Mitsubishi Heavy Industries Limited

Mitsubishi Nichiyu Forklift Co., Ltd.

Mitsubishi Power, Ltd.

Mitsubishi Heavy Industries Machinery Systems, Ltd.

Takaharu Hiroe

Kazunari Ide

Ryo Sase

Yoshikatsu Ikawa

Kensuke Futahashi

Koki Tateishi

Tomohide Yamada

Yukihito Okuda

Hiroshi Ito

Satoshi Hada

Shinichi Yoshioka

Akihiko Saito

Hiroyoshi Kubo

Keisuke Mori

Hideyuki Watanabe

Hiroshi Ishibuchi

Ryuji Takenaka

Kiyomitsu Ogawa

Yusuke Hazui

Masataka Kawaguchi

Yoshimi Okazaki

Koshiro Fukumoto

Ryota Adachi

Akira Ogino

Tomohiro Akaki

Akihiro Maekawa

Kei Moriyama

Nobuhiro Osaki

Hiroyuki Iiyama

Tadashi Murata

Toshio Ishiwaki

Makoto Sakuno

Tomohiro Doi

Yoshito Nagahama

Hiroshi Kitayama

Shoichiro Hosomi

Yasunobu Igashima

Ren Ishii

A settlement device includes a measured value acquisition unit to acquire a measured value of active power transmitted or received at a connection point of a power transmission and distribution network and a regulating power providing means capable of providing regulating power to the power transmission and distribution network and a measured value of a frequency at the connection point; a regulating power measurement unit to measure regulating power at the connection point on the basis of the acquired measured value of the active power and the acquired measured value of the frequency; a regulating power amount calculation unit to calculate an amount of regulating power of a prescribed period at the connection point by integrating the regulating power over time; a power amount acquisition unit to acquire an amount of power transmitted or received in the prescribed period at the connection point; and a settlement unit.

Measurement device, measurement system, measurement method, and non-transitory computer readable medium for determining settlement for compensating a user for power received or provided

A control apparatus is configured to control driving of a power generation apparatus including a motor and a power generator. The control apparatus includes a processor configured to calculate: (i) a first adjustment force command value for controlling the motor in accordance with a deviation between an observed value and a reference value of a rotation speed of the power generator; (ii) a correction value for compensating for a delay of an electric output of the power generator; and (iii) a second adjustment force command value for controlling the motor by adding the first adjustment force command value and the correction value.

Control apparatus, control method, and non-transitory computer readable medium

In a granular material supply system including a tank that stores granular material, a carrier line through which the granular material flowing out of the tank is carried to a carrier destination, and a cutout line that connects the tank and the carrier line and through which the granular material flowing out of the tank is supplied to the carrier line, a control device includes a density control unit configured to control a density of the granular material on a downstream side of a junction of the cutout line and the carrier line to a set value predetermined and a flow rate control unit configured to control a flow rate of the granular material to be supplied to the carrier destination through the carrier line to a command value instructed by the carrier destination.

Control device, granular material supply system, control method, and program

A startup control device for adjusting a startup schedule during startup of a power generation plant, the device includes: a determining unit which determines, on the basis of a predicted value of a physical quantity corresponding to the elapsed time from startup when the power generation plant has started up on the basis of a prescribed optimal startup schedule, and an observed value of the physical quantity acquired during the startup of the power generation plant, whether the observed value will exceed the predicted value. The device also includes a speed adjusting unit which, if the determining unit determines that the observed value will exceed the predicted value, issues an instruction to decelerate the speed of progress of elapsed time from the startup in the optimal startup schedule; and a startup timer which progresses the elapsed time from the startup at a speed based on the instruction.

Startup control device, startup control method, and program

The corrugated cardboard sheet manufacturing system including a production state information acquisition device; a control value information acquisition device for acquiring control value information of a control element of a corrugated cardboard sheet manufacturing apparatus exerting an influence on the warp of a corrugated cardboard sheet; a warp information acquisition device for acquiring information of a warp amount of the corrugated cardboard sheet; a storage device for storing a performance data set including at least production state information, the control value information, and the warp information; a pre-control table storing a standard control value of the control element set in accordance with a production state; a correction table for correcting the standard control value to set an initial control value; an update device for updating the correction table by reflecting the performance data set; and control device for performing feedforward control of the control element using the initial control value.

Corrugated cardboard sheet manufacturing system

A control apparatusthat is configured to control driving of a power generation apparatus including a motor and a power generator, the control apparatus including a processorexecuting: a process of calculating a first adjustment force command value used for controlling the motor in accordance with a deviation between an observed value and a reference value of a rotation speed of the power generator; a process of calculating a correction value for compensating for a delay of an electric output of the power generator; and a process of calculating a correction value for compensating for a delay of an electric output of the power generator; and a process of calculating a second adjustment force command value used for controlling the motor by adding the first adjustment force command value and the correction value.

An abnormality detection device that detects an abnormality of a target device includes a processor that executes a process of acquiring a plurality of types of measured values of the target device, a process of calculating Mahalanobis distances of the acquired plurality of types of measured values, a process of extracting the plurality of Mahalanobis distances calculated in a past predetermined period from a point in time of evaluation of the target device and calculating a moving average value of a square value of each of the extracted Mahalanobis distances, and a process of determining whether or not an abnormality has occurred in the target device on the basis of the moving average value.

Abnormality detection device, abnormality detection method, and non-transitory computer-readable medium

An abnormality detecting apparatus that is configured to detect a presence or absence of an abnormality in a rotating machine includes a processor that is configured to execute a measured value acquisition process of acquiring, on the basis of a detection signal output from a vibration sensor that is configured to measure vibration caused by rotation of the rotating machine, a measured value including an amplitude and a phase of the vibration; a Mahalanobis distance calculation process of calculating a Mahalanobis distance of the measured value acquired at a time point at which the rotating machine is evaluated on the basis of a unit space configured with a plurality of measured values acquired at a plurality of past time points; and a determination process of determining that an abnormality has occurred in the rotating machine in a case where the calculated Mahalanobis distance exceeds a predetermined threshold value.

Abnormality detecting apparatus, rotating machine, abnormality detection method, and non- transitory computer readable medium

An anomaly detecting device includes: a singular value decomposition unit configured to perform singular value decomposition of a variance-covariance matrix of a measured value matrix ycomposed of measured values acquired by a plurality of sensors in a time period considered to be normal, to thereby calculate a singular vector U and a singular value matrix S; an anomaly determination unit configured to apply the singular vector U and the singular value matrix S to a measured value matrix yto be evaluated and which is acquired in an arbitrary time period to determine whether an anomaly is present from a result of application; and an anomalous part identification unit configured to, when the measured value matrix yis determined to be anomalous, identify an anomalous part based on a diagonal element of a matrix obtained in association with the measured value matrix y.

Anomaly detecting device, anomaly detection method and program

An adjusting power measuring apparatus includes: a processor that: acquires an active power measurement value of active power exchanged at a connection point between a targeted power grid and an adjusting power supply source that supplies adjusting power to the targeted power grid, acquires a frequency measurement value of frequency at the connection point, calculates, based on the active power measurement value and the frequency measurement value, a first adjusting power coefficient indicating a degree of influence that fluctuation in the active power has on fluctuation in the frequency, calculates, based on the first adjusting power coefficient and a fluctuation measurement value of the fluctuation in the frequency, the adjusting power supplied from the adjusting power supply source to the targeted power grid, and determines, based on the calculated adjusting power, compensation to be paid to an owner of the adjusting power supply source.

Adjusting power measuring apparatus, adjusting power measuring system, and measuring instrument

A signal processing apparatus includes a CPU which executes an input step of receiving an input of a measurement value of a target parameter at a first time, in which noise is superimposed on a true value of the target parameter, a calculation step of calculating a variation amount of the measurement value of the target parameter at the first time, based on a maximum likelihood estimate of the target parameter at a second time and calculating a maximum likelihood estimate of the variation amount, and an output step of outputting a value obtained by adding the maximum likelihood estimate of the variation amount to the maximum likelihood estimate of the target parameter at the second time, as a maximum likelihood estimate of the target parameter at the first time.

Signal processing apparatus, turbine system, signal processing method, and program

A control device is configured to control a temperature of a shaft seal portion around a rotating shaft of a rotating machine by adjusting an amount of cooling air to be supplied to the shaft seal portion. The control device is configured to calculate a sensitivity indicated using the temperature of the shaft seal portion with respect to a flow rate of the cooling air supplied to the shaft seal portion and control the flow rate of the cooling air so that the sensitivity has a predetermined target value based on the sensitivity which has been calculated. When the sensitivity is calculated, the flow rate is varied in a predetermined range having a certain flow rate as a center. The sensitivity is calculated from variation in the temperature of the shaft seal portion with respect to variation in the flow rate.

Control device, gas turbine, control method, and program

A control device () of a plant which controls operation amounts of a plurality of types of equipment constituting the plant, the control device includes a prediction model deriving unit () that derives a prediction model from which a monitoring target value is output, an adjustment amount calculating unit () that calculates adjustment amounts of operation amounts in the case where the monitoring target value becomes a desired value and calculates differences between the operation amounts of existing control and the calculated operation amounts as first adjustment amounts, a constraint condition setting unit () that sets constraint conditions based on a measurement value and operation conditions of the plant, and an operation amount calculating unit () that calculates second adjustment amounts to which the constraint conditions are applied and calculates a plurality of the adjusted operation amounts based on each of the calculated second adjustment amounts.

Control device, control method and computer readable medium for controlling plant based on prediction model and constraint condition

An abnormality detection device includes a processor and a storage unit connected to the processor. The processor is configured to execute an error vector acquisition process of acquiring an error vector representing a difference between a measurement value vector having multiple measurement values measured at a determination time as elements and an average value vector having an average value of the measurement values accumulated in the storage unit as an element, a component acquisition process of acquiring a plurality of components into which the error vector is decomposed with respect to a direction of a singular vector, a comparing process of comparing a value obtained by squaring each of the components into which the error vector is decomposed with respect to the direction of the singular vector with corresponding variance in the direction of the singular vector individually with respect to the direction of the singular vector, and a determination process of performing an abnormality determination on the basis of plural compared results in the comparing process.

Abnormality detection device, abnormality detection method, and program

An information-processing method is provided, including a step of specifying first data clusters to which the first data each belongs and second data clusters to which the second data each belongs; a step of extracting the first data belonging to one of the first data clusters and the second data acquired at a corresponding time as correspondent data; a step of totalizing the number of pieces of correspondent data included in each of the second data clusters and calculating a total value for each cluster for the second data; and a step of specifying the second data clusters which are transition destinations of the correspondent data in a subsequent time and counting the number of pieces of transition destination data which is the correspondent data transitioning from each of the second data clusters which are transition sources to the second data clusters which are the transition destinations.

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Tokyo, Japan

Takaharu Hiroe