Abstract: A method of monitoring a plant by using a Mahalanobis distance calculated from data of a plurality of variables each of which indicates a state of the plant includes: a dividing step of dividing a range of a single variable which indicates a state of the plant into a plurality of first range bands on the basis of a frequency distribution of the single variable; and a unit space creating step of creating a plurality of unit spaces which serve as a basis of calculation of the Mahalanobis distance on the basis of the respective data of the plurality of variables respectively corresponding to a plurality of second range bands of the single variable determined on the basis of the plurality of first range bands.

Abstract: A plant monitoring device (20) is provided with: a detection value acquisition unit (211) that acquires a bundle of detection values; a first Mahalanobis distance calculation unit (212) that calculates a first Mahalanobis distance by using as a reference a unit space generated on the basis of a bundle of past detection values; a first SN ratio calculation unit (214) that calculates a first SN ratio for each of a plurality of evaluation items; a second Mahalanobis distance calculation unit (215) that calculates a second Mahalanobis distance by increasing or decreasing each of the detection values; a second SN ratio acquisition unit (216) that converts the first SN ratio for each of the evaluation items and acquires a second SN ratio on the basis of the first and second Mahalanobis distances; and an addition unit (217) that calculates an added value of a plurality of the second SN ratios acquired within a prescribed period for each of the evaluation items.

Abstract: A plant monitoring method using a Mahalanobis distance calculated from data of a plurality of variables indicating the state of the plant. The plant monitoring method includes: acquiring data in a first period in the past up to the current point of time as first data; predicting data in a second period from the current point of time as second data; and creating, on the basis of the first data and the second data, a unit space that serves as a base for calculating the Mahalanobis distance. In the prediction step, the second data is predicted on the basis of: data in a third period obtained, as third data, by shifting the first period to the past by a prescribed period; data in a fourth period obtained, as fourth data, by shifting the second period to the past by the prescribed period, and the first data.

Abstract: Provided are a diagnosing device, a diagnosing method, and a program with which it is possible to detect abnormalities accurately even if there is a small amount of data or the number of data points varies. This diagnosing device is provided with a Mahalanobis distance calculating unit which calculates the Mahalanobis distance (referred to as ‘MD value’ hereinbelow) of a detected value, and an abnormality determining unit which determines the presence or absence of an abnormality on the basis of the MD value, wherein the abnormality determining unit determines the presence or absence of an abnormality by arranging that a determination that there is no abnormality is more likely to occur if the number of samples per unit space is small than if the number of samples per unit space is large.

Abstract: A unit space update device, which generates a unit space, includes: a detection value acquisition unit which acquires a bundle of detection values detected at a constant cycle; and a deletion processing unit which deletes one bundle from the bundles of the detection values constituting the unit space, when adding the bundle of the detection values to the unit space. The deletion processing unit includes at least one among: a first processing unit which randomly deletes one bundle from the bundles of the detection values forming the unit space; and a second processing unit which, with respect to the detection value of the predetermined evaluation item among the plurality of evaluation items, deletes any one bundle of the bundles including the detection value with the highest appearance frequency in the unit space, or one of two bundles having the smallest difference between the detected values in the unit space.

Abstract: An acquisition unit acquires a bundle of detection values for each of a plurality of sensor values pertaining to a plant. A distance calculation unit obtains the Mahalanobis distance of the bundle of detection values acquired by the acquisition unit using, as reference, a unit space constituted by a collection of bundles of detection values for each of the plurality of sensor values. A determining unit determines, based on whether the Mahalanobis distance is at or within a prescribed threshold, whether the operation state of the plant is normal or abnormal. A trend specification unit specifies a trend with regards to at least one sensor value. An abnormality cause estimation unit estimates an abnormality cause based on the trend for the sensor value(s), and a fault site estimation database for holding the relationship between abnormality causes that may occur in the plant and sensor values for each of the trends.

Abstract: A plant monitoring device (20) is provided with: a detection value acquisition unit (211) that acquires a bundle of detection values; a first Mahalanobis distance calculation unit (212) that calculates a first Mahalanobis distance; a plant state determination unit (213) that determines whether the operation state of a plant is normal or abnormal; a cause detection value estimation unit (214) that estimates a cause detection value which represents a cause of the abnormality of the plant; a second Mahalanobis distance calculation unit (215) that calculates a second Mahalanobis distance by increasing or decreasing the detection value estimated as the cause detection value; and an identification unit (216) that identifies whether the abnormality can be relieved by increasing or decreasing the detection value estimated as the cause detection value.

Abstract: Provided are a diagnosing device, a diagnosing method, and a program with which it is possible to detect abnormalities accurately even if there is a small amount of data or the number of data points varies. This diagnosing device is provided with a Mahalanobis distance calculating unit which calculates the Mahalanobis distance (referred to as ‘MD value’ hereinbelow) of a detected value, and an abnormality determining unit which determines the presence or absence of an abnormality on the basis of the MD value, wherein the abnormality determining unit determines the presence or absence of an abnormality by arranging that a determination that there is no abnormality is more likely to occur if the number of samples per unit space is small than if the number of samples per unit space is large.

Abstract: A plant monitoring device (20) is provided with: a state quantity acquiring unit (211) which acquires state quantities for each of a plurality of characteristic items relating to a plant; an abnormality degree calculating unit (212) which calculates a degree of abnormality representing a degree of approach toward an abnormal side relative to a limit value that is predetermined for each characteristic item, for the state quantities acquired at a plant monitoring timing; a distance calculating unit (213) which uses a statistical technique to calculate distances representing the degrees of separation, from the normal operating state of the plant, of the state quantity and the degree of abnormality acquired at the monitoring timing; and a determining unit (214) which determines the operating state of the plant on the basis of the calculated distances.

Abstract: A unit space generating device (141) which generates a unit space for use when diagnosing an operating state of a plant on the basis of a Mahalanobis distance is provided with: a sampling data acquiring unit (141A) which acquires a sampling data group comprising a plurality of state quantities of the plant, measured with a fixed period; an adoption determining unit (141C) which, on the basis of an adoption probability calculated each time the sampling data group is acquired, determines whether the sampling data group is to be adopted as a unit space generation data group serving as the basis for a unit space; a unit space generating unit (141D) which generates unit spaces on the basis of a plurality of the adopted unit space generation data groups; and an output value acquiring unit (141B) which acquires an output value of the plant corresponding to the sampling data group.

Abstract: A plant monitoring device (20) is provided with: a detection value acquisition unit (211) that acquires a bundle of detection values; a first Mahalanobis distance calculation unit (212) that calculates a first Mahalanobis distance; a plant state determination unit (213) that determines whether the operation state of a plant is normal or abnormal; a cause detection value estimation unit (214) that estimates a cause detection value which represents a cause of the abnormality of the plant; a second Mahalanobis distance calculation unit (215) that calculates a second Mahalanobis distance by increasing or decreasing the detection value estimated as the cause detection value; and an identification unit (216) that identifies whether the abnormality can be relieved by increasing or decreasing the detection value estimated as the cause detection value.

Abstract: A unit space update device, which generates a unit space, includes: a detection value acquisition unit which acquires a bundle of detection values detected at a constant cycle; and a deletion processing unit which deletes one bundle from the bundles of the detection values constituting the unit space, when adding the bundle of the detection values to the unit space. The deletion processing unit includes at least one among: a first processing unit which randomly deletes one bundle from the bundles of the detection values forming the unit space; and a second processing unit which, with respect to the detection value of the predetermined evaluation item among the plurality of evaluation items, deletes any one bundle of the bundles including the detection value with the highest appearance frequency in the unit space, or one of two bundles having the smallest difference between the detected values in the unit space.

Abstract: A unit space generating device (141) which generates a unit space for use when diagnosing an operating state of a plant on the basis of a Mahalanobis distance is provided with: a sampling data acquiring unit (141A) which acquires a sampling data group comprising a plurality of state quantities of the plant, measured with a fixed period; an adoption determining unit (141C) which, on the basis of an adoption probability calculated each time the sampling data group is acquired, determines whether the sampling data group is to be adopted as a unit space generation data group serving as the basis for a unit space; a unit space generating unit (141D) which generates unit spaces on the basis of a plurality of the adopted unit space generation data groups; and an output value acquiring unit (141B) which acquires an output value of the plant corresponding to the sampling data group.

Abstract: An analysis system which permits sample pretreatment which comprises: a sample rack; a sample container supply, a sample dispenser, a solvent-removing evaporator, a solvent dispenser for dispensing a second solvent, a sample-stirring means, a sample aspirating-and-transferring means, a sample recovery means, a sample container recovery means, and a control means for controlling the aforementioned various means.

Abstract: An analysis system which permits sample pretreatment which comprises: a sample rack; a sample container supply, a sample dispenser, a solvent-removing evaporator, a solvent dispenser for dispensing a second solvent, a sample-stirring means, a sample aspirating-and-transferring means, a sample recovery means, a sample container recovery means, and a control means for controlling the aforementioned various means.

Abstract: The present invention provides a plurality of transmitter/receiver coils instead of a single transmitter/receiver coil heretofore used. RF pulses containing the resonance frequency of a nuclide to be observed are successively supplied to these coils. The resultant resonance signals are stored and accumulated individually for the separate transmitter/receiver coils to obtain visual information with a high signal-to-noise ratio in a short time.