G05B23/0208

SYSTEMS AND METHODS FOR LEARNING DATA PATTERNS PREDICTIVE OF AN OUTCOME

System and methods for learning data patterns predictive of an outcome are described. An example system may include a plurality of input sensors communicatively coupled to a controller; a data collection circuit structured to collect output data from the plurality of input sensors; and a machine learning data analysis circuit structured to receive the output data, learn received output data patterns indicative of an outcome, and learn a preferred input data collection band among a plurality of available input data collection bands. The machine learning data analysis circuit may be structured to learn received output data patterns by being seeded with a model based on industry-specific feedback. The outcome may be at least one of: a reaction rate, a production volume, or a required maintenance.

SYSTEMS FOR SELF-ORGANIZING DATA COLLECTION IN AN INDUSTRIAL ENVIRONMENT

Systems for self-organizing data collection in an industrial environment are disclosed. An example system may include a self-propelled mobile data collector for handling a plurality of sensor inputs from sensors in the industrial environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may include a self-organizing system for self-organizing at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system organizes a swarm of self-propelled mobile data collectors to collect data from a plurality of target systems in the industrial environment.

SYSTEMS FOR SELF-ORGANIZING DATA COLLECTION AND STORAGE IN A POWER GENERATION ENVIRONMENT

Systems for self-organizing data collection and storage in a power generation environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the power generation system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.

METHODS AND SYSTEMS FOR SENSOR FUSION IN A PRODUCTION LINE ENVIRONMENT

Systems and methods for data collection in an industrial production system including a plurality of components are disclosed. An example system may include a sensor communication circuit structured to interpret a plurality of data values from a sensed parameter group, the sensed parameter group including a plurality of sensors including a vibration sensor and a temperature sensor, and the plurality of sensors operatively coupled to at least one of the plurality of components; a data analysis circuit structured to detect an operating condition of the industrial production system based on detecting that the data values from the vibration sensor indicate a vibration pattern that matches a stored vibration fingerprint together with detecting that the data values from the temperature sensor indicate a change in a temperature; and a response circuit structured to modify a production-related operating parameter of the industrial production system in response to the detected operating condition.

Method and system for adjusting an operating parameter on a production line

Systems, methods and apparatus for data collection in an industrial environment are disclosed. A system according to one embodiment can include a plurality of input sensors operatively coupled to a production line, the plurality of sensors communicatively coupled to a data collector having a controller, the controller including: a data collection band circuit structured to determine at least one collection parameter for at least one of the plurality of sensors from which to process output data, a machine learning data analysis circuit structured to receive output data from the at least one of the plurality of sensors and learn output data patterns indicative of a state of the production line, and a response circuit structured to adjust an operating parameter of a component of the production line based on one of a mismatch or a match of the output data pattern and the state of the production line.

Systems and methods for adjusting process parameters in a production environment

Systems and methods for process monitoring through data collection in a production environment can include a data collector communicatively coupled to a plurality of input channels, each input channel connected to a monitoring point from which data is collected, the collected data providing a plurality of process parameter values for the production environment; a data storage structured to store collected data from the plurality of input channels; a data acquisition circuit structured to interpret the plurality of process parameter values from the collected data; a data analysis circuit structured to analyze the plurality of process parameter values to detect a process condition associated with the production environment; and a response circuit structured to adjust an operational process for the production environment in response to the detected process condition.

SYSTEMS FOR SELF-ORGANIZING DATA COLLECTION AND STORAGE IN A MANUFACTURING ENVIRONMENT

Systems for self-organizing data collection and storage in a manufacturing environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the manufacturing system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.

METHODS AND SYSTEMS FOR DETECTION IN AN INDUSTRIAL INTERNET OF THINGS DATA COLLECTION ENVIRONMENT WITH INTELLIGENT DATA MANAGEMENT FOR INDUSTRIAL PROCESSES INCLUDING SENSORS

An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of sensors to collect data, a data storage structured to store a plurality of data collection management plans, a data acquisition circuit structured to interpret a plurality of detection values from the collected data, and a data analysis circuit structured to analyze the collected data and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of sensors.

Method and system of a noise pattern data marketplace for a power station

Systems and methods for interactions with power station noise patterns are disclosed. A system can include a data collector communicatively coupled to a plurality of input channels, wherein at least one of the plurality of input channels is operatively coupled to a vibration detection facility structured to detect a noise pattern of a power station, a library structured to store the detected noise pattern, an interface circuit structured to make the noise pattern available to a noise pattern marketplace, the noise pattern marketplace including a plurality of noise patterns from a plurality of power stations; and a user interface for accessing at least one of the plurality noise patterns of the noise pattern marketplace.

Methods and systems for industrial internet of things data collection in downstream oil and gas environment

A system for monitoring an oil and gas process includes a data acquisition circuit structured to interpret a plurality of detection values corresponding to input received from a detection package which includes at least one of a plurality of input sensors each operatively coupled to at least one of a plurality of components of an industrial production process; a data analysis circuit structured to analyze a subset of the plurality of detection values to determine a status parameter; and an analysis response circuit structured to adjust the detection package in response to the status parameter, wherein the plurality of available sensors have at least one distinct sensing parameter selected from the sensing parameters consisting of: input ranges, sensitivity values, locations, reliability values, duty cycle values, sensor types, and maintenance requirements.