Intelligent analysis system and method for fluid-filled electrical equipment

An intelligent analysis apparatus for fluid-filled electrical transformers, said apparatus comprising:

• plural sensors adapted to be coupled to a transformer having a containment vessel configured to contain a fluid and coil disposed in said containment vessel, said sensors being configured to output signals indicative of plural operating parameters of the transformer;
• and
• a diagnostic device coupled to said sensors, said diagnostic device having a processor operative to determine operating characteristics of the transformer based on at least one analytical model of the transformer and the signals outputted by said sensors by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the signals of said sensors in a causal network, wherein said diagnostic device compares a parameter calculated by the at least one analytical model with a corresponding measured parameter and uses a result of the comparison as an indicator in the causal network, and further wherein probabilities of the causal network are adjusted based on the probability of the indicators obtained from the analytical model or sensed parameters;
• and still further wherein the at least one analytical model is adjusted over time in correspondence to acceptable behavioral changes of the transformer over time.

An intelligent analysis apparatus for fluid-filled electrical equipment of the type having components surrounded by fluid, said apparatus comprising:

• sensing means for sensing plural operating parameters of electrical equipment having a containment vessel configured to contain a fluid and at least one electrical component disposed in said containment vessel and for outputting signals indicative of the plural operating parameters of said electrical equipment;
• and
• diagnostic means for determining operating characteristics of the electrical equipment based on at least one analytical model of the electrical equipment and the signals outputted by said sensing means by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the signals of said sensing means in causal network, wherein said diagnostic means comprises means for comparing a parameter calculated by the at least one analytical model with a corresponding measured parameter and means for using a result of the comparison as an indicator in the causal network, and further wherein said diagnostic means comprises means for adjusting probabilities of the causal network based on the probability of the indicators obtained from the analytical model or sensed parameters;
• and still further wherein said diagnostic means comprises means for adjusting variables of the at least one analytical model over time in correspondence to acceptable behavioral changes of the electrical equipment over time.

A method for intelligent analysis of fluid-filled electrical equipment of the type having components surrounded by fluid, said method comprising the steps of:

• coupling plural sensors to electrical equipment having a containment vessel configured to contain a fluid and at least one electrical component disposed in said containment vessel;
• sensing plural operating parameters of the electrical equipment with the sensors;
• generating signals indicative of the plural operating parameters of the electrical equipment sensed in said sensing step;
• and
• determining operating characteristics of the electrical equipment based on at least one analytical model of the electrical equipment and the signals generated in said generating step by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the generated in said generating step in a causal network, wherein said determining step comprises the steps of comparing a parameter calculated by the at least one analytical model with a corresponding measured parameter as indicated by signals in said generating step and using a result of said comparing step as an indicator in the causal network, and further wherein said determining step comprises the step of adjusting the probabilities of the causal network based on the probability of the indicators obtained from the analytical model or sensed parameters;
• and still further wherein said determining step comprises the step of adjusting variables of the at least one analytical model over time in correspondence to acceptable behavioral changes of the electrical equipment over time.