysis.
A rule-based step at the end of the analysis yields a final 'score' for that transformer. If the score is not within an acceptable range, an alarm is triggered and emails can be sent to selected users of the system.
A step change in DGA analytics
The availability of TOAN as a tool for automated DGA analysis represents one of the most significant changes in DGA diagnostics in the last decade.
While Duval and others continue to expand, and improve ratio based methods that in the right hands are powerful and effective, alarming on faults, not ppm, is more appropriate where in-house expertise is not available. Apart from the ability to identify a specific fault condition, the prospects of being able to handle large populations of online monitors automatically makes ANNs and in this case, TOAN, a step change in DGA analytics.
Summary
Diagnostic methods are emerging that are much more sophisticated than the traditional ratio based systems. In the form of TOAN, asset managers have a powerful new tool for managing large volumes of DGA.
If this sounds like something that could help your transformer fleet, get in touch with our team to find out more.