Patent classifications
Y02P80/00
Data collection systems with pattern analysis for an industrial environment
The present disclosure describes monitoring systems for data collection in an industrial environment. A system can include a data collection circuit to collect output data from a plurality of sensors such as vibration sensors, ambient environment condition sensors and local sensors for collecting non-vibration data proximal to a machine in the environment. The sensors may be communicatively coupled to a data collection circuit, and a machine learning data analysis circuit may receive the output data and learn received data patterns predictive of at least one of an outcome and a state. The monitoring system may determine if the output data matches a learned received output data pattern, wherein the data collection circuit collects data points from sensors based on the learned received output data patterns, the outcome, or the state.
Data collection systems and methods for updating sensed parameter groups based on pattern recognition
The present disclosure describes systems for data collection in an industrial environment. A system can include an industrial system including a plurality of components, at least one component operatively coupled to a sensor, and a sensor communication circuit to interpret a plurality of sensor data values in response to a sensed parameter group. A pattern recognition circuit may determine a recognized pattern value in response to at least a portion of the data values, wherein the recognized pattern value includes a secondary value. A sensor learning circuit may update the sensed parameter group in response to the recognized pattern value and adjust the interpreting the plurality of sensor data values in response to the updated sensed parameter group. The pattern recognition circuit and the sensor learning circuit iteratively determine the recognized pattern value and update the sensed parameter group to improve a sensing performance value.
Systems and methods for network-sensitive data collection
The present disclosure describes systems for self-organized, network-sensitive data collection in an industrial environment. A system can include an industrial system including a plurality of components, at least one operatively coupled to a sensor, a sensor communication circuit to interpret sensor data values, and a system collaboration circuit to communicate a portion of the data values to a storage target according to a sensor data transmission protocol. A transmission environment circuit may determine transmission conditions corresponding to the communication of the portion of data values to the storage target and a network management circuit update the data transmission protocol in response to the transmission conditions.
Systems and methods for network-sensitive data collection
The present disclosure describes systems for self-organized, network-sensitive data collection in an industrial environment. A system may include an industrial system with a plurality of components operatively coupled to sensors, a sensor communication circuit to interpret the data values from the sensors, and a system collaboration circuit to communicate at least a portion of the data values over a network to a storage target computing device according to a sensor data transmission protocol. A transmission environment circuit may determine transmission feedback corresponding to the communication of the data values over the network, and a network management circuit to update the sensor data transmission protocol in response to the transmission feedback.
Systems and methods for data collection including pattern recognition
The present disclosure describes systems and methods for data collection in an industrial environment. A method can include providing a plurality of sensors to components of an industrial system, interpreting the data values from the sensors in response to a sensed parameter group, the group including a fused plurality of sensors. The method may also include determining a recognized pattern value comprising a secondary value determined in response to the data values, updating the sensed parameter group in response to the recognized pattern value, and adjusting the interpreting the data values in response to the updated sensed parameter group.
Systems and methods for data collection and data sharing in an industrial environment
The present disclosure describes systems for data collection in an industrial environment having a self-sufficient data acquisition box for capturing and analyzing data in an industrial process. A system can include a data circuit for analyzing a plurality of sensor inputs, a network control circuit for sending and receiving information related to sensor inputs to an external system, wherein the system provides sensor data to one or more similarly configured systems, and wherein the data circuit dynamically nominates a similarly configured system capable of providing sensor data to replace the system.
METHODS FOR SELF-ORGANIZING DATA COLLECTION AND STORAGE
Methods for data collection in an industrial environment having self-organization functionality are disclosed. A method may include analyzing a plurality of sensor inputs and sampling data received from the plurality of sensor inputs. The method may also include self-organizing at least one of: (i) a storage operation of the data; (ii) a collection operation of sensors that provide the plurality of sensor inputs, and (iii) a selection operation of the plurality of sensor inputs. The storage operation includes storing the data in a local database, and summarizing the data over a given time period to reduce a size of the data.
METHODS FOR SELF-ORGANIZING DATA COLLECTION AND STORAGE
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 and 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.
SYSTEMS FOR DATA COLLECTION AND STORAGE INCLUDING NETWORK EVALUATION AND DATA STORAGE PROFILES
Systems for data collection in an industrial environment are disclosed. A system may include a sensor communication circuit to interpret a plurality of sensor data values, a sensor data storage profile circuit to determine a data storage profile, the data storage profile comprising a data storage plan for the plurality of sensor data values. A system may also include a network coding circuit to provide a network coding value in response to the plurality of sensor data values and the data storage profile, and a sensor data storage implementation circuit to store at least a portion of the plurality of sensor data values in response to the data storage profile and the network coding value.
SYSTEMS FOR DATA COLLECTION AND SELF-ORGANIZING STORAGE INCLUDING ENHANCING RESOLUTION
Systems for data collection and self-organizing storage including enhanced resolution are disclosed. An example system includes an industrial system with a plurality of components, a subset of which is operatively coupled to a plurality of sensors which provide sensor values. An example system may further include self-organizing storage for at least a portion of the plurality of sensor values and a means for enhancing resolution of the sensor values in response to an enhanced data request value or an alert value. Enhanced resolution may include an enhanced spatial resolution, an enhanced time domain resolution, a greater number of the plurality of sensor values than a standard resolution of the plurality of sensor values, or a greater precision of at least one of the plurality of sensor values than the standard resolution of the plurality of sensor values.