Johnson Controls Technology Company

Johnson Controls Tyco IP Holdings Llp

Andrew J Boettcher

Kirk H Drees

Steven R Vitullo

Michael J Wenzel

Youngchoon Park

Vijaya S Chennupati

James P Kummer

Gerald A Asp

Peter A Craig

Vivek Narain

Sudhi R Sinha

Young Min Lee

Vaidhyanathan Venkiteswaran

Karl F Reichenberger

Andrew J Przybylski

Walter Andrew Martin

Miguel Galvez

Homero L Noboa

Ryan A Piaskowski

Clay G Nesler

Shawn D Schubert

Jason T Sawyer

Donald R Albinger

Daniel M Curtis

Thomas M Seneczko

Siddharth Goyal

Saman Beyhaghi

A building system including one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to collect building device data of a building device, the building device data comprising a plurality of data samples of a data point and generate a time correlated data stream for the data point, the time correlated data stream comprising values of the plurality of data samples of the data point. The instructions cause the one or more processors to generate a time correlated reliability data stream for the data point, the time correlated reliability data stream comprising a plurality of reliability values indicating reliability of the values of the plurality of data samples of the data point.

Building system with a time correlated reliability data stream

A building energy management system includes building equipment, a data collector, an analytics service, a timeseries database, and an energy management application. The building equipment monitor and control one or more variables in the building energy management system and provide data samples of the one or more variables. The data collector collects the data samples from the building equipment and generates a data timeseries including a plurality of the data samples. The analytics service performs one or more analytics using the data timeseries and generates a results timeseries including a plurality of result samples indicating results of the analytics. The timeseries database stores the data timeseries and the results timeseries. The energy management application retrieves the data timeseries and the results timeseries from the timeseries database in response to a request for timeseries data associated with the one or more variables.

Building energy management system with energy analytics

A system for generating and using a predictive model to control building equipment includes building equipment operable to affect one or more variables in a building and an operating data aggregator that collects a set of operating data for the building equipment. The system includes an autocorrelation corrector that removes an autocorrelated model error from the set of operating data by determining a residual error representing a difference between an actual output of the building equipment and an output predicted by the predictive model, using the residual error to calculate an autocorrelation for the model error, and transforming the set of operating data using the autocorrelation. The system includes a model generator module that generates a set of model coefficients for the predictive model using the transformed set of operating data and a controller that controls the building equipment by executing a model-based control strategy that uses the predictive model.

Systems and methods for adaptively updating equipment models

A system for detecting faults in building equipment includes an integration fault detector, a kernel density fault detector, and a fault detector selector. The integration fault detector is configured to detect faults in the building equipment by analyzing time series data using an integration fault detection technique. The kernel density fault detector is configured to detect faults in the building equipment by analyzing the time series data using a kernel density estimation fault detection technique. The fault detector selector is configured to select the integration fault detector or the kernel density fault detector for use in detecting faults in the building equipment based on an attribute of the time series data.

Systems and methods for fault detection and handling by assessing building equipment performance

A building management system (BMS) includes a controller that monitors performance values for a controlled process during a first time period relative to initial outlier detection limits and generates new outlier detection limits for the controlled process in response to a detected change in the controlled process during the first time period. The controller monitors the performance values relative to the new outlier detection limits during a second time period to detect outliers during the second time period. The controller calculates a confidence difference for an estimated confidence parameter based on a number of outliers detected using the new outlier detection limits during the second time period. The controller adjusts the new outlier detection limits in response to the confidence difference dropping below a threshold value.

Systems and methods for retraining outlier detection limits in a building management system

An operating data aggregator module collects a first set of operating data and a second set of operating data for building equipment. A model generator module generates a first set of model coefficients and a second set of model coefficients for a predictive model for the building equipment using the first set of operating data and the second set of operating data, respectively. A test statistic module generates a test statistic based on a difference between the first set of model coefficients and the second set of model coefficients. A critical value module calculates critical value for the test statistic. A hypothesis testing module compares the test statistic with the critical value using a statistical hypothesis test to determine whether the predictive model has changed. In response to a determination that the predictive model has changed, a fault indication may be generated and/or the predictive model may be adaptively updated.

A fault detection and diagnostics (FDD) system is provided for a refrigeration circuit having an evaporator and a compressor configured to circulate a refrigerant through the evaporator. The FDD system includes a communications interface configured to receive a measurement of a thermodynamic property affected by the refrigeration circuit and a processing circuit having a processor and memory. The processing circuit is configured to use the measured thermodynamic property to determine an expected suction entropy of the refrigerant at a suction of the compressor, use the expected suction entropy to determine an expected thermodynamic discharge property of the refrigerant at a discharge of the compressor, determine an actual thermodynamic discharge property of the refrigerant at the discharge of the compressor, and detect a fault in the refrigeration circuit by comparing the expected thermodynamic discharge property with the actual thermodynamic discharge property.

Fault detection and diagnostic system for a refrigeration circuit

A controller for a building management system includes a first data interface configured to receive data from the building management system and a processing circuit including a processor and a memory device storing a fault detection rule having an initial threshold value. The processing circuit is configured to detect a first fault in the building management system using the stored fault detection rule having the initial threshold value and to use the data from the building management system to determine whether an adjustment to the stored fault detection rule is needed. In response to a determination that an adjustment to the stored fault detection rule is needed, the processing circuit is configured to calculate a new threshold value for the stored fault detection rule and update the stored fault detection rule by replacing the initial threshold value with the new threshold value.

Systems and methods for using rule-based fault detection in a building management system

A method for detecting and cleansing suspect building automation system data is shown and described. The method includes using processing electronics to automatically determine which of a plurality of error detectors and which of a plurality of data cleansers to use with building automation system data. The method further includes using processing electronics to automatically detect errors in the data and cleanse the data using a subset of the error detectors and a subset of the cleansers.

Systems and methods for data quality control and cleansing

A controller for a building management system includes a system of rules for detecting faults in the building management system. The rules include content conditions and trigger conditions. The content conditions are not checked until one or more of the trigger conditions are met. A rule-based fault detection engine may be implemented by a low level building equipment controller. One or more thresholds for a rule may be automatically or manually adjusted.

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Wauwatosa, WI, United States of America

Andrew J Boettcher