Indoor environment model creation device
First Claim
1. An indoor environment model creation device configured to create an indoor environment model of an indoor space in which air-conditioning equipment, a CO2 sensor, and a humidity sensor are installed, the air-conditioning equipment being configured to condition air, the CO2 sensor being configured to measure a CO2 concentration in the indoor space, the humidity sensor being configured to measure an indoor humidity of the indoor space,the indoor environment model comprising a physics model including a heat parameter, a physics model including a moisture parameter, and a physics model including a CO2 concentration parameter,the indoor environment model creation device comprising:
- a memory configured to store operation data of the air-conditioning equipment in a learning target period as learning-use input data, and store measurement data measured by the CO2 sensor and the humidity sensor; and
processing circuitry configured to comprehensively learn a plurality of physics models with use of the learning-use input data and the measurement data stored in the memory,wherein the processing circuitry is configured to simultaneously solve a physics model comprising a parameter that is included in common in all of the plurality of physics models and the heat parameter, a physics model comprising a parameter that is common to all of the plurality of physics models and the moisture parameter, and a physics model comprising a parameter that is common to all of the plurality of physics models and the CO2 concentration parameter, and to perform convergence calculation, to thereby concurrently determine all parameters that are included in all of the plurality of physics models, and learn the physics models.
1 Assignment
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Accused Products
Abstract
An indoor environment model creation device is configured to create an indoor environment model of an indoor space in which air-conditioning equipment configured to condition air, an indoor humidity sensor configured to measure an indoor humidity of the indoor space, and a CO2 sensor configured to measure a CO2 concentration in the indoor space are installed. The indoor environment model includes a plurality of physics models in which heat, moisture, and CO2 concentration parameters are included. The indoor environment model creation device includes: a data storage unit configured to store operation data of the air-conditioning equipment in a learning target period as learning-use input data, and store measurement data measured by the CO2 sensor and the humidity sensor; and a model parameter learning unit configured to comprehensively learn the plurality of physics models with use of the learning-use input data and the measurement data, which are stored in the data storage unit.
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Citations
9 Claims
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1. An indoor environment model creation device configured to create an indoor environment model of an indoor space in which air-conditioning equipment, a CO2 sensor, and a humidity sensor are installed, the air-conditioning equipment being configured to condition air, the CO2 sensor being configured to measure a CO2 concentration in the indoor space, the humidity sensor being configured to measure an indoor humidity of the indoor space,
the indoor environment model comprising a physics model including a heat parameter, a physics model including a moisture parameter, and a physics model including a CO2 concentration parameter, the indoor environment model creation device comprising: -
a memory configured to store operation data of the air-conditioning equipment in a learning target period as learning-use input data, and store measurement data measured by the CO2 sensor and the humidity sensor; and processing circuitry configured to comprehensively learn a plurality of physics models with use of the learning-use input data and the measurement data stored in the memory, wherein the processing circuitry is configured to simultaneously solve a physics model comprising a parameter that is included in common in all of the plurality of physics models and the heat parameter, a physics model comprising a parameter that is common to all of the plurality of physics models and the moisture parameter, and a physics model comprising a parameter that is common to all of the plurality of physics models and the CO2 concentration parameter, and to perform convergence calculation, to thereby concurrently determine all parameters that are included in all of the plurality of physics models, and learn the physics models. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An indoor environment model creation device configured to create an indoor environment model of an indoor space in which air-conditioning equipment, a CO2 sensor, and a humidity sensor are installed, the air-conditioning equipment being configured to condition air, the CO2 sensor being configured to measure a CO2 concentration in the indoor space, the humidity sensor being configured to measure an indoor humidity of the indoor space,
the indoor environment model comprising a physics model including a heat parameter, a physics model including a moisture parameter, and a physics model including a CO2 concentration parameter, the indoor environment model creation device comprising: -
a memory configured to store operation data of the air-conditioning equipment in a learning target period as learning-use input data, and store measurement data measured by the CO2 sensor and the humidity sensor; and a processing circuitry configured to comprehensively learn a plurality of physics models with use of the learning-use input data and the measurement data stored in the memory, wherein the plurality of physics models consist of a physics model comprising a parameter that is included in common in all of the plurality of physics models and the heat parameter, a physics model comprising a parameter that is common to all of the plurality of physics models and the moisture parameter, and a physics model comprising a parameter that is common to all of the plurality of physics models and the CO2 concentration parameter, and wherein the processing circuitry is configured to first select some of the plurality of physics models as a learning target, and learn the parameter that is included in common in all of the plurality of physics models and a parameter that is uniquely included in a target physics model, and, in learning of the remaining physics models, the processing circuitry is configured to set thus first learned value as a value of a parameter common to all physics models and learn, for each of the remaining physics models, only a parameter uniquely included in each of the remaining physics models. - View Dependent Claims (8)
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9. A method, implemented by an indoor environment model creation device configured to create an indoor environment model of an indoor space in which air-conditioning equipment, a CO2 sensor, and a humidity sensor are installed, the air-conditioning equipment being configured to condition air, the CO2 sensor being configured to measure a CO2 concentration in the indoor space, the humidity sensor being configured to measure an indoor humidity of the indoor space,
the indoor environment model comprising a physics model including a heat parameter, a physics model including a moisture parameter, and a physics model including a CO2 concentration parameter, the method comprising: -
storing, at a memory, operation data of the air-conditioning equipment in a learning target period as learning-use input data, and storing measurement data measured by the CO2 sensor and the humidity sensor; and comprehensively learn a plurality of physics models with use of the learning-use input data and the measurement data stored in the memory, wherein the method includes simultaneously solving a physics model comprising a parameter that is included in common in all of the plurality of physics models and the heat parameter, a physics model comprising a parameter that is common to all of the plurality of physics models and the moisture parameter, and a physics model comprising a parameter that is common to all of the plurality of physics models and the CO2 concentration parameter, and performing convergence calculation, to thereby concurrently determine all parameters that are included in all of the plurality of physics models, and learn the physics models.
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Specification