Abstract: A corrosion monitoring system includes one or more objects coupled to respective portions of a transformer tank. The one or more objects are configured to corrode before the respective portions of the transformer tank. At least one optical sensor is coupled to each of the objects. The at least one optical sensor has an optical output that changes in response to strain of the object. An analyzer is coupled to the at least one optical sensor. The analyzer is configured to perform one or more of detecting and predicting corrosion of the transformer tank based on the output of the at least one optical sensor.

Abstract: An approach to detecting partial discharge events involves retrofitting an electrical system to include a capacitive sensor configured to capacitively sense partial discharge events of a component of the electrical system. The capacitive sensor has a first electrical conductor that forms a first terminal of the capacitive sensor, a second electrical conductor that forms a second terminal of the capacitive sensor, and a dielectric that separates the first electrical conductor and the second electrical conductor. The capacitive sensor generates an electrical sensor signal at an output of the capacitive sensor in response to the partial discharge event. The electrical sensor signal is converted to an optical signal and the optical signal is processed to detect an occurrence of the partial discharge event.

Abstract: A corrosion monitoring system includes one or more objects coupled to respective portions of a transformer tank. The one or more objects are configured to corrode before the respective portions of the transformer tank. At least one optical sensor is coupled to each of the objects. The at least one optical sensor has an optical output that changes in response to strain of the object. An analyzer is coupled to the at least one optical sensor. The analyzer is configured to perform one or more of detecting and predicting corrosion of the transformer tank based on the output of the at least one optical sensor.

Abstract: An approach to detecting partial discharge events involves retrofitting an electrical system to include a capacitive sensor configured to capacitively sense partial discharge events of a component of the electrical system. The capacitive sensor has a first electrical conductor that forms a first terminal of the capacitive sensor, a second electrical conductor that forms a second terminal of the capacitive sensor, and a dielectric that separates the first electrical conductor and the second electrical conductor. The capacitive sensor generates an electrical sensor signal at an output of the capacitive sensor in response to the partial discharge event. The electrical sensor signal is converted to an optical signal and the optical signal is processed to detect an occurrence of the partial discharge event.

Abstract: A corrosion monitoring system includes one or more objects coupled to respective portions of a transformer tank. The one or more objects are configured to corrode before the respective portions of the transformer tank. At least one optical sensor is coupled to each of the objects. The at least one optical sensor has an optical output that changes in response to strain of the object. An analyzer is coupled to the at least one optical sensor. The analyzer is configured to perform one or more of detecting and predicting corrosion of the transformer tank based on the output of the at least one optical sensor.

Abstract: Techniques for evaluating the accuracy of a predicted effectiveness of an improvement to an infrastructure include collecting data, representative of at least one pre-defined metric, from the infrastructure during first and second time periods corresponding to before and after a change has been implemented, respectively. A machine learning system can receive compiled data representative of the first time period and generate corresponding machine learning data. A machine learning results evaluator can empirically analyze the generated machine learning data. An implementer can implement the change to the infrastructure based at least in part on the data from a machine learning data outputer. A system performance improvement evaluator can compare the compiled data representative of the first time period to that of the second time period to determine a difference, if any, and compare the difference, if any, to a prediction based on the generated machine learning data.