The present invention relates to a method and a system for production accounting in process industries using Artificial Intelligence (AI). More particularly the present invention relates to fault detection in a plurality of measuring instruments and process equipment in a process plant. A plurality of measured signals from the measuring instruments is received by the process control system and noise is extracted from the plurality of measured signals. The extracted noise is correlated with a noise extracted from a plurality of reference signals using an AI based data analysis technique. Further, the process control system identifies deviations in the one or more parameters. The process control system detects the faults the plurality of measuring instruments or the process equipment using the correlated noises and the identified deviations of the one or more parameters.

An abnormality detection apparatus for working tools configured to be used in a machining process performed by a machine tool, the abnormality detection apparatus includes a storage portion which previously stores correlations between features of a plurality of operating portions relation to the machining process performed by the machine tool, and a tool condition of each of a plurality of working tool types, and a tool condition determining portion which determines the tool condition of the working tools based on the correlations.

The invention relates to a method for checking a time-discrete signal value of a sensor for freedom from errors, wherein the signal value of the sensor is converted into a first measured value and a second measured value by two different evaluating devices of an electronic system, wherein the first and second measured values are transmitted to a control system by the electronic system, and the control system calculates a first control signal from the first measured value and, in parallel thereto, a second control signal from the second measured value, wherein the control system comprises a comparator which compares the first control signal and second control signal to verify the identity thereof.

An abnormality detection apparatus for working tools configured to be used in a machining process performed by a machine tool, the abnormality detection apparatus includes a storage portion which previously stores correlations between features of a plurality of operating portions relation to the machining process performed by the machine tool, and a tool condition of each of a plurality of working tool types, and a tool condition determining portion which determines the tool condition of the working tools based on the correlations.

An online monitoring system for industrial processes, such as nuclear power processes, including a data acquisition unit configured to sample output signals simultaneously from a plurality of process sensors, and a computing unit configured to record sampled output signals from the data acquisition unit and to cross-correlate the output signals from two or more of the process sensors to diagnose operation of the industrial process, identify loose parts and/or degradation of industrial plant equipment, enable virtual sensing, calculate sensor response time using the noise analysis technique, and to verify sensor calibration using the cross calibration method and/or empirical and/or physical modeling.

The invention relates to a method for checking a time-discrete signal value of a sensor for freedom from errors, wherein the signal value of the sensor is converted into a first measured value and a second measured value by two different evaluating devices of an electronic system, wherein the first and second measured values are transmitted to a control system by the electronic system, and the control system calculates a first control signal from the first measured value and, in parallel thereto, a second control signal from the second measured value, wherein the control system comprises a comparator which compares the first control signal and second control signal to verify the identity thereof.