AUTOMATIC THRESHOLD SELECTION OF MACHING LEARNING/DEEP LEARNING MODEL FOR ANOMALY DETECTION OF CONNECTED CHILLERS

    公开(公告)号:US20190383510A1

    公开(公告)日:2019-12-19

    申请号:US16198377

    申请日:2018-11-21

    摘要: 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.

    BUILDING MANAGEMENT AUTONOMOUS HVAC CONTROL USING REINFORCEMENT LEARNING WITH OCCUPANT FEEDBACK

    公开(公告)号:US20190353378A1

    公开(公告)日:2019-11-21

    申请号:US15980547

    申请日:2018-05-15

    IPC分类号: F24F11/50 G05B13/02 F24F11/65

    摘要: A building management system includes one or more processors, and one or more computer-readable storage media communicably coupled to the one or more processors and having instructions stored thereon that cause the one or more processors to: define a state of a zone or space within a building; control an HVAC system to adjust a temperature of the zone or space corresponding to a first action; receive utterance data from a voice assist device located in the zone or space; analyze the utterance data to identify a sentiment relating to the temperature of the zone or space; calculate a reward based on the state, the first action, and the sentiment; determine a second action to adjust the temperature of the zone or space based on the reward; and control the HVAC system to adjust the temperature of the zone or space corresponding to the second action.

    BUILDING SYSTEM WITH A RECOMMENDATION ENGINE THAT OPERATES WITHOUT STARTING DATA

    公开(公告)号:US20210383276A1

    公开(公告)日:2021-12-09

    申请号:US17339322

    申请日:2021-06-04

    IPC分类号: G06N20/00 G06N5/04 G05B13/02

    摘要: A building system including one or more memory devices configured to store instructions thereon, that, when executed by one or more processors, cause the one or more processors to generate building recommendations based on recommendation requests with a model of a first model type when less than a predefined amount of model training data is available and receive feedback data on the recommendation requests generated by the model of the first model type. The instructions cause the one or more processors to transition from generating the building recommendations by the model of the first model type to a second model of a second model type by comparing performance of the first model type to the second model type based on the feedback data.

    COST SAVINGS FROM FAULT PREDICTION AND DIAGNOSIS

    公开(公告)号:US20210262689A1

    公开(公告)日:2021-08-26

    申请号:US17318877

    申请日:2021-05-12

    摘要: A heating, ventilation, and air conditioning (HVAC) fault prediction system for a building including a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to receive HVAC data relating to a plurality of HVAC components, the HVAC data indicating performance of the plurality of HVAC components, generate, based on the received HVAC data, a univariate prediction model and a multivariate prediction model, generate, using the received HVAC data, one or more predicted operational parameters for the plurality of HVAC components corresponding to a future time period, and execute at least one of the univariate prediction model or the multivariate prediction model on the one or more predicted operational parameters to predict a HVAC fault associated with at least one of the plurality of HVAC components to occur during the future time period.

    BUILDING SYSTEM WITH ADAPTIVE FAULT DETECTION

    公开(公告)号:US20210191379A1

    公开(公告)日:2021-06-24

    申请号:US16725940

    申请日:2019-12-23

    IPC分类号: G05B23/02

    摘要: A building system for detecting faults in an operation of building equipment. The building system comprising one or more memory devices configured to store instructions thereon that cause one or more processors to perform a cumulative sum (CUSUM) analysis on actual building data and corresponding predicted building data to obtain cumulative sum values for a plurality of times within a first time period; determine a first time at which a first cumulative sum value is at a first maximum; identify a second cumulative sum value at a second maximum at a second time occurring after the first time; compare the identified second cumulative sum value to a threshold; and based on determining that the identified second cumulative sum value does not exceed the threshold, determine that a first fault ended at the first time.

    ADAPTIVELY LEARNING SURROGATE MODEL FOR PREDICTING BUILDING SYSTEM DYNAMICS FROM SYSTEM IDENTIFICATION MODEL

    公开(公告)号:US20210191348A1

    公开(公告)日:2021-06-24

    申请号:US16726038

    申请日:2019-12-23

    IPC分类号: G05B13/04 F24F11/64

    摘要: Systems and methods for training a surrogate model for predicting system states for a building management system based on generated data from a system identification model are disclosed herein. The system identification model is used to generate predicted system parameters of a zone of the building based on historic data from operation of the building equipment. The surrogate model is trained based on the predicted system parameters from the system identification model. Predicted future parameters of the variable state of the building are generated using the surrogate model. The surrogate model is re-trained based on new operational data from the building equipment. An updated series of predicted future parameters is generated using the re-trained surrogate model.

    METHODS AND SYSTEMS FOR TRAINING HVAC CONTROL USING SURROGATE MODEL

    公开(公告)号:US20210191342A1

    公开(公告)日:2021-06-24

    申请号:US16725999

    申请日:2019-12-23

    摘要: Systems and methods for training a reinforcement learning (RL) model for HVAC control are disclosed herein. A calibrated simulation model is used to train a surrogate model of the HVAC system operating within a building. The surrogate model is used to generate simulated experience data for the HVAC system. The simulated experience data can be used to train a reinforcement learning (RL) model of the HVAC system. The RL model is used to control the HVAC system based on the current state of the system and the best predicted action to perform in the current state. The HVAC system generates real experience data based on the actual operation of the HVAC system within the building. The real experience data is used to retrain the surrogate model, and additional simulated experience data is generated using the surrogate model. The RL model can be retrained using the additional simulated experience data.

    BUILDING MANAGEMENT SYSTEM WITH DYNAMIC ENERGY PREDICTION MODEL UPDATES

    公开(公告)号:US20210116874A1

    公开(公告)日:2021-04-22

    申请号:US16657398

    申请日:2019-10-18

    IPC分类号: G05B13/04 G06Q50/06 G01D4/00

    摘要: A building management system including building equipment operable to affect a variable state or condition of a building. The building management system includes a controller including a processing circuit. The processing circuit is configured to obtain an energy prediction model (EPM) for predicting energy requirements over time. The processing circuit is configured to monitor one or more triggering events to determine if the EPM should be retrained. The processing circuit is configured to, in response to detecting that a triggering event has occurred, identify updated values of one or more hyper-parameters of the EPM. The processing circuit is configured to operate the building equipment based on the EPM.