Abstract: According to one embodiment, an anomaly sign detection system comprising one or more computers configured to: calculate a correction value for correcting at least one actual process value from the at least one actual process value and at least one reference process value; determine whether each of plurality of actual process values is correlated with the at least one reference process value or not, based on correction-necessity coefficient of determination; use the correction value for correcting at least one actual process value determined to be correlated with the at least one reference process value among the plurality of actual process values; generate learning input data including at least one corrected process value as the at least one actual process value corrected by the correction value; and perform machine learning by inputting the learning input data to anomaly sign detection model.

Abstract: An inductor component includes an element body including a magnetic layer containing a resin and a magnetic powder; a coil wiring line arranged inside the element body; and an insulating coating film covering the coil wiring line and not including a magnetic material. In a cross section perpendicular to an extension direction of the coil wiring line, a top surface thickness of a part of the insulating coating film covering the top surface of the coil wiring line and a side surface thickness of parts of the insulating coating film covering side surfaces of the coil wiring line are less than or equal to 10 ?m, and a corner thickness of parts of the insulating coating film that cover corners of the coil wiring line interposed between the top surface and the side surfaces is at least half of the top surface thickness and/or the side surface thickness.

Abstract: According to one embodiment, an anomaly detection apparatus includes a processing circuit. The processing circuit is configured to: acquire measured values from sensors installed in a system, a first function, a first threshold, and a second function to output a second threshold; generate the predicted values based on the measured value and the first function; detect that a deviation between the measured values and the predicted values exceeds the first threshold; calculate the feature quantities based on the measured values; and determine whether a number of consecutive times is equal to or larger than the second threshold to detect an anomaly or a sign of the anomaly.

Abstract: According to one embodiment, an abnormality sign detection system comprising one or more computers configured to perform machine learning of an abnormality-sign detection-model that detects at least one of an abnormality in a target facility to be monitored and a sign of the abnormality, wherein the one or more computers are configured to: acquire a plurality of process amounts generated at the target facility; classify each of the plurality of process amounts into either correlation data for which correlation between the plurality of process amounts is learned or decorrelation data for which correlation between the plurality of process amounts is not learned; generate learning input data depending on classification, the learning input data being data in which each of the plurality of process amounts is associated with the correlation data or the decorrelation data; and perform the machine learning by inputting the learning input data to the abnormality-sign detection-model.

Abstract: According to an embodiment, a monitoring apparatus configured to generate time-series predicted data based on time-series measured data and a prediction model that generates predicted data including one or more predicted values predicted to be output from one or more sensors; and generate, for a first sensor among the one or more sensors, a displayed image including a measured value graph representing a temporal change in a measured value included in the time-series measured data in a second period after a first period, a predicted value graph representing a temporal change in a predicted value included in time-series predicted data in the second period, past distribution information representing a distribution of a measured value in the first period, and measurement distribution information representing a distribution of the measured value included in the time-series measured data in the second period.

Abstract: According to one embodiment, a data processing apparatus includes a processor. The processor calculates, from the first measurement data, a first differential value set that is a set of first differential values in a time direction at a time included in the first period of the measurement values of the sensor of interest. The processor calculates, from the second measurement data, a second differential value set that is a set of second differential values in a time direction at a time included in the second period of the measurement values of the sensor of interest. The processor generates a first differential value distribution and a second differential value distribution using the second differential value set.

Abstract: According to one embodiment, a processing circuit classifies a time-series data corresponding to process amounts generated in a target facility into groups. For each of groups, the processing circuit applies time-series data included in the group to a first auto-encoder, which differs depending upon each group, and outputs time-series data. The processing circuit applies input difference data, which are based on output time-series data on the process amounts and the input time-series data, to a single second auto-encoder, and outputs difference data. The processing circuit determines an abnormality of the target facility, based on the comparison between addition data which are based on the output difference data and the output time-series data, and the input time-series data.

Abstract: According to an embodiment, a monitoring apparatus configured to generate time-series predicted data based on time-series measured data and a prediction model that generates predicted data including one or more predicted values predicted to be output from one or more sensors; and generate, for a first sensor among the one or more sensors, a displayed image including a measured value graph representing a temporal change in a measured value included in the time-series measured data in a second period after a first period, a predicted value graph representing a temporal change in a predicted value included in time-series predicted data in the second period, past distribution information representing a distribution of a measured value in the first period, and measurement distribution information representing a distribution of the measured value included in the time-series measured data in the second period.

Abstract: According to one embodiment, each of driving mechanisms is differently connected to one of control rods located in a nuclear reactor. A driving mechanism drives a connected control rod to be inserted and withdrawn with a high-pressure driving water by opening and closing control valves thereof. Driving time data of unlatch, insertion, withdrawal and settle of each control rod, is stored. The driving time data is measured by a test of insertion and withdrawal at a periodical inspection before starting operation of the nuclear reactor. At least one is selected from the control rods, based on a command to select and drive a control rod. A timing table that prescribes timings to open and close each control valve to unlatch, insert, withdraw and settle the selected control rod, is created based on the driving time data thereof. The selected control rod is driven based on the timing table.

Abstract: According to one embodiment, each of driving mechanisms is differently connected to one of control rods located in a nuclear reactor. A driving mechanism drives a connected control rod to be inserted and withdrawn with a high-pressure driving water by opening and closing control valves thereof. Driving time data of unlatch, insertion, withdrawal and settle of each control rod, is stored. The driving time data is measured by a test of insertion and withdrawal at a periodical inspection before starting operation of the nuclear reactor. At least one is selected from the control rods, based on a command to select and drive a control rod. A timing table that prescribes timings to open and close each control valve to unlatch, insert, withdraw and settle the selected control rod, is created based on the driving time data thereof. The selected control rod is driven based on the timing table.

Abstract: The feedwater controller of a nuclear power plant having three or more feedwater pumps supplying water to the reactor vessel, electric motors driving the feedwater pumps and electric power converters connected to the electric motors is equipped with a flow rate controller and a trip compensation means. The flow rate controller calculates a flow rate to the reactor vessel based on a detected value indicating a condition of the nuclear power plant and a preset value of the water level of the reactor vessel, and generates a rotation speed command signal for the electric motors based on the flow rate command signal. The trip compensation means increases the rotation speed of the electric motors not having tripped if one of the feedwater pumps trips.

Abstract: The feedwater controller of a nuclear power plant having three or more feedwater pumps supplying water to the reactor vessel, electric motors driving the feedwater pumps and electric power converters connected to the electric motors is equipped with a flow rate controller and a trip compensation means. The flow rate controller calculates a flow rate to the reactor vessel based on a detected value indicating a condition of the nuclear power plant and a preset value of the water level of the reactor vessel, and generates a rotation speed command signal for the electric motors based on the flow rate command signal. The trip compensation means increases the rotation speed of the electric motors not having tripped if one of the feedwater pumps trips.

Abstract: A can lid for a can, including a top plate to which a tab having a tab nose is coupled by a rivet at the substantial center thereof, a tab nose recess formed in the top plate underneath the tab nose and having a smooth bottom surface with no step part, and a score formed in the top plate surrounding around the tab nose recess and having a start point and an end point located in front of the rivet and defining therebetween a hinge space.

Abstract: A coil assembly comprises a plurality of conductive spiral pattern layers which are piled up via (an) insulating layer(s) on a wafer. The electrical connection between the spiral patterns is established by means of a conductive member, which is a portion of the upper spiral pattern layer, filled in a through-hole which is made in the insulating layer so that the spiral patterns are connected in series to develop a high voltage when the coil assembly is moved in a magnetic field.