Honeywell International Inc.

Honeywell Asca Inc.

Ecoation Innovative Solutions Inc.

Honeywell G.m.b.h.

Garrett Transportation I Inc.

Gregory Edward Stewart

Michael L Rhodes

Adrian Matias Fuxman

Johan Backstrom

Syed M Shahed

Francesco Borrelli

Saber Miresmailli

David Joachim Germann

Soumitri N Kolavennu

Gregory James Hampson

Jaroslav Pekar

Tariq Samad

Marc Light

Junqiang Fan

Stephen P Humpston

Patrick O Wspanialy

Gavin Schneider

Sebastien Tixier

Curtis L Taylor

David Kucera

Frank Martin Haran

Daniel Pachner

Danlei Chu

Philip D Loewen

Wyatt Culler

Cristian Gheorghe

Nathan Lawrence

Lino E Coria Mendoza

Allison Marie Christensen

Bhushan Gopaluni

Charles P Luebke

Dinkar A Mylaraswamy

Wendy K Foslien

Sharath Venkatesha

Matthew Brian Below

Brian C Krafthefer

Joseph Z Lu

Michael Forbes

Ondrej Santin

Jonathan T Grunow

Jonathan McDonald

Jeffry Thurston Donner

Jan Zirnstein

Pengling He

Francis Martin Haran

Eduardo Aparecido Sereguin Cabral De Melo

John A Escargega

Jonathan Mcdonald

Kelsey Gerbrandt

Devin G Kirk

Sohail Nazari

Robert Paul Cartier Dooner

Vladimir Ravlena

Francesco Borralli

Jeff Boehler

Johan U Backstrom

David Germann

Soumitri N c/o Honeywell Int Inc Kolavennu

Sved M Shahed

Borrelli Francesco

Samad Tariq

Junqiang c/o Honeywell Int Inc Fan

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.

Flame analytics system

A method includes obtaining data measurements associated with plants in at least one growing area. The data measurements are associated with one or more characteristics of the plants and one or more characteristics of the at least one growing area. The method also includes processing at least some of the data measurements to identify one or more anomalous plant production issues associated with the plants. At least one anomalous plant production issue is associated with uneven production by the plants in at least part of the at least one growing area. The method further includes generating at least one visualization presenting at least some of the data measurements or processed versions of at least some of the data measurements in a spatial manner that corresponds to the at least one growing area. The at least one visualization identifies information associated with the one or more anomalous plant production issues.

Platform for real-time identification and resolution of spatial production anomalies in agriculture

An apparatus includes at least one processor configured to obtain stereo-spatio-temporal data measurements of plants in a growing area. The stereo-spatio-temporal data measurements include (i) first spatio-temporal data measurements of the plants in the growing area and (ii) second spatio-temporal data measurements of the plants in the growing area. The at least one processor is also configured to analyze the stereo-spatio-temporal data measurements to identify one or more actual or potential problems associated with one or more of the plants. The at least one processor is further configured to generate a graphical user interface identifying at least one of the one or more actual or potential problems with the one or more plants. The first and second spatio-temporal data measurements of each stereo-spatio-temporal data measurement are associated with at least one common plant characteristic and different three-dimensional positions within the growing area taken at one or more known times.

Data processing platform for analyzing stereo-spatio-temporal crop condition measurements to support plant growth and health optimization

A mobile platform includes at least one first sensor mounted at a first position on the mobile platform and at least one second sensor mounted at a second position on the mobile platform, where the first position is offset from the second position. The at least one first sensor is configured to capture first data measurements of plants in the growing area. The at least one second sensor is configured to capture second data measurements of the plants in the growing area. Each of the first and second data measurements is associated with a three-dimensional position within the growing area and a time. The first and second sensors are configured to generate at least one common type of data measurement such that at least some of the first and second data measurements represent stereo-spatio-temporal data measurements of the plants in the growing area.

Stereo-spatial-temporal crop condition measurements for plant growth and health optimization

A method includes obtaining data measurements associated with plants in at least one growing area. The plants have a common genotype and are grown under different growing or environmental conditions in the at least one growing area. The data measurements are associated with one or more characteristics of the plants and multiple characteristics of the growing or environmental conditions. The method also includes processing at least some of the data measurements to identify one or more of the growing or environmental conditions associated with at least one desired characteristic being expressed in the plants being grown. The method further includes outputting an identification of the one or more growing or environmental conditions identified as achieving a specific genotype or phenotype trait for the plants. The specific genotype or phenotype trait is associated with the at least one desired characteristic.

System and method for testing plant genotype and phenotype expressions under varying growing and environmental conditions

An apparatus includes at least one processor configured to obtain multiple spatiotemporal population projection models. Different spatiotemporal population projection models are associated with different pests, diseases, or biocontrol agents in a growing area. Each spatiotemporal population projection model defines how the associated pest, disease, or biocontrol agent spreads and contracts in the growing area over time. The at least one processor is also configured to receive information associated with an actual presence of a specific pest, disease, or biocontrol agent at one or more locations in the growing area. Different locations in the growing area are associated with different plants. The at least one processor is further configured to project a future presence of the specific pest, disease, or biocontrol agent in the growing area using the spatiotemporal population projection model associated with the specific pest, disease, or biocontrol agent.

Real-time projections and estimated distributions of agricultural pests, diseases, and biocontrol agents

A method includes receiving manual input from a human operator, where the manual input includes human observation data measurements associated with plants in a growing area. The method also includes, for each human observation data measurement, identifying a height of a movable portion of a mobile platform on which the human operator rides, identifying a location of the mobile platform in the growing area, identifying a time at which the human observation data measurement is received, and associating the human observation data measurement with a three-dimensional position within the growing area and the time in order to generate a spatio-temporal data measurement. The three-dimensional position includes the height and the location. The method further includes storing, processing, or transmitting at least some of the spatio-temporal data measurements or one or more results based on at least some of the spatio-temporal data measurements.

Generation of stereo-spatio-temporal crop condition measurements based on human observations and height measurements

A method and system for reinforcement learning can include an actor-critic framework comprising an actor and a critic, the actor comprising an actor network and the critic comprising a critic network; and a controller comprising a neural network embedded in the actor-critic framework and which can be tuned according to reinforcement learning based tuning including anti-windup tuning.

Method and system for directly tuning PID parameters using a simplified actor-critic approach to reinforcement learning

A method and system for reinforcement learning can involve applying a finite-difference approach to a controller, and tuning the controller in response to applying the finite-difference approach by taking a state as an entirety of a closed-loop step response. The disclosed finite-different approach is based on a random search to tuning the controller, which operates on the entire closed-loop step-response of the system and iteratively improves the gains towards a desired closed-loop response. This allows for prescribing stability requirement into the reward function without any modeling procedures.

Application of simple random search approach for reinforcement learning to controller tuning parameters

A method includes acquiring process data collected in an industrial process control and automation system. The method also includes reducing a dimension space of the process data by combining two or more parameters of the process data or examining a frequency response of the process data. The method further includes determining a change in a process based on a change in the process data in the reduced dimension space. The method also includes outputting a result based on the determined change in the process.

System and method for monitoring changes in process dynamic behavior by mapping parameters to a lower dimensional space

A method includes identifying costs associated with different outcomes of a failure prediction algorithm. The algorithm is configured to predict one or more faults with at least one piece of industrial equipment. The different outcomes include both successful and unsuccessful predictions by the algorithm. The method also includes identifying a threshold value for the algorithm using the costs, where the threshold value is used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed. The method further includes providing the threshold value to the algorithm. The threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. In addition, the method can include generating a signal indicating whether maintenance is needed based on a comparison of an indicator value calculated using the algorithm and the threshold value.

Cost-driven system and method for predictive equipment failure detection

A method includes identifying a statistical performance of a monitoring rule associated with an asset monitoring system. The monitoring rule includes logic configured to identify one or more faults with at least one asset, and the statistical performance includes an effectiveness of the monitoring rule in identifying the one or more faults. The method also includes identifying an economic performance of the monitoring rule, where the economic performance is based on costs associated with different outcomes of the monitoring rule. The method further includes updating or replacing the monitoring rule based on the economic performance.

Calibration technique for rules used with asset monitoring in industrial process control and automation systems

A system and approach for catalyst model parameter identification with modeling accomplished by an identification procedure that may incorporate a catalyst parameter identification procedure which may include determination of parameters for a catalyst device, specification of values for parameters and component level identification. Component level identification may be of a thermal model, adsorption and desorption, and chemistry. There may then be system level identification to get a final estimate of catalyst parameters.

Approach for aftertreatment system modeling and model identification

A method includes receiving information associated with operation of multiple pieces of industrial equipment at multiple sites. The multiple pieces of industrial equipment are of a same or similar type, and the information represents different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment. The method also includes analyzing the information to identify correlations in the information associated with one or more conditions involving the pieces of industrial equipment. The method further includes, based on the analyzing, generating one or more monitoring rules or routines to be used to identify the one or more conditions. The multiple pieces of industrial equipment could include machines with rotating components, machines with heat transfer equipment, or general process equipment.

System and method for asset fleet monitoring and predictive diagnostics using analytics for large and varied data sources

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Vancouver, Canada

Gregory Edward Stewart