LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM
A learning device (100) learns a state of an air conditioning system in which refrigerant circulates. The air conditioning system includes an outdoor unit and at least one indoor unit. The learning device (100) includes: a first data acquisition unit (110); and a model generation unit (120). The fir...
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| creator | ISHIGAKI, Mitsuhiro HASHIKAWA, Takahiro HOKARI, Hiroaki |
| description | A learning device (100) learns a state of an air conditioning system in which refrigerant circulates. The air conditioning system includes an outdoor unit and at least one indoor unit. The learning device (100) includes: a first data acquisition unit (110); and a model generation unit (120). The first data acquisition unit (110) is configured to acquire operation data of the air conditioning system. The model generation unit (120) is configured to convert a specific model (M1 to M3) into a trained model using the operation data. The operation data includes a specific parameter and at least one of a temperature of air passing through the second heat exchanger, a temperature and a pressure of the refrigerant, and a temperature outside a space where each of the at least one indoor unit is arranged. The specific model (M1 to M3) estimates the specific parameter from the operation data other than the specific parameter. The specific parameter includes at least one of an operating frequency of the compressor, a degree of opening of the expansion valve, and an amount of air blown per unit time by the blower. |
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The air conditioning system includes an outdoor unit and at least one indoor unit. The learning device (100) includes: a first data acquisition unit (110); and a model generation unit (120). The first data acquisition unit (110) is configured to acquire operation data of the air conditioning system. The model generation unit (120) is configured to convert a specific model (M1 to M3) into a trained model using the operation data. The operation data includes a specific parameter and at least one of a temperature of air passing through the second heat exchanger, a temperature and a pressure of the refrigerant, and a temperature outside a space where each of the at least one indoor unit is arranged. The specific model (M1 to M3) estimates the specific parameter from the operation data other than the specific parameter. 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The air conditioning system includes an outdoor unit and at least one indoor unit. The learning device (100) includes: a first data acquisition unit (110); and a model generation unit (120). The first data acquisition unit (110) is configured to acquire operation data of the air conditioning system. The model generation unit (120) is configured to convert a specific model (M1 to M3) into a trained model using the operation data. The operation data includes a specific parameter and at least one of a temperature of air passing through the second heat exchanger, a temperature and a pressure of the refrigerant, and a temperature outside a space where each of the at least one indoor unit is arranged. The specific model (M1 to M3) estimates the specific parameter from the operation data other than the specific parameter. The specific parameter includes at least one of an operating frequency of the compressor, a degree of opening of the expansion valve, and an amount of air blown per unit time by the blower.</description><subject>AIR-CONDITIONING, AIR-HUMIDIFICATION, VENTILATION, USE OF AIRCURRENTS FOR SCREENING</subject><subject>BLASTING</subject><subject>HEATING</subject><subject>LIGHTING</subject><subject>MECHANICAL ENGINEERING</subject><subject>RANGES</subject><subject>VENTILATING</subject><subject>WEAPONS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPD0cXUM8vP0c1dwcQ3zdHZVcPRzUfD0c3MNcvUD8qCCbv5BCsEhjiGuCv5uCo6eQQrO_n4uniGe_mCdwZHBIa6-PAysaYk5xam8UJqbQcHNNcTZQze1ID8-tbggMTk1L7Uk3jXAxMjM0MTcwNHEmAglAKkzLGM</recordid><startdate>20240403</startdate><enddate>20240403</enddate><creator>ISHIGAKI, Mitsuhiro</creator><creator>HASHIKAWA, Takahiro</creator><creator>HOKARI, Hiroaki</creator><scope>EVB</scope></search><sort><creationdate>20240403</creationdate><title>LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM</title><author>ISHIGAKI, Mitsuhiro ; HASHIKAWA, Takahiro ; HOKARI, Hiroaki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_EP4261470A43</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre ; ger</language><creationdate>2024</creationdate><topic>AIR-CONDITIONING, AIR-HUMIDIFICATION, VENTILATION, USE OF AIRCURRENTS FOR SCREENING</topic><topic>BLASTING</topic><topic>HEATING</topic><topic>LIGHTING</topic><topic>MECHANICAL ENGINEERING</topic><topic>RANGES</topic><topic>VENTILATING</topic><topic>WEAPONS</topic><toplevel>online_resources</toplevel><creatorcontrib>ISHIGAKI, Mitsuhiro</creatorcontrib><creatorcontrib>HASHIKAWA, Takahiro</creatorcontrib><creatorcontrib>HOKARI, Hiroaki</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ISHIGAKI, Mitsuhiro</au><au>HASHIKAWA, Takahiro</au><au>HOKARI, Hiroaki</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM</title><date>2024-04-03</date><risdate>2024</risdate><abstract>A learning device (100) learns a state of an air conditioning system in which refrigerant circulates. The air conditioning system includes an outdoor unit and at least one indoor unit. The learning device (100) includes: a first data acquisition unit (110); and a model generation unit (120). The first data acquisition unit (110) is configured to acquire operation data of the air conditioning system. The model generation unit (120) is configured to convert a specific model (M1 to M3) into a trained model using the operation data. The operation data includes a specific parameter and at least one of a temperature of air passing through the second heat exchanger, a temperature and a pressure of the refrigerant, and a temperature outside a space where each of the at least one indoor unit is arranged. The specific model (M1 to M3) estimates the specific parameter from the operation data other than the specific parameter. The specific parameter includes at least one of an operating frequency of the compressor, a degree of opening of the expansion valve, and an amount of air blown per unit time by the blower.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | AIR-CONDITIONING, AIR-HUMIDIFICATION, VENTILATION, USE OF AIRCURRENTS FOR SCREENING BLASTING HEATING LIGHTING MECHANICAL ENGINEERING RANGES VENTILATING WEAPONS |
| title | LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM |
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