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.

Systems and methods for data collection in an industrial environment are disclosed. An expert graphical user interface showing representations of components of an industrial machine to which sensors are attach is disclosed. The user interface may enable a user to select at least one of the components resulting in a search of a database of industrial machine failure modes for modes that correspond to the selected component. The corresponding failure mode may be presented to the user. The selection of the component may cause a controller to reference and implement a data collection template for configuring the system to automatically collect data from sensors associated with the selected component to detect at least one of the corresponding failure modes.

Systems and methods for monitoring a vehicle steering system are disclosed. An example monitoring system for a vehicle steering system may include a vehicle steering system comprising a rack, a pinion, and a steering column; a data acquisition circuit structured to interpret a plurality of detection values corresponding input sensors operationally coupled to the rack, the pinion, or the steering column; a data storage circuit structured to store specifications, and to buffer the plurality of detection values for a predetermined length of time. The example system may further include a timer circuit structured to generate a timing signal based on a first detected value of the plurality of detection values; a steering system analysis circuit to determine a steering system performance parameter in response to a relative phase difference and a response circuit structured to perform at least one operation in response to the steering system performance parameter.

Systems, methods and apparatus for data collection in an industrial environment are described. Signals from a plurality of analog sensors may be routed via an analog crosspoint switch which includes at least one high current output drive circuit suitable for routing an analog signal. The switch may be configured with data routing information from a data collection template where the routing includes switching a portion of the analog signals to a portion of the plurality of analog signal paths.

Method of back-calculation for determining candidate sources of data collection for data that contributes to a condition of an industrial machine are disclosed. Methods may include determining a condition of interest, following routes of data collection determined from a configuration and operational template, determining a data collection template configured for collecting and processing data from the contributing data, and updating the operational template of the data collection system in response to the determined data collection template.

Methods and systems for data collection for a chemical or pharmaceutical production process is disclosed. The system according to one disclosed non-limiting embodiment of the present disclosure can include a plurality of data collectors including a swarm of self-organized data collector members, wherein the swarm of self-organized data collector members organize to enhance data collection based on at least one of capabilities and conditions of the data collector members of the swarm, and wherein the plurality of data collectors is coupled to a plurality of input channels for acquiring collected data relating to the chemical or pharmaceutical production process, and a data acquisition and analysis circuit for receiving the collected data via the plurality of input channels and structured to analyze the received collected data using a neural network to monitor a plurality of conditions relating to the chemical or pharmaceutical production process.

Methods and systems for detection in an industrial Internet of Things (IoT) data collection environment with intelligent data collection and equipment package adjustment for oil and gas equipment are disclosed. An example monitoring system for data collection in an oil and gas production environment can include a data collector communicatively coupled to a plurality of input channels connected to data collection points operatively coupled to at least one piece of equipment of an equipment package of the oil and gas production environment. The system further includes a data acquisition circuit to interpret detection values from the plurality of input channels and a data analysis circuit to utilize an expert system diagnostic tool to identify an off-nominal process state based on the detection values. The system may further include a response circuit to adjust an equipment package parameter in response to the off-nominal process state.

Methods and systems for noise detection and removal in a motor are disclosed. An example system for monitoring a plurality of components of a motor in an industrial environment may include a data acquisition circuit to interpret a plurality of detection values, each detection value corresponding to a plurality of input sensors operationally coupled to the motor; a data processing circuit to utilize at least one of the detection values to perform at least one noise processing operation on at least a portion of the detection values; a signal evaluation circuit to determine a motor performance parameter in response to the noise processed portion of the of detection values; and a response circuit structured to perform at least one operation in response to the motor performance parameter.

Methods and systems for data collection in an industrial environment with haptic feedback and data communication and bandwidth control are disclosed. A system can include a data collector to collect data based on a selected data collection routine, a data storage to store a plurality of collector routes and data, a data acquisition circuit to interpret the data and determine an occurrence of an anomalous condition, a data analysis circuit to evaluate a data communication constraint and adjust a volume of data communicated between the input channels and the data storage, wherein the data analysis circuit determines an aggregate rate of data being collected, and, if the aggregate rate exceeds a current bandwidth allocation rate, request an increase to the current bandwidth allocation rate, and a haptic user device for generating a haptic stimulation in response an occurrence of a specified anomalous condition.