Estimating the remaining useful life of a power transformer based on real-time sensor data and periodic dissolved gas analyses

A non-transitory, computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for estimating a remaining useful life (RUL) of a power transformer, the method comprising:

• during a surveillance mode, iteratively performing the following operations:
• receiving a set of present time-series signals gathered from sensors in the power transformer,
• using an inferential model to generate estimated values for the set of present time-series signals,
• performing a pairwise differencing operation between actual values and the estimated values for the set of present time-series signals to produce residuals,
• performing a sequential probability ratio test (SPRT) on the residuals to produce SPRT alarms having associated tripping frequencies (TFs),
• using a logistic-regression model to compute an RUL-based risk index for the power transformer based on the TFs;
• and
• when the risk index exceeds a risk-index threshold, generating a notification indicating that the power transformer needs to be replaced;
• and
• periodically updating the logistic-regression model based on the results of periodic dissolved gas analyses (DGAs) for the transformer to more accurately compute the RUL-based index for the power transformer.

A system that estimates a remaining useful life (RUL) of a power transformer, comprising:

• at least one processor and at least one associated memory;
• and
• a notification mechanism that executes on the at least one processor, wherein during a surveillance mode, the notification mechanism:
• receives a set of present time-series signals gathered from sensors in the power transformer,
• uses an inferential model to generate estimated values for the set of present time-series signals,
• performs a pairwise differencing operation between actual values and the estimated values for the set of present time-series signals to produce residuals,
• performs a sequential probability ratio test (SPRT) on the residuals to produce SPRT alarms having associated tripping frequencies (TFs),
• uses a logistic-regression model to compute an RUL-based risk index for the power transformer based on the TFs;
• and
• when the risk index exceeds a risk-index threshold, generates a notification indicating that the power transformer needs to be replaced;
• wherein the notification mechanism periodically updates the logistic-regression model based on the results of periodic dissolved gas analyses (DGAs) for the transformer to more accurately compute the RUL-based index for the power transformer.