Data collection systems and methods for updating sensed parameter groups based on pattern recognition

1. A system for data collection in an industrial environment, the system comprising:

an industrial system comprising a plurality of components, and a plurality of sensors each operatively coupled to at least one of the plurality of components;

a sensor communication circuit structured to interpret a plurality of sensor data values in response to a sensed parameter group;

a pattern recognition circuit structured to determine a recognized pattern value in response to at least a portion of the plurality of sensor data values, wherein the recognized pattern value includes a secondary value comprising a value determined in response to the at least a portion of the plurality of sensor data values;

a sensor learning circuit structured to update the sensed parameter group in response to the recognized pattern value, wherein the sensor communication circuit is further structured to adjust the interpreting the plurality of sensor data values in response to the updated sensed parameter group; and

wherein the pattern recognition circuit is further structured to iteratively perform the determining the recognized pattern value and the sensor learning circuit is configured to iteratively update the sensed parameter group to improve a sensing performance value, wherein the sensing performance value comprises a signal-to-noise performance for detecting a value of interest in the industrial system.

2. The system of claim 1 , wherein the sensed parameter group comprises a fused plurality of sensors, and wherein the secondary value comprises a value determined in response to the fused plurality of sensors.

3. The system of claim 1 , further comprising, a system characterization circuit structured to determine a system characterization value for the industrial system in response to the recognized pattern value.

4. The system of claim 1 , further comprising a system collaboration circuit structured to interpret cloud-based data, wherein the cloud-based data comprises a second plurality of sensor data values, the second plurality of sensor data values corresponding to at least one offset industrial system, and wherein determining the recognized pattern value is further in response to the cloud-based data.

5. The system of claim 1 , wherein determining the recognized pattern value comprises performing at least one operation selected from the operations consisting of: determining a signal effectiveness of at least one sensor of the sensed parameter group and the updated sensed parameter group relative to a value of interest; determining a sensitivity of at least one sensor of the sensed parameter group and the updated sensed parameter group relative to the value of interest; determining a predictive confidence of at least one sensor of the sensed parameter group and the updated sensed parameter group relative to the value of interest; determining a predictive delay time of at least one sensor of the sensed parameter group and the updated sensed parameter group relative to the value of interest; determining a predictive accuracy of at least one sensor of the sensed parameter group and the updated sensed parameter group relative to the value of interest; determining a predictive precision of at least one sensor of the sensed parameter group and the updated sensed parameter group relative to the value of interest; and updating the recognized pattern value in response to external feedback.

6. The system of claim 1 , wherein the sensed parameter group comprises at least one of: i) a triaxial vibration sensor, ii) a vibration sensor and a second digital sensor that is not a vibration sensor, or iii) an analog sensor.

7. The system of claim 1 , wherein the sensing performance value further comprises a calculation efficiency for determining the secondary value.

8. The system of claim 1 , wherein the sensing performance value further comprises at least one of an accuracy or a precision of the secondary value.

9. The system of claim 1 , wherein the sensing performance value further comprises a redundancy capacity for determining the secondary value.

10. The system of claim 1 , wherein the sensing performance value further comprises a lead time value for determining the secondary value.

11. The system of claim 1 , further comprising, a machine learning data analysis circuit structured to receive the plurality of sensor data values as output data and learn received output data patterns predictive of at least one of a predicted outcome or a predicted state.

12. The system of claim 2 , wherein the secondary value comprises at least one value selected from the values consisting of: a virtual sensor output value; a process prediction value; a process state value; a component prediction value; a component state value; and a model output value having the sensor data values from the fused plurality of sensors as an input.

13. The system of claim 2 , wherein the fused plurality of sensors comprises at least one of the following combinations: a vibration sensor and a temperature sensor, a vibration sensor and a pressure sensor, a vibration sensor and an electric field sensor, a vibration sensor and a heat flux sensor, a vibration sensor and a galvanic sensor, or a vibration sensor and a magnetic sensor.

14. The system of claim 3 , wherein determining the system characterization value comprises performing at least one operation selected from a plurality of operations consisting of: determining a prediction value for one of the plurality of components; determining a future state value for one of the plurality of components; determining an anticipated maintenance health state information for one of the plurality of components; and determining a predicted maintenance interval for at least one of the plurality of components.

15. The system of claim 3 , wherein determining the system characterization value comprises performing at least one operation selected from a plurality of operations consisting of: determining a predicted outcome for a process associated with the industrial system; determining a predicted future state for a process associated with the industrial system; and determining a predicted off-nominal operation for the process associated with the industrial system.

16. The system of claim 3 , wherein determining the system characterization value comprises performing at least one operation selected from a plurality of operations consisting of: determining a predicted off-nominal operation for one of the plurality of components; determining a predicted fault operation for one of the plurality of components; determining a predicted exceedance value for one of the plurality of components, and determining a predicted saturation value for one of the plurality of sensors.

17. The system of claim 4 , wherein the pattern recognition circuit further iteratively improves the determining the recognized pattern value in response to the cloud-based data.

18. The system of claim 7 , wherein a value of the calculation efficiency comprises one or more determinations selected from the group consisting of: a processor operation to determine the secondary value, a memory utilization for determining the secondary value, a number of sensor inputs from the plurality of sensors for determining the secondary value, or supporting data long-term storage for supporting the secondary value.

19. The system of claim 11 , wherein the system is structured to determine if the output data matches a learned received output data pattern.

20. The system of claim 11 , wherein the system triggers an alert based on the predicted outcome or the predicted state.