Systems and methods for data collection in an industrial environment are disclosed. A plurality of input sensors communicatively coupled to a controller, a data collection circuit structured to collect output data from a plurality of input sensors, and a machine learning data analysis circuit structured to receive the output data and learn received output data patterns indicative of an outcome, wherein the machine learning data analysis circuit is structured to learn received output data patterns by being seeded with a model based on industry-specific feedback.

Systems for self-organizing collection and storage in a distribution environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the distribution environment, wherein the sensor inputs sense at least one of an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system selected from a group consisting of a power system, a conveyor system, a robotic transport system, a robotic handling system, a packing system, a cold storage system, a hot storage system, a refrigeration system, a vacuum system, a hauling system, a lifting system, an inspection system, and a suspension system. A system may further include a self-organizing system for: a storage operation of the data, a data collection operation, or a selection operation.

Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels, wherein at least one input channel is connected to a high data rate source; a data storage structured to store detection parameters for the plurality of input channels, wherein a high data rate detection parameter is stored, wherein the high data rate detection parameter comprises at least a portion of data from the high data rate source; a data analysis circuit structured to analyze the plurality of detection values by evaluating a data handling constraint of the monitoring system with respect to the high data rate detection parameter; and a response circuit structured to adjust a data selection parameter to thereby adjust a data volume handled by the monitoring system in response to the data handling constraint.

An apparatus, methods and systems for network-sensitive data collection related to a process in an industrial environment are disclosed. The system can include a data collector communicatively coupled to a plurality of input channels and to a network infrastructure, each of the plurality of input channels communicatively coupled to at least one sensor of the industrial environment, a data storage circuit structured to store a plurality of collector routes and wherein the data collector receives collected data from the plurality of input channels utilizing a collector route, a data analysis circuit structured to determine a data collection quality parameter and interpret the collected data to determine a state value of the industrial environment and an analysis response circuit structured to adjust the selected one of the plurality of collector routes in response to one of the data collection quality parameter or the state value of the industrial environment.

Methods and systems for data collection in an industrial environment include a data collector communicatively coupled to a plurality of input channels, wherein at least one of the input channels is connected to a vibration detection facility coupled to a plurality of vibration components. A data storage stores a plurality of vibration patterns for the plurality of vibration components in a library of vibration patterns. A data acquisition circuit interprets a plurality of detection values, each comprising a representation of collected data corresponding to at least one of the plurality of input channels. A data analysis circuit analyzes the plurality of detection values to determine if one of the plurality of vibration components has a recognized vibration pattern corresponding to a stored vibration pattern from the library of vibration patterns. A response circuit adjusts a process of the environment in response to the vibration component having the recognized vibration pattern.

An apparatus, methods and systems for a monitoring system for data collection in a vehicle are disclosed. The system can include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to input received from at least one of a plurality of input sensors, each of the plurality of input sensors operatively coupled to at least one of a plurality of components of the vehicle, a data analysis circuit structured to determine a state value, wherein the data analysis circuit includes a pattern recognition circuit structured to determine the state value by analyzing a subset of the plurality of detection values and at least one external detection value using at least one of a neural net or an expert system, and an analysis response circuit structured to adjust a parameter of the vehicle in response to the state value.

Systems, methods and apparatus for modifying a data collection trajectory for conveyors are described. An example system may include a data acquisition circuit to interpret a plurality of detection values, each corresponding to at least one of a plurality of input sensors communicatively coupled to the data acquisition circuit. The system may further include a data storage circuit to store specifications and anticipated state information for a plurality of conveyor types and an analysis circuit to analyze the plurality of detection values relative to specifications and anticipated state information to determine a conveyor performance parameter. A response circuit may initiate an action in response to the conveyor performance parameter.

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.

An insert for an electrical panel including an insulative block including a first edge, second edge, a pair of sides, a first end, and a second end. The insert further includes at least one void defined in the insulative block extending from the second edge into the insulative block.

An insert for an electrical panel including an insulative block including a first edge, second edge, a pair of sides, a first end, and a second end. The insert further includes at least one void defined in the insulative block extending from the second edge into the insulative block.