Machine fault diagnostics system and method

A method for diagnosing a physical machine or process, the method comprising the steps of:

• (1) acquiring a first set of data from the physical machine or process;
• (2) preprocessing said first set of data using an autoregressive model, said preprocessing generating an autoregressive parameter;
• and
• (3) detecting abnormal conditions in said autoregressive parameter using an overall root means square (RMS) measurement and a covariance statistic of an exponentially weighted moving average (EWMA), wherein if an abnormal condition is detected then,
• (a) identifying whether said physical machine or process has a fault, including,
• (i) determining a hypothesis with the aid of a fault diagnostic network, and if said fault diagnostic network cannot generate a hypothesis, then
• (ii) determining a hypothesis with the aid of a model-based reasoning approach, wherein said model-based reasoning approach uses fuzzy logic;
• and
• (b) supplying said identifiable fault to a fault expert system having a knowledge base with a set of rules, wherein said fault reasoning expert system checks said identifiable fault against said set of rules.