Methods and devices for self organization of data collection are disclosed. A device can include a data acquisition circuit to request and receive a plurality of detection values, each of the plurality of detection values corresponding to a plurality of input sensors forming a self-organizing data pool and communicatively coupled to the data acquisition circuit, a data storage component to store specifications and anticipated state information for the plurality of input sensors of the data pool, and a response circuit to provide the data acquisition circuit with direction regarding a manner in which the plurality of detection values is requested.

Systems and methods for data collection and detection of noise patterns. A system may 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 an industrial machine, a library 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 industrial machines, and a user interface for accessing the plurality of noise patterns of the noise pattern marketplace.

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.

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.

Systems and methods for data collection in an industrial environment are disclosed. A system can include a plurality of analog sensors, wherein each of the plurality of analog sensors is operationally coupled to a respective data collection point of a machine component, and generates a respective stream of detection values. A data acquisition and analysis circuit can receive the respective stream of detection values and analyze the respective stream of detection values using an expert system analysis circuit, wherein the expert system analysis circuit determines an occurrence of an anomalous condition based on an analysis of the respective stream of detection values, wherein the expert system analysis circuit utilizes a neural network including one of a probabilistic, a time delay, and a convolutional neural network.

Systems and methods for data collection and detection of motor noise patterns are disclosed. A system may include a data collector communicatively coupled to at least one input channel, wherein the at least one input channel is operatively coupled to a vibration detection facility structured to detect a motor noise pattern of a motor, a library to store the detected motor noise pattern, an interface circuit structured to make the detected motor noise pattern available to a motor noise pattern data marketplace including a plurality of motor noise patterns from a plurality of motors, and a user interface for accessing at least one of the plurality of motor noise patterns of the motor noise pattern marketplace.

Methods and systems for data collection in a chemical or pharmaceutical production process with haptic feedback and control of data communication are disclosed. A system can include a data collector to collect data from plurality of input channels based on a selected data collection routine, a data storage to store a plurality of collector routes and collected data, wherein the plurality of collector routes each includes a different data collection routine, a data acquisition circuit to interpret the collected data and determine an occurrence of an anomalous condition, a data analysis circuit to analyze the collected data by evaluating a data communication constraint of the monitoring system and adjusting a volume of collected data communicated between the input channels and the data storage, and a haptic user device for generating a haptic stimulation in response to an occurrence of a specified anomalous condition.

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.

Systems and methods for data collection for an industrial heating process are disclosed. The system according to one embodiment 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 industrial heating 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 industrial heating process.