Systems, methods and apparatus for data monitoring are disclosed. A system may include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to at least one of a plurality of input sensors communicatively coupled to the data acquisition circuit, a data storage circuit structured to store specifications and anticipated state information for a plurality of bearing types, a bearing analysis circuit structured to analyze the plurality of detection values relative to specifications and anticipated state information to determine a bearing performance parameter, and a response circuit structured to initiate an action in response to the bearing performance parameter.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system can comprise a plurality of distinct data-handling layers. The plurality of distinct data-handling layers can comprise an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in the IIoT system; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; an adaptive intelligent systems layer that facilitates the coordinated development and deployment of intelligent systems in the IIoT system; and an industrial management application platform layer that includes a plurality of applications and that manages the platform in a common application environment. The adaptive intelligent systems layer can include a robotic process automation system that develops and deploys automation capabilities for one or more of the plurality of industrial entities in the IIoT system.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system can comprise a plurality of distinct data-handling layers. The plurality of distinct data-handling layers can comprise an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in the IIoT system; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; an adaptive intelligent systems layer that facilitates the coordinated development and deployment of intelligent systems in the IIoT system; and an industrial management application platform layer that includes a plurality of applications and that manages the platform in a common application environment. The adaptive intelligent systems layer can include a robotic process automation system that develops and deploys automation capabilities for one or more of the plurality of industrial entities in the IIoT system.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system can comprise a plurality of distinct data-handling layers. The plurality of distinct data-handling layers can comprise an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in the IIoT system; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; an adaptive intelligent systems layer that facilitates the coordinated development and deployment of intelligent systems in the IIoT system; and an industrial management application platform layer that includes a plurality of applications and that manages the platform in a common application environment. The adaptive intelligent systems layer can include a robotic process automation system that develops and deploys automation capabilities for one or more of the plurality of industrial entities in the IIoT system.

A system or method for determining virtual data of a system, relative to a measurement point having a sensor located nearby, is determined by a controller. The system calculates modeled data at the measurement point, filters the modeled data to determine filtered data, and calculates a differential between the modeled data and the filtered data to determine a compensation term. The system also determines raw-sensed data from the sensor at the measurement point, and combines that raw-sensed data with the compensation data to calculate the virtual data at the measurement point. In some configurations, the modeled data is determined from a physics-based model. Furthermore, filtering the modeled data may include using a low-pass filter, and a time constant for the low-pass filter may be calculated based on operating conditions of the system.

A method for setting alarm levels for a machine provides defining at least one condition indicator reflecting the condition of the machine with respect to a defect to be monitored of the machine, the at least one condition indicator defined from machine kinematic data, recording measurements of process related parameters during a predetermined period during which the machine is operating normally, calculating at least one condition indicator value for the at least one condition indicator) using machine condition data, determining a graph of the at least one condition indicator value as a function of a first process related parameter chosen from the measured process related parameters, dividing the graph into operating classes, each operating class being representative of different operating conditions of the machine, calculating an alarm level value for each operating class, setting the determined alarm level value at the midpoint of each operating class.

System for data collection and monitoring in an industrial environment are disclosed. A data acquisition circuit may interpret a plurality of detection values, each of the plurality of detection values corresponding to at least one of a plurality of input sensors. A data storage circuit may store sensor specifications, anticipated state information and detected values for use by a signal evaluation to determine a sensor overload status, a sensor fault status or a sensor validity value of at least one sensor in response to the plurality of detection values and at least one of an anticipated state information or a sensor specification. A response circuit may perform an operation in response to one of a sensor overload status, a sensor health status, or a sensor validity status.

Systems, methods and apparatus for network sensitive data collection are disclosed. A system according to one embodiment can include a plurality of input sensors operatively coupled to a component of an industrial environment and a data collector having a controller. The controller may include: a transmission environment circuit to determine a transmission condition corresponding to transmission of a subset of output data, a network management circuit to update a sensor data transmission protocol, a data collection band circuit to determine at least one collection parameter, a machine learning data analysis circuit to receive output data and learn at least one output data pattern, and a response circuit to adjust an operating parameter of the component based on one of a mismatch or a match of the at least one output data pattern and the state of the component.

A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.

Monitoring, systems and methods for data collection in an industrial environment are disclosed. A system may include a data collector communicatively coupled to a plurality of input channels and to a network infrastructure, wherein the data collector collects data based on a selected data collection routine, a data storage structured to store a plurality of collector routes and collected data, 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 sense a change in operation and determine an aggregate rate of data being collected from the plurality of input channels. If the aggregate rate exceeds a throughput parameter the data analysis circuit alters the data collection to reduce the amount of data collected or, based on the sensed change, modify a collector route.