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.

A test system for testing a control unit of a system includes a management server which is configured to provide predefined test instructions, a monitoring system, and a number of output units. The monitoring system is configured to convert test instructions provided by the management server into operating instructions for setting a test configuration on a control unit of a system using predefined assignment logic. The monitoring system is also configured to divide operating instructions for setting the test configuration into partial instructions for setting a partial configuration on the control unit and to temporally and/or logically classify the partial instructions. Respective output units of the number of output units are configured to output the partial instructions transmitted by the monitoring system.

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.

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.

Systems, methods and apparatus for data collection in an industrial environment having wearable haptic stimulators are disclosed. Data received from a plurality of sensors operationally coupled to a machine of an industrial environment, where the data is representative of a sensed condition, may be used to determine at least one haptic stimulation that corresponds to the received data. In response to the determined haptic stimulation, at least one signal may be sent to at least one wearable haptic stimulator, wherein the wearable haptic stimulator is responsive to the signal.

Systems, methods and apparatus for monitoring data collection are disclosed. A system according to one disclosed non-limiting embodiment of the present disclosure can include a plurality of input sensors operatively coupled to a component in a power station, the plurality of input sensors communicatively coupled to a data collector having a controller, the controller including: a data collection band circuit structured to determine a collection parameter for at least one of the plurality of sensors from which to process output data, and a machine learning data analysis circuit structured to receive output data and learn output data patterns indicative of a state of the power station, wherein the monitoring system adjusts an operating parameter of a component of the power station based on one of a mismatch or a match of the output data pattern and the state of the power station.

Embodiments described herein provide a system for facilitating comprehensive control data for a device. During operation, the system determines one or more properties of the device that can be applied to empirical data of the device. The empirical data can be obtained based on experiments performed on the device. The system applies the one or more properties to the empirical data to obtain derived data and learns an efficient policy for the device based on both empirical and derived data. The efficient policy indicates one or more operations of the device that can reach a target state from an initial state of the device. The system then determines an operation for the device based on the efficient policy.