Method for data collection and frequency analysis with self-organization functionality
A system and method for data collection and frequency analysis with self-organization functionality includes analyzing with a processor a plurality of sensor inputs, sampling with the processor data received from at least one of the plurality of sensor inputs at a first frequency, and self-organizing with the processor a selection operation of the plurality of sensor inputs.
1. A method comprising:
analyzing with a processor a plurality of sensor inputs;
sampling with the processor data received from at least one of the plurality of sensor inputs at a first frequency; and
self-organizing with the processor a selection operation of the plurality of sensor inputs, wherein the selection operation comprises:
receiving a signal relating to at least one condition of an industrial environment; and
based, at least in part, on the signal, changing at least one of the sensor inputs analyzed and sampling the data received from at least one of the plurality of sensor inputs at a second frequency,
wherein the selection operation further comprises identifying a target signal to be sensed,
wherein the selection operation further comprises:
identifying other data collectors sensing in a same signal band as the target signal to be sensed; and
based on the identified other data collectors, changing at least one of the sensor inputs analyzed and a frequency of the sampling;
wherein the selection operation further comprises:
receiving data indicative of one or more environmental conditions near a target associated with the target signal;
comparing the received one or more environmental conditions of the target with past environmental conditions near the target or another target similar to the target; and
based, at least in part, on the comparison, changing at least one of the sensor inputs analyzed and a frequency of the sampling.
2. The method of claim 1 , wherein the at least one condition of the industrial environment is a signal-to-noise ratio of the sampled data.
3. The method of claim 1 , wherein the selection operation further comprises:
identifying one or more non-target signals in a same frequency band as the target signal to be sensed; and
based, at least in part, on the identified one or more non-target signals, changing at least one of the sensor inputs analyzed and a frequency of the sampling.
4. The method of claim 1 , wherein the selection operation further comprises:
identifying a level of activity of a target associated with the target signal to be sensed; and
based, at least in part, on the identified level of activity, changing at least one of the sensor inputs analyzed and a frequency of the sampling.
5. The method of claim 1 , wherein the selection operation further comprises transmitting at least a portion of the received sampling data to another data collector according to a predetermined hierarchy of data collection.
6. A method for data collection in an industrial environment having self-organization functionality, comprising:
analyzing at a data collector a plurality of sensor inputs from one or more sensors, wherein at least one of the plurality of sensor inputs corresponds to a vibration sensor providing frequency data corresponding to a component of the industrial environment;
sampling data received from the plurality of sensor inputs;
receiving data indicative of at least one condition of the industrial environment in proximity to the component of the industrial environment;
transmitting at least a portion of the received sampled data to another data collector according to a predetermined hierarchy of data collection;
receiving feedback via a network connection relating to a quality or sufficiency of the transmitted data;
analyzing the received feedback, and based, at least in part, on the analysis of the received feedback, changing at least one of: the sensor inputs analyzed, the frequency of sampling, the data stored, and the data transmitted
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,
wherein the selection operation comprises:
receiving a signal relating to at least one condition of the component of the industrial environment; and
based, at least in part, on the signal, changing a frequency of the sampling of the one of the plurality of sensor inputs corresponding to the vibration sensor.
7. The method of claim 6 , wherein the at least one condition of the industrial environment is a signal-to-noise ratio of the sampled data.
8. The method of claim 6 , wherein at least one of the one or more sensors forms a part of the data collector.
9. The method of claim 6 , wherein at least one of the one or more sensors is external to the data collector.
10. The method of claim 6 , wherein the vibration sensor is configured to sense at least one of: an operational mode, a fault mode, or a health status of the component of the industrial environment.
11. A method for data collection in an industrial environment having self-organization functionality, comprising:
analyzing at a data collector a plurality of sensor inputs from one or more sensors;
sampling data received from the sensor inputs; and
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,
wherein the selection operation comprises:
identifying a target signal to be sensed;
receiving a signal relating to at least one condition of the industrial environment,
based, at least in part, on the signal, changing at least one of the sensor inputs analyzed and a frequency of the sampling;
receiving data indicative of environmental conditions near a target associated with the target signal;
transmitting at least a portion of the received sampling data to another data collector according to a predetermined hierarchy of data collection;
receiving feedback via a network connection relating to one or more yield metrics of the transmitted data;
analyzing the received feedback, and based on the analysis of the received feedback, changing at least one of the sensor inputs analyzed, the frequency
of sampling, the data stored, and the data transmitted.
12. The method of claim 11 , wherein the at least one condition of the industrial environment is a signal-to-noise ratio of the sampled data.
13. The method of claim 11 , wherein at least one of the one or more sensors forms a part of the data collector.
14. The method of claim 11 , wherein at least one of the one or more sensors is external to the data collector.
15. The method of claim 11 , wherein the plurality of sensor inputs is configured to sense at least one of an operational mode, a fault mode and a health status of at least one target system.
16. A method for data collection in an industrial environment having self-organization functionality, comprising:
analyzing at a data collector a plurality of sensor inputs from one or more sensors;
sampling data received from the sensor inputs; and
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,
wherein the selection operation comprises:
identifying a target signal to be sensed,
receiving a signal relating to at least one condition of the industrial environment,
based, at least in part, on the signal, changing at least one of the sensor inputs analyzed and a frequency of the sampling,
receiving data indicative of environmental conditions near a target associated with the target signal,
transmitting at least a portion of the received sampling data to another data collector according to a predetermined hierarchy of data collection,
receiving feedback via a network connection relating to a quality or sufficiency of the transmitted data,
analyzing the received feedback, and
based, at least in part, on the analysis of the received feedback, executing a dimensionality reduction algorithm on the sensed data.
17. The method of claim 16 , wherein the dimensionality reduction algorithm is one or more of a Decision Tree, a Random Forest, a Principal Component Analysis, a Factor Analysis, a Linear Discriminant Analysis, Identification based on correlation matrix, a Missing Values Ratio, a Low Variance Filter, a Random Projection, a Nonnegative Matrix Factorization, a Stacked Auto-encoder, a Chi-square or Information Gain, a Multidimensional Scaling, a Correspondence Analysis, a Factor Analysis, a Clustering, and a Bayesian Models.
18. The method of claim 16 , wherein the dimensionality reduction algorithm is performed at the data collector.
19. The method of claim 16 , wherein executing the dimensionality reduction algorithm comprises sending the sensed data to a remote computing device.
20. The method of claim 16 , wherein the at least one condition of the industrial environment is a signal-to-noise ratio of the sampled data.
21. The method of claim 16 , wherein at least one of the one or more sensors forms a part of the data collector.
22. The method of claim 16 , wherein at least one of the one or more sensors is external to the data collector.
23. The method of claim 16 , wherein the plurality of sensor inputs is configured to sense at least one of an operational mode, a fault mode and a health status of at least one target system.