Abnormality omen estimation device for air conditioner, abnormality omen estimation model learning device for air conditioner, and air conditioner
An abnormality omen estimation model learning device (22A) estimates the degree of abnormality omen for each abnormality type of an air conditioner provided with an outdoor unit, an indoor unit, and a remote controller. A communication circuit (51) receives a communication frame transmitted among an...
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| creator | ISHIKAWA TOSHIHIRO SENDA, SHUICHIRO HIROSE KATSUHIRO |
| description | An abnormality omen estimation model learning device (22A) estimates the degree of abnormality omen for each abnormality type of an air conditioner provided with an outdoor unit, an indoor unit, and a remote controller. A communication circuit (51) receives a communication frame transmitted among an outdoor unit, an indoor unit, and a remote controller. A communication history storage means (52) stores the received communication frames. A learning data generator (53) generates learning data using the communication frames stored in the communication experience storage device (52). A model generator (54) uses the generated learning data to learn an estimation model that estimates the degree of abnormality omen for each abnormality type of the air conditioning device.
本发明的异常预兆推测模型学习装置(22A)对具备室外机、室内机以及遥控器的空调装置的每个异常种类的异常预兆度进行推测。通信电路(51)接收在室外机、室内机以及遥控器之间传送的通信帧。通信经历存储装置(52)存储已接收到的通信帧。学习数据生成器(53)使用通信经历存储装置(52)中存储的通信帧，来生成学习数据。模型生成器(54)使用已生成的学习数据，学习对空调装置的每个异常种类的异常预兆度进行推测的推测模型。 |
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本发明的异常预兆推测模型学习装置(22A)对具备室外机、室内机以及遥控器的空调装置的每个异常种类的异常预兆度进行推测。通信电路(51)接收在室外机、室内机以及遥控器之间传送的通信帧。通信经历存储装置(52)存储已接收到的通信帧。学习数据生成器(53)使用通信经历存储装置(52)中存储的通信帧，来生成学习数据。模型生成器(54)使用已生成的学习数据，学习对空调装置的每个异常种类的异常预兆度进行推测的推测模型。</description><language>chi ; eng</language><subject>AIR-CONDITIONING, AIR-HUMIDIFICATION, VENTILATION, USE OF AIRCURRENTS FOR SCREENING ; BLASTING ; HEATING ; LIGHTING ; MECHANICAL ENGINEERING ; RANGES ; VENTILATING ; WEAPONS</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220722&DB=EPODOC&CC=CN&NR=114787562A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220722&DB=EPODOC&CC=CN&NR=114787562A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ISHIKAWA TOSHIHIRO</creatorcontrib><creatorcontrib>SENDA, SHUICHIRO</creatorcontrib><creatorcontrib>HIROSE KATSUHIRO</creatorcontrib><title>Abnormality omen estimation device for air conditioner, abnormality omen estimation model learning device for air conditioner, and air conditioner</title><description>An abnormality omen estimation model learning device (22A) estimates the degree of abnormality omen for each abnormality type of an air conditioner provided with an outdoor unit, an indoor unit, and a remote controller. A communication circuit (51) receives a communication frame transmitted among an outdoor unit, an indoor unit, and a remote controller. A communication history storage means (52) stores the received communication frames. A learning data generator (53) generates learning data using the communication frames stored in the communication experience storage device (52). A model generator (54) uses the generated learning data to learn an estimation model that estimates the degree of abnormality omen for each abnormality type of the air conditioning device.
本发明的异常预兆推测模型学习装置(22A)对具备室外机、室内机以及遥控器的空调装置的每个异常种类的异常预兆度进行推测。通信电路(51)接收在室外机、室内机以及遥控器之间传送的通信帧。通信经历存储装置(52)存储已接收到的通信帧。学习数据生成器(53)使用通信经历存储装置(52)中存储的通信帧，来生成学习数据。模型生成器(54)使用已生成的学习数据，学习对空调装置的每个异常种类的异常预兆度进行推测的推测模型。</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>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZJjkmJSXX5SbmJNZUqmQn5uap5BaXJKZm1iSmZ-nkJJalpmcqpCWX6SQmFmkkJyfl5IJkkgt0lFIxKMvNz8lNUchJzWxKC8zLx2_MXkp6II8DKxpiTnFqbxQmptB0c01xNlDN7UgPz61uCAxOTUvtSTe2c_Q0MTcwtzUzMjRmBg1ALI8UK8</recordid><startdate>20220722</startdate><enddate>20220722</enddate><creator>ISHIKAWA TOSHIHIRO</creator><creator>SENDA, SHUICHIRO</creator><creator>HIROSE KATSUHIRO</creator><scope>EVB</scope></search><sort><creationdate>20220722</creationdate><title>Abnormality omen estimation device for air conditioner, abnormality omen estimation model learning device for air conditioner, and air conditioner</title><author>ISHIKAWA TOSHIHIRO ; SENDA, SHUICHIRO ; HIROSE KATSUHIRO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN114787562A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</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>ISHIKAWA TOSHIHIRO</creatorcontrib><creatorcontrib>SENDA, SHUICHIRO</creatorcontrib><creatorcontrib>HIROSE KATSUHIRO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ISHIKAWA TOSHIHIRO</au><au>SENDA, SHUICHIRO</au><au>HIROSE KATSUHIRO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Abnormality omen estimation device for air conditioner, abnormality omen estimation model learning device for air conditioner, and air conditioner</title><date>2022-07-22</date><risdate>2022</risdate><abstract>An abnormality omen estimation model learning device (22A) estimates the degree of abnormality omen for each abnormality type of an air conditioner provided with an outdoor unit, an indoor unit, and a remote controller. A communication circuit (51) receives a communication frame transmitted among an outdoor unit, an indoor unit, and a remote controller. A communication history storage means (52) stores the received communication frames. A learning data generator (53) generates learning data using the communication frames stored in the communication experience storage device (52). A model generator (54) uses the generated learning data to learn an estimation model that estimates the degree of abnormality omen for each abnormality type of the air conditioning device.
本发明的异常预兆推测模型学习装置(22A)对具备室外机、室内机以及遥控器的空调装置的每个异常种类的异常预兆度进行推测。通信电路(51)接收在室外机、室内机以及遥控器之间传送的通信帧。通信经历存储装置(52)存储已接收到的通信帧。学习数据生成器(53)使用通信经历存储装置(52)中存储的通信帧，来生成学习数据。模型生成器(54)使用已生成的学习数据，学习对空调装置的每个异常种类的异常预兆度进行推测的推测模型。</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 | Abnormality omen estimation device for air conditioner, abnormality omen estimation model learning device for air conditioner, and air conditioner |
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