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公开(公告)号：US20230359157A1
公开(公告)日：2023-11-09
申请号：US18218983
申请日：2023-07-06
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Young M. Lee , Sugumar Murugesan , ZhongYi Jin , Jaume Amores
CPC classification number: G05B13/048 , F24F11/38 , F24F11/63 , G06N20/00 , F24F11/64 , G05B13/04 , G05B13/0265 , G05B13/027 , G05B13/028 , G06N5/04
Abstract: A model management system for building equipment includes one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to determine whether fault data exists in equipment data used to generate a plurality of shutdown prediction models for the building equipment, generate a first performance evaluation value for each of the plurality of shutdown prediction models using a first evaluation technique in response to a determination that the fault data exists in the equipment data, generate a second performance evaluation value for each of the plurality of shutdown prediction models using a second evaluation technique in response to a determination that the fault data does not exist in the equipment data, and select one of the plurality of shutdown prediction models based on the first performance evaluation value and the second performance evaluation value.
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公开(公告)号：US20230393539A1
公开(公告)日：2023-12-07
申请号：US18204631
申请日：2023-06-01
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Surajit Borah , Santle Camilus , ZhongYi Jin , Vish Ramamurti , Young M. Lee
CPC classification number: G05B13/027 , G05B13/04 , G06F40/30 , G06N3/049
Abstract: A building system including one or more memory devices configured to store instructions that, when executed by one or more processors, cause the one or more processors to receive training data including acronym strings and tag strings, train a sequence to sequence neural network based on the training data, receive an acronym string for labeling, the acronym string comprising a particular plurality of acronyms, and generate a tag string for the acronym string with the sequence to sequence neural network, wherein the sequence to sequence neural network outputs a tag of the tag string for one acronym of the particular plurality of acronyms based on the one acronym and contextual information of the acronym string, wherein the contextual information includes other acronyms of the particular plurality of acronyms.
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公开(公告)号：US11874809B2
公开(公告)日：2024-01-16
申请号：US16895817
申请日：2020-06-08
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： ZhongYi Jin , Erik S. Paulson , Simin Zhou , Ryan A. Piaskowski , Youngchoon Park
IPC: G06F16/21 , G06F16/28 , G05B19/042
CPC classification number: G06F16/211 , G05B19/042 , G06F16/288 , G05B2219/2614
Abstract: A building system of a building, the building system comprising one or more memory devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive building metadata, the building metadata describing a plurality of components of the building, generate, based on the building metadata, a plurality of entities, each of the plurality of entities representing one of the plurality of components, and determine, based on the building metadata, relationships between the plurality of entities. The instructions cause the one or more processors to generate a plurality of metadata strings in a universal building schema comprising a plurality of characters representing a first entity of the plurality of entities, one or more second entities of the plurality of entities related to the first entity, and one or more relationships between the first entity and the one or more second entities.
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公开(公告)号：US20230033206A1
公开(公告)日：2023-02-02
申请号：US17963699
申请日：2022-10-11
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Young M. Lee , Sugumar Murugesan , ZhongYi Jin , Jaume Amores , Kelsey Carle Schuster , Steven R. Vitullo , Henan Wang
Abstract: A fault prediction system for building equipment includes one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to receive device data for a plurality of devices of the building equipment, the device data indicating performance of the plurality of devices; generate, based on the received device data, a plurality of prediction models comprising at least one of single device prediction models generated for each of the plurality of devices or cluster prediction models generated for device clusters of the plurality of devices; label each of the plurality of prediction models as an accurately predicting model or an inaccurately predicting model based on a performance of each of the plurality of prediction models; and predict a device fault with each of the plurality of prediction models labeled as an accurately predicting model.
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Patent Agency Ranking
公开(公告)号：US11531310B2
公开(公告)日：2022-12-20
申请号：US16198416
申请日：2018-11-21
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Sugumar Murugesan , Young M. Lee , ZhongYi Jin , Jaume Amores
Abstract: A model management system for a building, including one or more memory devices and one or more processors. The one or more memory devices are configured to store instructions to be executed on the one or more processors. The one or more processors are configured to determine whether chiller fault data exists in chiller data used to generate a plurality of chiller shutdown prediction models. The one or more processors are further configured to generate a first performance evaluation value for each of the plurality of chiller shutdown prediction models using a first evaluation technique in response to a determination that chiller fault data exists in the chiller data, and generate a second performance evaluation value for each of the plurality of chiller shutdown prediction models using a second evaluation technique in response to a determination that chiller fault data does not exist in the chiller data. The one or more processors are configured to select one of the plurality of chiller shutdown prediction models based on the first performance evaluation in response to the determination that chiller fault data exists in the chiller data, and select one of the plurality of chiller shutdown prediction models based on the second performance evaluation in response to the determination that chiller fault data does not exist in the chiller data.
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公开(公告)号：US11474485B2
公开(公告)日：2022-10-18
申请号：US16198456
申请日：2018-11-21
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Young M. Lee , Sugumar Murugesan , ZhongYi Jin , Jaume Amores , Kelsey Carle Schuster , Steven R. Vitullo , Henan Wang
Abstract: A chiller fault prediction system for a building, including one or more memory devices and one or more processors. The one or more memory devices are configured to store instructions to be executed on the one or more processors. The one or more processors are configured to receive chiller data for a plurality of chillers, the chiller data indicating performance of the plurality of chillers. The one or more processors are configured to generate, based on the received chiller data, a plurality of single chiller prediction models and a plurality of cluster chiller prediction models, the plurality of single chiller prediction models generated for each the plurality of chillers and the plurality of cluster chiller prediction models generated for chiller clusters of the plurality of chillers. The one or more processors are configured to label each of the plurality of single chiller prediction models and the plurality of cluster chiller prediction models as an accurately predicting chiller model or an inaccurately predicting chiller model based on a performance of each of the plurality of single chiller prediction models and a performance of each of the plurality of cluster chiller prediction models. The one or more processors are configured to predict a chiller fault with each of the plurality of single chiller prediction models labeled as the accurately predicting chiller models. The one or more processors are configured to predict a chiller fault for each of a plurality of assigned chillers assigned to one of a plurality of clusters labeled as the accurately predicting chiller model.
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公开(公告)号：US11747776B2
公开(公告)日：2023-09-05
申请号：US17963699
申请日：2022-10-11
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Young M. Lee , Sugumar Murugesan , ZhongYi Jin , Jaume Amores , Kelsey Carle Schuster , Steven R. Vitullo , Henan Wang
CPC classification number: G05B13/048 , F24F11/38 , F24F11/63 , F24F11/64 , G05B13/0265 , G05B13/04 , G06N20/00 , G05B13/027 , G05B13/028 , G06N5/04
Abstract: A fault prediction system for building equipment includes one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to receive device data for a plurality of devices of the building equipment, the device data indicating performance of the plurality of devices; generate, based on the received device data, a plurality of prediction models comprising at least one of single device prediction models generated for each of the plurality of devices or cluster prediction models generated for device clusters of the plurality of devices; label each of the plurality of prediction models as an accurately predicting model or an inaccurately predicting model based on a performance of each of the plurality of prediction models; and predict a device fault with each of the plurality of prediction models labeled as an accurately predicting model.
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公开(公告)号：US11693374B2
公开(公告)日：2023-07-04
申请号：US16885968
申请日：2020-05-28
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Surajit Borah , Santle Camilus , ZhongYi Jin , Vish Ramamurti , Young M. Lee
CPC classification number: G05B13/027 , G05B13/04 , G06F40/30 , G06N3/049
Abstract: A building system including one or more memory devices configured to store instructions that, when executed by one or more processors, cause the one or more processors to receive training data including acronym strings and tag strings, train a sequence to sequence neural network based on the training data, receive an acronym string for labeling, the acronym string comprising a particular plurality of acronyms, and generate a tag string for the acronym string with the sequence to sequence neural network, wherein the sequence to sequence neural network outputs a tag of the tag string for one acronym of the particular plurality of acronyms based on the one acronym and contextual information of the acronym string, wherein the contextual information includes other acronyms of the particular plurality of acronyms.
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公开(公告)号：US11604441B2
公开(公告)日：2023-03-14
申请号：US16198377
申请日：2018-11-21
Applicant: Johnson Controls Tyco IP Holdings LLP
Inventor： Sugumar Murugesan , Young M. Lee , ZhongYi Jin , Jaume Amores
Abstract: A chiller threshold management system for a building, including one or more memory devices and one or more processors. The one or more memory devices are configured to store instructions to be executed on the one or more processors. The one or more processors are configured to determine whether chiller fault data exists in chiller data used to generate a plurality of chiller prediction models. The one or more processors are further configured to generate a first threshold evaluation value for each of the plurality of chiller prediction models using a first evaluation technique in response to a determination that chiller fault data exists in the chiller data, and generate a second threshold evaluation value for each of the chiller prediction models using a second evaluation technique in response to a determination that chiller fault data does not exist in the chiller data. The one or more processors are configured to select a first threshold for each of the plurality of chiller prediction models based on the first threshold evaluation values in response to the determination that chiller fault data exists in the chiller data, and select a second threshold for each of the plurality of chiller prediction models based on the second threshold evaluation values in response to the determination that chiller fault data does not exist in the chiller data.
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