Flowmeter as an asset

1. A method comprising:

receiving, by a data processor configured within a flow meter, diagnostic data characterizing operation of the flow meter configured within an industrial plant to monitor a flow rate of a fluid within a pipe associated with the industrial plant, wherein the diagnostic data includes a sound speed;

determining, by the data processor and based on the received diagnostic data, an asset state object characterizing a state of the flow meter; and

providing, by the data processor, the asset state object.

2. The method of claim 1 , wherein the diagnostic data includes a signal-to-noise ratio, a signal file, a per-channel sound speed, a per-channel wedge sound speed, a per-channel peak percentage, a temperature, and/or a peak percentage.

3. The method of claim 1 , wherein the asset state object is determined using an asset model engine including a predictive model and/or machine learning engine.

4. The method of claim 1 , wherein the state of the flow meter includes an indication of the flow meter's reliability.

5. The method of claim 4 , wherein the state of the flow meter includes an indication of a downgrade of measurement accuracy, a number of failures, a channel status, and/or an overall status associated with the flow meter.

6. The method of claim 1 , wherein the asset state object includes an indication of reliability corresponding to one or more sensors coupled to the flow meter.

7. The method of claim 6 , wherein the asset state object includes an indication of a deterioration in transmission and/or reception associated with the one or more sensors coupled to the flow meter.

8. The method of claim 6 , wherein the one or more sensors includes a transducer.

9. A system comprising:

at least one data processor configured within a flow meter; and

memory storing instructions configured to cause the at least one data processor to perform operations comprising:

receiving diagnostic data characterizing operation of the flow meter, wherein the diagnostic data includes a sound speed and the flow meter is configured within an industrial plant to monitor a flow rate of a fluid within a pipe associated with the industrial plant;

determining, based on the received diagnostic data, an asset state object characterizing a state of the flow meter; and

providing the asset state object.

10. The system of claim 9 , wherein the diagnostic data includes a signal-to-noise ratio, a signal file, a per-channel sound speed, a per-channel wedge sound speed, a per-channel peak percentage, a temperature, and/or a peak percentage.

11. The system of claim 9 , wherein the asset state object is determined using an asset model engine including a predictive model and/or machine learning engine.

12. The system of claim 9 , wherein the state of the flow meter includes an indication of the flow meter's reliability.

13. The system of claim 12 , wherein the state of the flow meter includes an indication of a downgrade of measurement accuracy, a number of failures, a channel status, and/or an overall status associated with the flow meter.

14. The system of claim 9 , wherein the asset state object includes an indication of reliability corresponding to one or more sensors coupled to the flow meter.

15. The system of claim 14 , wherein the asset state object includes an indication of a deterioration in transmission and/or reception associated with the one or more sensors coupled to the flow meter.

16. The system of claim 14 , wherein the one or more sensors includes a transducer.

17. A non-transitory computer readable medium storing instructions which, when executed by at least one data processor forming part of at least one computing system, cause the at least one data processor to implement operations comprising:

receiving diagnostic data characterizing operation of a flow meter configured within an industrial plant to monitor a flow rate of a fluid within a pipe associated with the industrial plant, the diagnostic data received by a data processor configured within the flow meter, wherein the diagnostic data includes a sound speed;

determining, based on the received diagnostic data and by the data processor configured within the flow meter, an asset state object characterizing a state of the flow meter; and

providing, by the data processor configured within the flow meter, the asset state object.

18. The non-transitory computer readable medium of claim 17 , wherein the diagnostic data includes a signal-to-noise ratio, a signal file, a per-channel sound speed, a per-channel wedge sound peed, a per-channel peak percentage, a temperature, and/or a peak percentage.

19. The non-transitory computer readable medium of claim 17 , wherein the asset state object is determined using an asset model engine including a predictive model and/or machine learning engine.

20. The non-transitory computer readable medium of claim 17 , wherein the state of the flow meter includes an indication of the flow meter's reliability.

21. The non-transitory computer readable medium of claim 20 , wherein the state of the flow meter includes an indication of a downgrade of measurement accuracy, a number of failures, a channel status, and/or an overall status associated with the flow meter.

22. The non-transitory computer readable medium of claim 17 , wherein the asset state object includes an indication of reliability corresponding to one or more sensors coupled to the flow meter.

23. The non-transitory computer readable medium of claim 22 , wherein the asset state object includes an indication of a deterioration in transmission and/or reception associated with the one or more sensors coupled to the flow meter.

24. The non-transitory computer readable medium of claim 22 , wherein the one or more sensors includes a transducer.