Abstract: A device abnormality diagnosis method for a device to be diagnosed constituting a plant includes: obtaining time-series data of a plurality of state amounts of the plant which are correlated to an abnormality of the device to be diagnosed; a step of obtaining abnormality diagnosis data on the plurality of state amounts by performing pre-processing on at least one state amount of the plurality of state amounts to exclude, from the time-series data on the state amounts, data of the at least one state amount obtained in an exclusion period which is at least a part of a transient state period during which the device to be diagnosed is affected by a state change of another constituent device of the plant; and a step of performing abnormality diagnosis on the device to be diagnosed on the basis of the abnormality diagnosis data of the plurality of state amounts.

Abstract: An operation information analyzer includes: an information collection unit 11 configured to collect event information on events that have occurred during operation of an apparatus 20 including a plurality of devices 21; an information analysis unit 12 configured to organize the collected event information to generate and store index values used to evaluate operation conditions of the apparatus 20; and an information presentation unit 13 configured to present the index values stored in the information analysis unit 12 to a user. The information analysis unit 12 generates the index values for each period sectioned based on a change in an operation state of the apparatus.

Abstract: An anomaly monitoring device is installed in an integrated gasification combined cycle plant that experiences varying loads, and the device monitors a heat exchanger that performs heat exchange between a carbon-containing fuel and a heat exchange medium flowing through a heat transfer tube. For each load on the integrated gasification combined cycle plant, the anomaly monitoring device calculates the average value and the standard deviation of a state quantity of the heat exchanger, calculates the Mahalanobis distance on the basis of the average value and the standard deviation, and from the calculated Mahalanobis distance determines the presence or absence of an anomaly of the heat transfer surface of the heat transfer tube.

Abstract: An operation information analyzer includes: an information collection unit 11 configured to collect event information on events that have occurred during operation of an apparatus 20 including a plurality of devices 21; an information analysis unit 12 configured to organize the collected event information to generate and store index values used to evaluate operation conditions of the apparatus 20; and an information presentation unit 13 configured to present the index values stored in the information analysis unit 12 to a user. The information analysis unit 12 generates the index values for each period sectioned based on a change in an operation state of the apparatus.

Abstract: A device abnormality diagnosis method for a device to be diagnosed constituting a plant includes: obtaining time-series data of a plurality of state amounts of the plant which are correlated to an abnormality of the device to be diagnosed; a step of obtaining abnormality diagnosis data on the plurality of state amounts by performing pre-processing on at least one state amount of the plurality of state amounts to exclude, from the time-series data on the state amounts, data of the at least one state amount obtained in an exclusion period which is at least a part of a transient state period during which the device to be diagnosed is affected by a state change of another constituent device of the plant; and a step of performing abnormality diagnosis on the device to be diagnosed on the basis of the abnormality diagnosis data of the plurality of state amounts.

Abstract: An anomaly monitoring device (10) is installed in an IGCC plant that experiences varying loads, and the device monitors a heat exchanger (20) that performs heat exchange between a carbon-containing fuel and a heat exchange medium flowing through a heat transfer tube (24). For each load on the IGCC plant, the anomaly monitoring device (10) calculates the average value and the standard deviation of a state quantity of the heat exchanger (20), calculates the Mahalanobis distance on the basis of the average value and the standard deviation, and from the calculated Mahalanobis distance determines the presence or absence of an anomaly of the heat transfer surface (28) of the heat transfer tube (24). Due to this configuration, the anomaly monitoring device (10) can more reliably detect an anomaly of the heat exchanger (20).

Abstract: This method of monitoring and operating a heat exchanger for fuels containing carbon has a process to calculate the Mahalanobis distance on the basis of temperatures in a plurality of locations in the direction of flow in a heat transfer face of a heat exchanger of a heat exchanger for fuels containing carbon, a process to determine the presence of an abnormality on the heat transfer face by way of the Mahalanobis distance, and a process to modify the operating conditions of a removing device.