System and method for predicting industrial equipment motor behavior

A system comprising:

• a non-transitory computer-readable medium with instructions encoded thereon, wherein the medium is configured to predict a behavior of a motor;
• and one or more processors configured to, when executing the instructions, perform operations of:
• determining a plurality of predictive machine learning models;
• receiving input values from at least one sensor, said at least one sensor is configured to receive operational data from the motor;
• updating a probability of a plurality of operational outcome of the motor for each of a unit time stamp within a predetermined time period, comprising:
• calculating a percentage of input values that are correct;
• removing, at random, a plurality of input values corresponding to the percentage that are incorrect;
• calculating a mean square prediction error value from the input values not removed;
• calculating a weight of each of the plurality of predictive machine learning models;
• determining an upper bound and a lower bound of the input values not removed;
• calculating a counter value for each of the plurality of predictive machine learning models;
• updating the weight of each of the plurality of predictive machine learning models;
• calculating a normal probability;
• updating the upper bound and lower bound of the input values not removed;
• updating the normal probability based on the updated upper bound and updated lower bound of the input values not removed;
• calculating the probability of a plurality of operational outcomes of the motor;
• predicting the behavior of the motor for said unit time stamp;
• and transferring data respecting the predicted behavior of the motor to at least one of a personal computer (PC) and a smart phone.