The invention provides an equipment fault forecasting method based on a multi-dimension time sequence. A data excavation method based on the multi-dimension time sequence is provided according to highly densely sampled on-line operating electric measurement data in a power system, a variation feature of other equipment related to the fault, namely a 'precursor event' is excavated according to a historical time sequence training data building and time sequence decomposition algorithm, a feature event generation algorithm and a fault relationship excavation algorithm based on relation rules, the relation forms an equipment fault forecasting model, and powerful support is provided for fault forecasting and judgment of complex non-linear electric equipment through combination with on-line monitoring data. By means of the electric equipment fault forecasting method based on the multi-dimension time sequence, faults or impact possibly striking on the core equipment of a power enterprise is forecast in advance by effectively using the massive high-density operating monitored historical data of the equipment, and prevention measures are taken in time to avoid the faults and impact.