Method and apparatus for performing pre-emptive maintenance on operating equipment

A method of evaluating operating equipment to determine a maintenance requirement, comprising the steps of:

• sensing a plurality of operating parameters of said operating equipment, including sensing ambient temperature, equipment operating load, and vibration and producing respective data signals;
• performing a learning operation on the data signals using statistical processing;
• deriving a plurality of operating norms based on results of said statistical processing;
• utilizing statistical inference and fuzzy logic for analyzing the data signals based on the derived plurality of operating norms and producing a failure probability conclusion;
• transmitting the failure probability conclusion to a location remote from the operating equipment;
• and
• displaying the transmitted failure probability conclusion.

A method of determining maintenance requirements for an operating system including at least one machine, comprising the steps of:

• obtaining operating data from the system during operation including obtaining vibration data, operating load data, and ambient temperature data;
• forming obtained data into a raw data table;
• repeating the steps of obtaining and forming over a first set period of time to produce hourly data;
• storing the produced hourly data;
• performing learning mode calculations from the stored hourly data, including calculating upper and lower confidence intervals using stored hourly data representing a second set period of time;
• determining data values within the upper and lower confidence levels evidencing correct system operation;
• performing monitoring mode calculations by comparing present raw data with the data values evidencing correct system operation;
• and
• displaying to a user results of the step of comparing.