A system for changing a sensed parameter group for a motor includes a data collector communicatively coupled to a plurality of input sensors, each of the plurality of input sensors operatively coupled to a motor, wherein the motor comprises a component of an industrial environment; a controller, comprising: a data acquisition circuit structured to interpret a plurality of detection values corresponding to a sensed parameter group, wherein the sensed parameter group comprises at least a portion of the plurality of input sensors; a pattern recognition circuit structured to determine a recognized pattern value in response to the plurality of detection values; and a sensor learning circuit structured to update the sensed parameter group in response to the recognized pattern value.

Methods and systems for data collection in an industrial refining environment with haptic feedback and data storage control are disclosed. A system may include a data collector communicatively coupled to a plurality of input channels, 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, wherein the plurality of collector routes each include a different data collection routine, a data acquisition circuit structured to interpret the collected data and determine an occurrence of an anomalous condition, a data analysis circuit to evaluate a data storage constraint of the monitoring system and to adjust a volume of collected data stored in response to the evaluation, and a haptic user device for generating a haptic stimulation in response to an occurrence of a specified anomalous condition in the refining environment.

A monitoring system for data collection related to a production line of an industrial environment includes a data storage structured to store a plurality of data collection templates, each of the plurality of data collection templates comprising a data collection routine; a data collector structured to interpret a plurality of detection values that correspond to a plurality of input channels, wherein the plurality of detection values are obtained according to a data collection routine corresponding to a selected one of the plurality of data collection templates; wherein the data storage is further structured to store at least a portion of the plurality of detection values; a data analysis circuit structured to interpret at least a subset of the detection values to determine a state value corresponding to one of a process or a component of the production line; and an expert system circuit structured to perform a data collection modification by performing one of: adjusting the data collection routine corresponding to the selected one of the plurality of data collection templates; or selecting a different one of the plurality of data collection templates.

Systems and methods for data collection in an industrial production line are disclosed. A systems may 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 a data acquisition and analysis circuit for receiving the collected data and analyzing the received collected data using a neural network to determine an occurrence of an anomalous condition of at least one component.

A system for changing a sensed parameter group for a pump or fan includes a data collector communicatively coupled to a plurality of input sensors, each of the plurality of input sensors operatively coupled to a one of a pump or a fan, wherein the one of the pump or the fan comprises a component of an industrial environment; a controller, comprising: a data acquisition circuit structured to interpret a plurality of detection values corresponding to a sensed parameter group, wherein the sensed parameter group comprises at least a portion of the plurality of input sensors; a pattern recognition circuit structured to determine a recognized pattern value in response to the plurality of detection values; and a sensor learning circuit structured to update the sensed parameter group in response to the recognized pattern value.

Systems and method for data collection in an industrial environment can include interpreting a plurality of sensor data values, each sensor operatively coupled to at least one of a plurality of components in the industrial environmental. In response to at least a portion of the plurality of sensor data values, determining a recognized pattern value and providing a system characterization value for the industrial system in response to the recognized pattern value.

System and methods for data collection, processing, and utilization of signals in an industrial environment are disclosed. A data acquisition circuit structured to interpret a plurality of detection values from a plurality of input sensors communicatively coupled to the data acquisition circuit, a peak detection circuit to determine at least one peak value in response to the plurality of detection values, a peak response circuit to select at least one detection value in response to the at least one peak value, a communication circuit to communicate the at least one selected detection value to a remote server, and a monitoring application on the remote server to receive the at least one selected detection value, jointly analyze received detection values and recommend an action in response are disclosed herein.

Systems and methods for self-organizing data collection based on a production environment parameter are disclosed. An example monitoring system for data collection in a production environment may include a data collector coupled to a plurality of input channels coupled to a plurality of sensors co-located on a component of the production environment and to a network infrastructure; a data storage to store collected data; a data acquisition circuit to interpret a plurality of detection values, each of the plurality of detection values corresponding to at least one of the input channels; an expert system to self-organize data collection, wherein the self-organizing is based on a production parameter of the production environment; and wherein the data collector is responsive to the self-organizing to change a collection of the data.

A method may include receiving, by respective processing circuitry of one or more power modules of an industrial automation device, a control signal from a controller of the industrial automation device. The power modules may include driver circuitry and a power converter that may provide power to a motor based on the signal. The method may also include, detecting, by the respective processing circuitry, a lack of communication from the controller based on the signal, and, in response to detecting the lack of communication from the controller, transmitting, by the respective processing circuitry, a first command to gating signal enable circuitry to disable the driver circuitry, and transmitting, by the respective processing circuitry, a second command to driver power circuitry to prevent power from being provided to the driver circuitry.

A method for predicting end-of-life for a component includes determining a baseline lifetime model for a component connected to a machine functional safety system. The component is part of a system with physical devices. The method includes monitoring environmental conditions and usage conditions of the component and modifying the baseline lifetime model based on the monitored environmental and usage conditions to produce a modified lifetime model for the component. The method includes tracking a lifetime progress of the component with respect to the modified lifetime model and sending an alert in response to lifetime progress of the component reaching a lifetime threshold associated with the modified lifetime model.