A method of estimation on a curve of a relevant point for detecting an anomaly of a motor. The method includes selecting a profile including a binary code, each component of which codes a direction of variation between two consecutive characteristic points of at least one learning curve, a model making it possible to estimate a relevant point based on a set of characteristic points of a curve and a filter. The method also includes applying the filter of the profile selected to the curve, determining a set of characteristic points of the filtered curve and of a binary code, comparing the determined code and the code of the profile selected, and estimating, as a function of the comparison, the relevant point on the curve based on the characteristic points of the filtered curve and the model of the profile selected.

The present invention relates to an operation control method for a gasification power generation system for gasifying carbon-based fuel such as coal in a gasifier using oxygen or oxygen-enriched air as an oxidizing agent, burning the obtained syngas as fuel in a gas turbine, driving the gas turbine by the syngas, driving a steam turbine by steam generated using exhaust heat of the gas turbine, thus executing combined power generation.

Various embodiments include a system having: at least one computing device configured to tune a set of gas turbines (GTs) by performing actions including: commanding each GT in the set of GTs to a base load level, based upon a measured ambient condition for each GT; commanding each GT in the set of GTs to adjust a respective output to match a nominal mega-watt power output value, and subsequently measuring an actual fuel flow value and an actual emissions value for each GT; adjusting at least one of a fuel flow or a water flow for each GT to an adjusted water/fuel ratio in response to the actual emissions value deviating from an emissions level associated with the base load level, while maintaining the respective adjusted output; and adjusting an operating condition of each GT in the set of GTs based upon a difference between the respective measured actual fuel flow value and a nominal fuel flow value at the ambient condition, while maintaining the adjusted water/fuel ratio.

A condition monitoring device for an extracted-gas compression system including a compressor which increases pressure of extracted gas includes: a sensor for detecting a state quantity of the extracted gas flowing into the compressor; an erosion progression level calculation unit for calculating an erosion progression level of the compressor on the basis of the state quantity of the extracted gas; and a service life evaluation unit for evaluating a service life of the compressor on the basis of the erosion progression level of the compressor.

A method includes obtaining a first test matrix for a first aircraft system and a second test matrix for a second aircraft system. The method also includes, during a first operational test of the first test matrix, obtaining sensor data that includes second sensor data that is not specified by the first test matrix. The method includes evaluating a second operational test of the second test matrix by processing the second sensor data using a second analytic model of the second aircraft system. The method also includes generating second predicted sensor data based on the evaluation of the second operational test. The method includes generating a second error measure by comparing a second subset of the sensor data to the second predicted sensor data. The method includes determining, based at least in part on a range of the second sensor data, a test coverage metric of the second test matrix.

In a method for predicting a turbine outlet temperature at a future use of a gas turbine based on a past use thereof, the turbine outlet temperature (objective variable) at the future use is predicted by a turbine outlet temperature model by using a parameter (explanatory variable) in environmental and operational conditions planned for the future use and a rotating speed of a fan (explanatory variable) planned for the future use, and coefficients with respect to the explanatory variables are identified through a learning. In the learning, the coefficients are identified based on a regression learning of the explanatory variables and the objective variable of the turbine outlet temperature model made by using the parameter, the rotating speed of the fan and the turbine outlet temperature at the past use of the gas turbine.

Controlling a switching element in accordance with a voltage output from a signal amplifying circuit enables adjusting a voltage to be received by a current calculation circuit. Even when a range of a air volume to be used is wide and a range of output of a DC motor is wide, or a current flowing through the DC motor has a wide range, a resistance value of a shunt resistor and an amplification factor of a signal amplifying circuit are not required to be reduced, and thus current detection accuracy of the DC motor can be improved.

A data processing method is proposed, including: sensing, via at least one sensing portion, target information of a target device; receiving and processing, via an electronic device, the target information of the sensing portion to form feature information; processing, via the electronic device, the feature information into a label matrix, and establishing, via an artificial intelligence training method, a target model based on the label matrix; and after the electronic device captures real-time information of the target device, predicting, via the target model, a life limit of the target device, wherein a content of the target information is corresponding to a content of the real-time information. Thus, a good target model is constituted and is advantageous in training artificial intelligence by processing the feature information into the label matrix.

Provided is a steam turbine plant activation control device that can flexibly handle an initial state amount of a steam turbine plant and activate a steam turbine at a high speed. The activation control device 21 for the steam turbine plant includes a heat source device 1 configured to heat a low-temperature fluid using a heat source medium and generate a high-temperature fluid, a steam generator 2 for generating steam by thermal exchange with the high-temperature fluid, a steam turbine 3 to be driven by the steam, and adjusters 11, 12, 13, 14, 15 configured to adjust operation amounts of the plant.

Various embodiments include a system having: at least one computing device configured to tune a set of gas turbines (GTs) by performing actions including: commanding each GT in the set of GTs to a base load level, based upon a measured ambient condition for each GT; commanding each GT in the set of GTs to adjust a respective output to match a nominal mega-watt power output value, and subsequently measuring an actual fuel flow value for each GT; and adjusting an operating condition of each GT in the set of GTs based upon a difference between the respective measured actual fuel flow value and a nominal fuel flow value at the ambient condition.